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Why use theories in qualitative research?

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• Peer review
• Scott Reeves , associate professor 1 ,
• Mathieu Albert , assistant professor 2 ,
• Ayelet Kuper , assistant professor 3 ,
• Brian David Hodges , associate professor and vice-chair (education) 2
• 1 Department of Psychiatry, Li Ka Shing Knowledge Institute, Centre for Faculty Development, and Wilson Centre for Research in Education, University of Toronto, 200 Elizabeth Street, Eaton South 1-565, Toronto, Ontario, Canada M5G 2C4
• 2 Department of Psychiatry and Wilson Centre for Research in Education
• 3 Department of Medicine, Sunnybrook Health Sciences Centre, and Wilson Centre for Research in Education
• Correspondence to: S Reeves scott.reeves{at}utoronto.ca

Theories such as interactionism, phenomenology, and critical theory can be used to help design a research question, guide the selection of relevant data, interpret the data, and propose explanations of causes or influences

Previous articles in this series have addressed several methodologies used in qualitative research. Qualitative researchers also rely heavily on theories drawn from the social sciences and humanities to guide their research process and illuminate their findings. This article discusses the role and use of three theoretical approaches commonly used by qualitative researchers in health domains: interactionism, phenomenology, and critical theory. It also explains why such theories are important for clinicians, for health policy, and for patient care.

Why is theory useful?

Theories provide complex and comprehensive conceptual understandings of things that cannot be pinned down: how societies work, how organisations operate, why people interact in certain ways. Theories give researchers different “lenses” through which to look at complicated problems and social issues, focusing their attention on different aspects of the data and providing a framework within which to conduct their analysis.

Just as there is no one way to understand why, for instance, a culture has formed in a certain way, many lenses can be applied to a problem, each focusing on a different aspect of it. For example, to study doctor-nurse interactions on medical wards, various theories can provide insights into different aspects of hospital and ward cultures. Box 1 indicates how each of the theories discussed in this paper could be used to highlight different facets of this research problem.

Box 1 How different theories help illuminate the culture of doctor-nurse interactions on a medical ward

Phenomenology.

A researcher using phenomenology would approach the study of doctor-nurse interprofessional interactions by exploring how individual doctors and nurses made sense of their ward-based interprofessional experiences. Such a study would aim to elicit, through interviews, the meanings each individual attached to their interactions and the classifications they employed to …

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Article contents

Qualitative data analysis and the use of theory.

• Carol Grbich Carol Grbich Flinders University
• https://doi.org/10.1093/acrefore/9780190264093.013.554
• Published online: 23 May 2019

The role of theory in qualitative data analysis is continually shifting and offers researchers many choices. The dynamic and inclusive nature of qualitative research has encouraged the entry of a number of interested disciplines into the field. These discipline groups have introduced new theoretical practices that have influenced and diversified methodological approaches. To add to these, broader shifts in chronological theoretical orientations in qualitative research can be seen in the four waves of paradigmatic change; the first wave showed a developing concern with the limitations of researcher objectivity, and empirical observation of evidence based data, leading to the second wave with its focus on realities - mutually constructed by researcher and researched, participant subjectivity, and the remedying of societal inequalities and mal-distributed power. The third wave was prompted by the advent of Postmodernism and Post- structuralism with their emphasis on chaos, complexity, intertextuality and multiple realities; and most recently the fourth wave brought a focus on visual images, performance, both an active researcher and an interactive audience, and the crossing of the theoretical divide between social science and classical physics. The methods and methodological changes, which have evolved from these paradigm shifts, can be seen to have followed a similar pattern of change. The researcher now has multiple paradigms, co-methodologies, diverse methods and a variety of theoretical choices, to consider. This continuum of change has shifted the field of qualitative research dramatically from limited choices to multiple options, requiring clarification of researcher decisions and transparency of process. However, there still remains the difficult question of the role that theory will now play in such a high level of complex design and critical researcher reflexivity.

• qualitative research
• data analysis
• methodologies

Theory and Qualitative Data Analysis

Researchers new to qualitative research, and particularly those coming from the quantitative tradition, have often expressed frustration at the need for what appears to be an additional and perhaps unnecessary process—that of the theoretical interpretation of their carefully designed, collected, and analyzed data. The justifications for this process have tended to fall into one of two areas: the need to lift data to a broader interpretation beyond the Monty Pythonesque “this is my theory and it’s my very own,” to illumination of findings from another perspective—by placing the data in its relevant discipline field for comparison with previous theoretical data interpretations, while possibly adding something original to the field.

“Theory” is broadly seen as a set of assumptions or propositions, developed from observation or investigation of perceived realties, that attempt to provide an explanation of relationships or phenomena. The framing of data via theoretical imposition can occur at different levels. At the lowest level, various concepts such as “role,” “power,” “socialization,” “evaluation,” or “learning styles” refer to limited aspects of social organization and are usually applied to a specific group of people.

At a more complex level, theories of the Middle Range, identified by Robert Merton to link theory and practice, are used to build theory from empirical data. These tend to be discipline specific and incorporate concepts plus variables such as “gender,” “race,” or “class.” Concepts and variables are then combined into meaningful statements, which can be applied to more diverse social groups. For example, in education an investigation of student performance could emphasize such concepts as “safety,” “zero bullying,” “communication,” and “tolerance,” with variables such as “race” and “gender” to lead to a statement that good microsystems and a focus on individual needs are necessary for optimal student performance.

The third and most complex level uses the established or grand theories such as those of Sigmund Freud’s stages of children’s development, Jean Piaget’s theory of cognitive development, or Urie Bronfenbrenner’s ecological systems, which have been widely accepted as meaningful across a number of disciplines and provide abstract explanations of the uniformity of aspects of social organization, social behavior, and social change.

The trend in qualitative research regarding the application of chosen levels of theory has been generally either toward theory direction/verification or theory generation, although the two are often intertwined. In the first, a relevant existing theory is chosen early and acts as a point of critical comparison for the data to be collected. This approach requires the researcher to think theoretically as s/he designs the study, collects data, and collates it into analytical groupings. The danger of theory direction is that an over focus on a chosen theoretical orientation may limit what the researcher can access or “see” in the data, but on the upside, this approach can also enable the generation of new theoretical aspects, as it is rare that findings will fall precisely within the implications of existing statements. Theory generation is a much looser approach and involves either one or a range of relevant levels of theory being identified at any point in the research process, and from which, in conjunction with data findings, some new combination or distillation can enhance interpretation.

The question of whether a well-designed study should negate the need for theoretical interpretation has been minimally debated. Mehdi and Mansor ( 2010 ) identified three trends in the literature on this topic: that theory in qualitative research relates to integrated methodology and epistemology; that theory is a separate and additional element to any methodological underpinnings; and that theory has no solid relationship with qualitative research. No clear agreement on any of these is evident. Overall, there appears to be general acceptance that the process of using theory, albeit etically (imposed) or emically (integrated), enhances outcomes, and moves research away from being a-theoretical or unilluminated by other ideas. However, regarding praxis, a closer look at the issue of the use of theory and data may be in order. Theoretical interpretation, as currently practiced, has limits. To begin with, the playing field is not level. In the grounded theory tradition, Glaser and Strauss ( 1967 ) were initially clear that in order to prevent undue influence on design and interpretation, the researcher should avoid reviewing the literature on a topic until after some data collection and analysis had been undertaken. The presumption that most researchers would already be well versed in theory/ies and would have a broad spectrum to draw on in order to facilitate the constant comparative process from which data-based concepts could be generated was found to be incorrect. Glaser ( 1978 ) suggested this lack could be improved at the conceptual level via personal and professional reflexivity.

This issue became even more of a problem with the advent of practice-led disciplines such as education and health into the field of qualitative research. These groups had not been widely exposed to the theories of the traditional social sciences such as sociology, psychology, and philosophy, although in education they would have been familiar with John Dewey’s concept of “pragmatism” linking learning with hands-on activity, and were more used to developing and using models of practice for comparison with current realities. By the mid- 20th century , Education was more established in research and had moved toward the use of middle range theories and the late 20th-century grand theorists: Michel Foucault, with his emphasis on power and knowledge control, and Jurgen Habermas, with his focus on pragmatism, communication, and knowledge management.

In addition to addictive identification with particular levels of theory and discipline-preferred theories and methods, activity across qualitative research seems to fall between two extremes. At one end it involves separate processes of data collection and analysis before searching for a theoretical framework within which to discuss the findings—often choosing a framework that has gained traction in a specific discipline. This “best/most acceptable fit” approach often adds little to the relevant field beyond repetition and appears somewhat forced. At the other extreme there are those who weave methods, methodologies, data, and theory throughout the whole research process, actively critiquing and modifying it as they go, usually with the outcome of creating some new direction for both theory and practice. The majority of qualitative research practice, however, tends to fall somewhere between these two.

The final aspect of framing data lies in the impact of researchers themselves, and the early- 21st-century emphasis is on exposing relevant personal frames, particularly those of culture, gender, socioeconomic class, life experiences such as education, work, and socialization, and the researcher’s own values and beliefs. The twin purposes of this exposure are to create researcher awareness and encourage accountability for their impact on the data, as well as allowing the reader to assess the value of research outcomes in terms of potential researcher bias or prejudice. This critical reflexivity is supposed to be undertaken at all stages of the research but it is not always clear that it has occurred.

Paradigms: From Interactionism to Performativity

It appears that there are potentially five sources of theory: that which is generally available and can be sourced from different disciplines; that which is imbedded in the chosen paradigm/s; that which underpins particular methodologies; that which the researcher brings, and that which the researched incorporate within their stories. Of these, the paradigm/s chosen are probably the most influential in terms of researcher position and design. The variety of the sets of assumptions, beliefs, and researcher practices that comprise the theoretical paradigms, perspectives, or broad world views available to researchers, and within which they are expected to locate their individual position and their research approach, has shifted dramatically since the 1930s. The changes have been distinct and identifiable, with their roots located in the societal shifts prompted by political, social, and economic change.

The First Wave

The Positivist paradigm dominated research, largely unquestioned, prior to the early 20th century . It emphasized the distancing of the researcher from his/her subjects; researcher objectivity; a focus on objective, cause–effect, evidence-based data derived from empirical observation of external realities; experimental quantitative methods involving testing hypotheses; and the provision of finite answers and unassailable future predictions. From the 1930s, concerns about the limitations of findings and the veracity of research outcomes, together with improved communication and exposure to the worldviews of other cultures, led to the advent of the realist/post-positivist paradigm. Post-positivism, or critical realism, recognized that certainty in proving the truth of a hypothesis was unachievable and that outcomes were probably limited to falsification (Popper, 1963 ), that true objectivity was unattainable and that the researcher was most likely to impact on or to contaminate data, that both qualitative and quantitative approaches were valuable, and that methodological pluralism was desirable.

The Second Wave

Alongside the worldwide political shifts toward “people power” in the 1960s and 1970s, two other paradigms emerged. The first, the Interpretivist/Constructivist, focused on the social situations in which we as humans develop and how our construction of knowledge occurs through interactions with others in these contexts. This paradigm also emphasized the gaining of an understanding of the subjective views or experiences of the participants being researched, and recognized the impact of the researcher on researcher–researched mutually constructed realities. Here, theory generation is the preferred outcome to explain the what, how, and why of the findings. This usually involves the development of a conceptual model, forged from both the data gained and from the application/integration of relevant theory, to provide explanations for and interpretations of findings, together with a new perspective for the field/discipline.

The second paradigm, termed the Critical/Emancipatory, focused on locating, critiquing, and changing inequalities in society. The identification of the location of systemic power discrepancies or systematic power misuse in situations involving gender, sexuality, class, and race is expected to be followed by moves to right any oppression discovered. Here, the use of theory has been focused more on predetermined concept application for “fit.” This is because the very strong notion of problematic societal structures and power inappropriately wielded have been the dominant underpinnings.

In both the Interpretive and Critical paradigms, researcher position shifted from the elevated and distant position of positivism, to one of becoming equal with those being researched, and the notion of researcher framing emerged to cover this shift and help us—the readers—to “see” (and judge) the researcher and her/his processes of data management more clearly.

The Third Wave

In the 1980s, the next wave of paradigmatic options—postmodernism and poststructuralism—emerged. Postmodernism, with its overarching cultural implications, and poststructuralism, with its focus on language, severely challenged the construction, limitations, and claims to veracity of all knowledge and in particular the use of theory derived from siloed disciplines and confined research methods. Regardless of whether the postmodern/poststructural label is attached to grounded theory, ethnography, phenomenology, action, or evaluative designs, one general aspect that prevails is a focus on language. Language has become viewed as dubious, with notions of “slippage”—the multiple meanings of individual words, and “difference”—the difference and deferral of textual meaning (Derrida, 1970 , 1972 ), adding complexity. Double coding, irony, and juxtaposition are encouraged to further identify meaning, and to uncover aspects of social organization and behavior that have been previously marginalized or made invisible by existing discourses and discursive practices. Texts are seen as complex constructions, and intertextuality is favored, resulting in multiply constructed texts. The world is viewed as chaotic and unknowable; individuals are no longer seen as two dimensional—they are viewed as multifaceted with multiple realities. Complex “truths” are perceived as limited by time and context, requiring multiple data sets and many voices to illuminate them, and small-scale focused local research is seen as desirable. The role of researcher also changed: the politics of position and self-reflexivity dominate and the researcher needs to clearly expose past influences and formerly hidden aspects of his/her life. S/he inhabits the position of an offstage or decentered facilitator, presenting data for the reader to judge.

Theory is used mainly at the conceptual level with no particular approach being privileged. The researcher has become a “bricoleur” (Levi-Strauss, 1962 ) or handyman, using whatever methods or theories that are within reach, to adapt, craft, and meld technological skills with mythical intellectual reflection in order to create unique perspectives on the topic. Transitional interpretations dominate, awaiting further challenges and deconstruction by the next researcher in the field.

The need for multifaceted data sets in the 1990s led inevitably to a search for other research structures, and mixed and multiple methods have become topical. In crossing the divide between qualitative and quantitative approaches, the former initially developed its own sub-paradigms: pragmatist (complimentary communication and shared meanings) and transformative/emancipatory (inequalities in race, class, gender, and disability, to be righted). An increasing focus on multiple methods led to the advent of dialectics (multiple paradigm use) and critical realism (the acceptance of divergent results) (Shannon-Baker, 2016 ). The dilemmas of theory use raised by these changes include whether to segregate data sets and try to explain disparate outcomes in terms of diversity using different theories; whether to integrate them through a homogeneous “smoothing” process—one theory fits all, in order to promote a singular interpretation; or whether to let the strongest paradigm—in terms of data—dominate the theoretical findings.

The Fourth Wave

During the early 21st century , as the third wave was becoming firmly established, the Performative paradigm emerged. The incorporation of fine art–based courses into universities has challenged the prescribed rules of the doctoral thesis, initially resulting in a debate—with echoes of Glaser and Strauss—as to whether theory, if used initially, is too directive, thereby potentially contaminating the performance, or whether theory application should be an outcome to enhance performances, or even whether academic guidelines regarding theory use need to be changed to accommodate these disciplines (Bolt, 2004 ; Freeman, 2010 ; Riley & Hunter, 2009 ). Performativity is seen in terms of “effect,” a notion derived from John Austin’s ( 1962 ) assertion that words and speech utterances do not just act as descriptors of content, they have social force and impact on reality. Following this, a productive work is seen as capable of transforming reality (Bolt, 2016 ). The issue most heard here is the problem of how to judge this form of research when traditional guidelines of dependability, transformability, and trustworthiness appear to be irrelevant. Barbara Bolt suggests that drawing on Austin’s ( 1962 ) terms “locutionary” (semantic meaning), “illocutionary” (force), and “perlocutionary” (effect achieved on receivers), together with the mapping of these effects in material, effective, and discursive domains, may be useful, despite the fact that mapping transformation may be difficult to track in the short term.

During the second decade of the 21st century , however, discussions relating to the use of theory have increased dramatically in academic performative research and a variety of theoreticians are now cited apart from John Austin. These include Maurice Merleu-Ponty ( 1945 and the spatiality of lived events; Jacques Derrida ( 1982 ) on iterability, simultaneous sameness, and difference; Giles Deleuze and Felix Guatarri ( 1987 ) on rituals of material objects and transformative potential; Jean-Francois Lyotard ( 1988 ) on plurality of micro narratives, “affect,” and its silent disruption of discourse; and Bruno Latour ( 2005 ) with regard to actor network theory—where theory is used to engage with rather than to explain the world in a reflective political manner.

In performative doctoral theses, qualitative theory and methods are being creatively challenged. For example, from the discipline of theater and performance Lee Miller and Joanne/Bob Whalley ( 2010 ) disrupt the notion of usual spaces for sincere events by taking their six-hour-long performance Partly Cloudy, Chance of Rain , involving a public reaffirmation of their marriage vows, out of the usual habitats to a service station on a highway. The performance involves a choir, a band, a pianist, 20 performers dressed as brides and grooms, photographers, a TV crew, an Anglican priest, plus 50 guests. The theories applied to this event include an exploration of Marc Auge’s ( 1992 ) conception of the “non-place”; Mikhail Bakhtin’s ( 1992 ) concepts of “dialogism” (many voices) together with “heteroglossia” (juxtaposition of many voices in a dialogue); and Ludwig Wittgenstein’s ( 1953 ) discussion of the “duck rabbit”—once the rabbit is seen (participatory experience) the duck (audience) is always infected by its presence. This couple further challenged the guidelines of traditional doctoral theses by successfully negotiating two doctoral awards for a joint piece of research

A more formal example of a doctoral thesis (Reik, 2014 ) using traditional qualitative approaches has examined at school level the clash of paradigms of performative creative styles of teaching with the neoliberalist focus on testing, curriculum standardization, and student outcomes.

Leah Mercer ( 2012 ), an academic in performative studies, used the performative paradigm in her doctoral thesis to challenge and breach not only the methodological but also the theoretical silos of the quantitative–qualitative divide. The physics project is an original work using live performances of personal storytelling with video and web streaming to depict the memories, preoccupations, and the formative relationship of two women, an Australian and an American, living in contemporary mediatized society. Using scientific theory, Mercer explores personal identity by reframing the principles of contemporary physics (quantum mechanics and uncertainty principle) as aesthetic principles (uncertainty and light) with the physics of space (self), time (memory), light (inspiration), and complementarity (the reconciliation of opposites) to illuminate these experiences.

The performative paradigm has also shifted the focus on the reader, developed in postmodernism, to a broader group—an active audience. Multi-methods have been increased to include symbolic imagery, in particular visual images, as well as sound and live action. The researcher’s role here is often that of performer within a cultural frame, creating and investigating multiple realities and providing the link between the text/script and the audience/public. Theory is either minimized to the level of concepts or used to break through the silos of different disciplines to integrate and reconcile aspects from long-lasting theoretical divides.

In these chronological lines of paradigm shifts, changes in researcher position and changes in the application of theory can clearly be seen. The researcher has moved out of the shadows and into the mainstream; her/his role has shifted from an authoritarian collector and presenter of finite “truths” to a creator and often performer of multiple and disparate data images for the audience to respond to. Theory options have shifted from direction and generation within existing perspectives to creative amalgamations of concepts from disciplines previously rarely combined.

Methodologies: From Anthropology to Fine Arts

It would be a simple matter if all the researcher had to contend with was siting oneself in a particular paradigm/s. Unfortunately, not only have paradigms shifted in terms of researcher position and theoretical usage but so also have methodological choices and research design. One of the most popular methodologies, ethnography, with its roots in classical anthropology and its fieldwork-based observations of action and interaction in cultural contexts, can illustrate the process of methodological change following paradigm shift. If a researcher indicates that he/she has undertaken an ethnographic study, the reader will be most likely to query “which form?”: classical?, critical?, auto?, visual?, ethno drama?, cyber/net?, or performative? The following examples from this methodology should indicate how paradigm shifts have resulted in increasing complexity of design, methods, and interpretive options.

In c lassical ethnography the greatest borrowing is from traditional anthropology in terms of process and tools, and this can be seen with the inclusion of initial time spent in the setting to learn the language of the culture and to generally “bathe” oneself in the environment, often with minimal data collection. This process is supposed to help increase researcher understanding of the culture and minimize the problem of “othering” (treating as a different species/alien). Then a fairly lengthy amount of time is usually spent in the cultural setting either as an observer or as a participant observer to collect as much data as is relevant to answer the research question. This is followed by a return to post-check whether the findings previously gathered have stood the test of time. The analytical toolkit can involve domain analysis, freelists, pilesorts, triads and taxonomies, frame and social network, and event analysis. Truncated mini-ethnographies became more common as time became an issue, but these can still involve years of managing descriptive data, often collected by several participating researchers as seen in Douglas, Rasmussen, and Flanagan’s ( 1977 ) study of the culture of a nudist beach. Shorter versions undertaken by one researcher, for example Sohn ( 2015 ), have explored strategies of teacher and student learning in a science classroom. Theoretical interpretation can be by conceptual application for testing, such as Margaret Mead’s ( 1931 ) testing of the concept of “adolescence”—derived from American culture—in Samoan culture, or, more generally, by concept generation. The latter can be seen in David Rozenhan’s ( 1973 ) investigation of the experience of a group of researcher pseudo-patients admitted to hospitals for the mentally ill in the United States. The main concepts generated were labeling, powerlessness, and depersonalization.

De-colonial ethnography recognizes the “othering” frames of colonial and postcolonial research and takes a position that past colonial supremacy over Third World countries persists in political, economic, educational, and social constructions. Decolonizing requires a critical examination of language, attitudes, and research methods. Kakal Battacharya ( 2016 ) has exposed the micro-discourses of the continuing manifestation of colonial power in a parallel narrative written by a South Asian woman and a white American male. Concepts of colonialism and patriarchy, displayed through the discourses exposed, provide a theoretical critique.

Within critical ethnography , with its focus on power location and alleviation of oppression, Dale Spender ( 1980 ) used structured and timed observations of the styles, quality, and quantity of interaction between staff and students in a range of English classrooms. The theory-directive methodological frames of feminism and gender inequality were applied to identify and expose the lesser time and lesser quality of interaction that teachers had with female students in comparison with that assigned to male students. Widespread distribution of these results alerted education authorities and led to change, in some environments, toward introducing single-sex classrooms for certain topics. This was seen as progress toward alleviating oppressive behaviors. This approach has produced many excellent educational studies, including Peter Willis ( 1977 ) on the preparation of working-class kids for working-class jobs; Michele Fine ( 1991 ) on African American and Latino students who dropped out of a New York high school; Angela Valenzuela ( 1999 ) on emigrant and other under-achievers in American schools; Lisa Patel ( 2013 ) on inclusion and exclusion of immigrants into education; and Jean Anyon ( 1981 ) on social stratification of identical curriculum knowledge in different classrooms

A less concept-driven and more descriptive approach to critical ethnography was emphasized by Phil Carspecken’s hermeneutic approach ( 1996 ), which triggered a move toward data-generated theoretical concepts that could then be used to challenge mainstream theoretical positions.

Post-critical ethnography emphasizes power and ideology and the social practices that contribute to oppression, in particular objectivity, positionality, representation and reflexivity, and critical insufficiency or “antipower.”

Responsibility is shifted to the researcher for the world they create and critique when they interpret their research contexts (Noblit, Flores, & Murillo, 2004 ).

Autoethnography emerged from the postmodern paradigm, with its search for different “truths” and different relationships with readers, and prompted an emphasis on personal experience and documentation of the self in a particular cultural context (Ellis, 2004 ). In order to achieve this, the researcher has to inhabit the dual positions of being the focus of activities, feelings, and emotions experienced in the setting while at the same time being positioned distantly—observing and recording the behaviors of the self in that culture. Well-developed skills of critical reflexivity are required. The rejection of the power-laden discourses/grand theories of the past and the emphasis on transitional explanations has resulted in minimal theorizing and an emphasis on data display, the reader, and the reader’s response. Open presentations of data can be seen in the form of narrative storytelling, or re-presentations in the form of fiction, dramatic performances, and poetry. Carolyn Ellis ( 2004 ) has argued that “story is theory and theory is story” and our “making sense of stories” involves contributing to a broader understanding of human existence. Application/generation of concepts may also occur, and the term “Critical Autoethnography” has been used (Hughes & Pennington, 2017 ), particularly where experiences of race, class, or gender inequality are being experienced. Jennifer Potter ( 2015 ) used the concept “whiteness of silence” to introduce a critical race element into her autoethnographic experience of black–white racial hatred experiences within a university class on African American communication in which she was a student.

Visual ethnography uses a variety of tools, including photography, sketches, movies, social media, the Web and virtual reality, body art, clothing, painting, and sculpture, to demonstrate and track culture. This approach has been available for some time both as a methodology in its own right and as a method of data collection. An example of this approach, which mixes classical and visual ethnography, is Philippe Bourgois and Jeff Schonberg’s 12-year study of two dozen homeless heroin injectors and crack smokers living under a freeway overpass in San Francisco ( 2009 ). Their data comprised extensive black and white photos, dialogue, taped conversations, and fieldwork observation notes. The themes of violence, race relations, family trauma, power relations, and suffering were theoretically interpreted through reworked notions of “power” that incorporated Pierre Bourdieu’s ( 1977 , 1999 ) concepts of “symbolic violence”—linking observed practices to social domination, and “habitus”—an individual’s personal disposition comprising unique feelings and actions grounded in biography and history; Karl Marx’s “lumpen” from “lumpenproletariat” ( 1848 ), the residual class—the vagrants and beggars together with criminal elements that lie beneath the labor force; and Michel Foucault’s “biopower” ( 1978 , 2008 )—the techniques of subjugation used by the state on the population, and “governmentality” ( 1991 )—where individuals are disciplined through institutions and the “knowledge–power” nexus. The ideas of these three theorists were used to create and weave a theory of “lumpen abuse” to interpret the lives of the participants.

Ethno Drama involves transforming the results from an ethnographic study into a performance to be shared, for example the educational experiences of children and youth (Gabriel & Lester, 2013 ). The performance medium can vary from a film (Woo, 2008 ), an article presented in dramatic form (Carter, 2014 ), or more usually a play script to be staged for an audience in a theater (Ethno Theater). One of the main purposes is to provide a hearing space for voices that have been marginalized or previously silenced. These voices and their contexts can be presented by research participants, actors, or the research team, and are often directed at professionals from the field. Audience-based meetings to devise recommendations for further action may follow a performance. Because of the focus on inequality, critical theory has been the major theoretical orientation for this approach. The structure of the presentation invites audiences to identify situations of oppression, in the hope that this will inform them sufficiently to enable modification of their own practices or to be part of the development of recommendations for future change.

Lesnick and Humphrie ( 2018 ) explored the views of identity of LGBTQ+ youth between 14 and 24 years of age via interviews and online questionnaires, the transcriptions of which were woven into a script that was performed by actors presenting stories not congruent with their own racial/gender scripts in order to challenge audience expectations and labels. The research group encouraged the schools where they performed to structure discussion groups to follow the school-located performances. The scripts and discussions revealed and were lightly interpreted through concepts of homelessness, racism, and “oppression Olympics”—the way oppressed people sometimes view one another in competition rather than in solidarity. These issues were found to be relevant to both school and online communities. Support for these young people was discovered to be mostly from virtual sources, being provided by dialogues within Facebook groups.

Cyber/net or/virtual ethnographies involve the study of online communities within particular cultures. Problems which have emerged from the practice of this approach include; discovery of the researcher lurking without permission on sites, gaining prior permission which often disturbs the threads of interaction, gaining permission post–data collection but having many furious people decline participation, the “facelessness” of individuals who may have uncheckable multiple personas, and trying to make sense of very disparate data in incomplete and non-chronological order.. There has been acceptance that online and offline situations can influence each other. Dibbell ( 1993 ) demonstrated that online sexual violence toward another user’s avatar in a text-based “living room” reduced the violated person to tears as she posted pleas for the violator to be removed from the site. Theoretical interpretation at the conceptual level is common; Michel Foucault’s concept of heterotopia ( 1967 , 1984 ) was used to explain such spatio-temporal prisons as online rooms. Heterotropic spaces are seen as having the capacity to reflect and distort real and imagined experiences.

Poststructural ethnography tracks the instability of concepts both culturally and linguistically. This can be demonstrated in the deconstruction of language in education (Lather, 2001 ), particularly the contradictions and paradoxes of sexism, gender, and racism both in texts and in the classroom. These discourses are implicated in relations of power that are dynamic and within which resistance can be observed. Poststructuralism accepts that texts are multiple, as are the personas of those who created them, and that talk such as that which occurs in a classroom can be linked with knowledge control. Walter Humes ( 2000 ) discovered that the educational management discourses of “community,” “leadership,” and “participation” could be disguised by such terms as “learning communities” and “transformational leadership.” He analyzed the results with a conceptual framework derived from management theory and policy studies and linked the findings with political power.

Performative ethnography , from the post-postmodern paradigm, integrates the performances of art and theater with the focus on culture of ethnography (Denzin, 2003 ). A collaborative performance ethnography (van Katwyk & Seko, 2017 ) used a poem re-presenting themes from a previous research study on youth self-harming to form the basis of the creation of a performative dance piece. This process enabled the researcher participants to explore less dominant ways of knowing through co-learning and through the discovery of self-vulnerability. The research was driven by a social justice-derived concern that Foucault’s notion of “sovereignty” was being implemented through a web of relations that commodified and limited knowledge, and sanctioned the exploitation of individuals and communities.

This exploration of the diversity in ethnographic methods, methodologies, and interpretive strategies would be repeated in a similar trek through the interpretive, critical, postmodern, and post-postmodern approaches currently available for undertaking the various versions of grounded theory, phenomenology, feminist research, evaluation, action, or performative research.

Implications of Changes for the Researcher

The onus is now less on finding the “right” (or most familiar in a field) research approaches and following them meticulously, and much more on researchers making their own individual decisions as to which aspects of which methodologies, methods and theoretical explanations will best answer their research question. Ideally this should not be constrained by the state of the discipline they are part of; it should be equally as easy for a fine arts researcher to carry out a classical ethnography with a detailed theoretical interpretation derived from a grand theorist/s as it would be for a researcher in law to undertake a performative study with the minimum of conceptual insights and the maximum of visual and theoretical performances. Unfortunately, the reality is that trends within disciplines dictate publication access, thereby reinforcing the prevailing boundaries of knowledge.

However, the current diversity of choice has indeed shifted the field of qualitative research dramatically away from the position it was in several decades ago. The moves toward visual and performative displays may challenge certain disciplines but these approaches have now become well entrenched in others, and in qualitative research publishing. The creativity of the performative paradigm in daring to scale the siloed and well-protected boundaries of science in order to combine theoretical physics with the theories of social science, and to re-present data in a variety of newer ways from fiction to poetry to researcher performances, is exciting.

Given that theoretical as well as methodological and methods’ domains are now wide open to researchers to pick and choose from, two important aspects—justification and transparency of process—have become essential elements in the process of convincing the reader.

Justification incorporates the why of decision-making. Why was the research question chosen? Why was the particular paradigm, or paradigms, chosen best for the question? Why were the methodology and methods chosen most appropriate for both the paradigm/s and research question/s? And why were the concepts used the most appropriate and illuminating for the study?

Transparency of process not only requires that the researcher clarifies who they are in the field with relation to the research question and the participants chosen, but demands an assessment of what impact their background and personal and professional frames have had on research decisions at all stages from topic choice to theoretical analysis. Problems faced in the research process and how they were managed or overcome also requires exposition as does the chronology of decisions made and changed at all points of the research process.

Now to the issue of theory and the question of “where to?” This brief walk through the paradigmatic, methodological, and theoretical changes has demonstrated a significant move from the use of confined paradigms with limited methodological options to the availability of multiple paradigms, co-methodologies, and methods of many shades, for the researcher to select among Regarding theory use, there has been a clear move away from grand and middle range theories toward the application of individual concepts drawn from a variety of established and minor theoreticians and disciplines, which can be amalgamated into transitory explanations. The examples of theoretical interpretation presented in this article, in my view, very considerably extend, frame, and often shed new light on the themes that have been drawn out via analytical processes. Well-argued theory at any level is a great enhancer, lifting data to heights of illumination and comparison, but it could equally be argued that in the presence of critical researcher reflexivity, complex, layered, longitudinal, and well-justified design, meticulous analysis, and monitored audience response, it may no longer be essential.

Bibliography

• Eco, U. (1979). The role of the reader . Bloomington: Indiana University Press.
• Gadamer, H. (1989). Truth and method ( J. Weinheimer & D. Marshall , Trans.). NY: Crossroad.
• Grbich, C. (2004). New approaches in social Research . London, U.K.: SAGE.
• Grbich, C. (2013). Qualitative data analysis: An introduction . London, U.K.: SAGE.
• Lincoln, Y. , & Denzin, N. (2000). Paradigmatic controversies: Contradictions and emerging confluences. In N. Denzin and Y. Lincoln , Handbook of qualitative research (2nd ed.). Thousand Oaks, CA: SAGE.
• Lyotard, J. (1983). Answering the question: What is post modernism? In E. Hassan & S. Hassan (Eds.), Innovation and renovation . Madison: University of Wisconsin Press.
• Pink, S. (2012). Advances in visual methodology . Thousand Oaks, CA: SAGE.
• Riley, S. , & Hunter, L. (Eds.). (2009). Mapping landscapes for performance as research . London: Palgrave Macmillan.
• Tinkler, P. (2011). Using photography in social and historic research . New Dehli, India: SAGE.
• Vis, F. , & Thelwall, M. (2012). Researching social media . New Dehli, India: SAGE.
• Von Hantelmann, D. (2010). How to do things with art . Zurich, Switzerland: JRP Ringier.
• Anyon, J. (1981). Social class and school knowledge . Curriculum Inquiry , 11 (1), 3–42.
• Auge, M. (1992). Non-Places: An introduction to supermodernity ( John Howe ). London, U.K.: Verso.
• Augé, M. (1995). Non-places: An introduction to anthropology of supermodernity . London, U.K.: Verso.
• Austin, J. (1962). How to do things with words [The William James Lectures, 1955]. Oxford, U.K.: Oxford University Press.
• Bakhtin, M. (1992). The dialogic imagination: Four essays . Austin: University of Texas Press.
• Battacharya, K. , & Gillen, N. (2016). Power, race and higher education: A cross-cultural parallel narrative . Rotterdam, The Netherlands: Sense.
• Bolt, B. (2004). Art beyond representation: The performative power of the image . London, U.K.: I.B Tauris.
• Bolt, B. (2016). Artistic research: A performative paradigm? Parse. #3 Repetitions and Reneges . Gothenburg, Sweden: University of Gothenburg.
• Bourdieu, P. (1977). Outline of a theory of practice . Cambridge, U.K.: Cambridge University Press.
• Bourdieu, P. (1999) The Weight of the world: Social suffering in contemporary society . Cambridge, U.K.: Polity Press.
• Bourgois, P. , & Schonberg, J. (2009). Righteous dopefiend: Homelessness, addiction, and poverty in urban America . Berkeley: University of California Press.
• Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design . Cambridge, MA: Harvard University Press.
• Carspecken, P. (1996). Critical ethnography in educational research . New York: Routledge.
• Carter, M. (2014). The teacher monologues: Exploring the identities and experiences of artist-teachers . Rotterdam, The Netherlands: Sense.
• Deleuze, G. , & Guattari, F. (1987). A thousand Plateaus: Capitalism and schizophrenia ( B. Massumi , Trans.). Minneapolis: University of Minnesota Press.
• Denzin, N. (2003). Performance ethnography : Critical pedagogy and the politics of culture . Thousand Oaks, CA: SAGE.
• Derrida, J. (1970). Structure, sign and play in the discourse of human sciences lecture presented at johns hopkins university , October 21, 1966.
• Derrida, J. (1972). Margins of philosophy: Plato to footnotes ( A. Bass , Trans.). Sussex, U.K.: Brighton and Harvester Press.
• Derrida, J. (1982). Sending: On representation . Social Research , 49 (2), 294–326.
• Dewey, J. (1998). The essential Dewey ( L. Hickman & T. Alexander , Eds.). (2 vols.) Bloomington: Indiana University Press.
• Dibbell, J. (1993). A rape in cyberspace from chapter 1 of My Tiny Life . Published in The Village Voice .
• Douglas, J. , Rasmussen, P. , & Fanagan, C. (1977). The nude beach . Thousand Oaks, CA: SAGE.
• Ellis, C. (2004). The ethnographic I: A methodological novel about autoethnography . Walnut Creek, CA: AltaMira.
• Fine, M. (1991). Framing dropouts: Notes on the politics of an urban high school . New York, NY: SUNY Press.
• Foucault, M. (1967, 1984). Des espaces autres (J. Miscowiec, Trans.). [ Of other spaces: Utopias and heterotropias]. Archtecture/Mouvement/Continuite , October.
• Foucault, M. (1978). Security, territory, population. Lectures at the Collège de France 1977–1978 ( A. Davidson , Ed.). New York, NY: Palgrave Macmillan.
• Foucault, M. (1991). Studies in governmentality: Two lectures by and an interview with Michel Foucault ( G. Burchell , C. Gordon , & and P. Miller , Eds.). Chicago: University of Chicago Press.
• Foucault, M. (2008). The birth of biopolitics . Lectures at the Collège de France 1978–1979 ( M. Senellart , Ed, Trans.; G. Burchell , Trans.). New York, NY: Palgrave Macmillan. (First published as Naissance de la Biopolitique 2004).
• Freeman, J. (2010). Blood, sweat and theory: Research through practice in performance . Faringdon, U.K.: Libri.
• Freud, S. (1953–1974). The standard edition of the complete psychological works of Sigmund Freud ( J. Strachey , Trans. and Ed.) (24 Vols). London, U.K.: Hogarth and the Institute of Psycho-Analysis.
• Gabriel, R. , & Lester, J. (2013). Performances of research: Critical issues in K–12 education . New York, NY: Peter Lang.
• Glaser, B. (1978). Theoretical sensitivity: Advances in the theory of grounded theory . Mill Valley, CA: Sociology Press.
• Glaser, B. , & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research . London: Aldine.
• Hughes, S. , & Pennington, J. (2017). Autoethnography: Process, product and possibility for critical social research . Thousand Oaks, CA: SAGE.
• Humes, W. (2000). The discourses of educational management . Journal of Educational Enquiry , 1 (1).
• Lather, P. (2001). Postmodernism, post-structuralism and post(critical) ethnography: Of ruins, aporias and angels. In P. Atkinson , A. Coffey , S. Delamont , J. Lofland , & L. Lofland (Eds.), Handbook of ethnography . Thousand Oaks, CA: SAGE.
• Latour, B. (2005). Reassembling the social: An introduction to actor–network theory . Oxford, U.K.: Oxford University Press.
• Lesnick, E. , & Humphrie, J. (2018). Amplifying youth voices through ethnodrama research . Washington, DC: National Association of Independent Schools.
• Levi-Strauss, C. (1962). The savage mind ( La pensee sauvage) ( G. Weidenfield & Nicholson Ltd. , Trans.). Chicago, IL: University of Chicago Press.
• Lyotard, J. (1988). Peregrinations: Law, form, event . The Wellek Library lectures at the University of California, Irvine. New York, NY.: Columbia University Press.
• Marx, K. , & Engels, F. (1848). The Communist Manifesto ( S. Moore , Trans.).
• Mead, M. (1931). The life of a Samoan girl: ALL TRUE. The record of actual adventures that have happened to ten women of today . New York, NY.: Brewer, Warren and Putnam.
• Mehdi, T. , & Mansor, A. (2010). A General perspective on the role of theory in qualitative research . Journal of International Social Research , 3 (11).
• Mercer, L. (2012). The Physics Project. In L. Mercer , J. Robson , & D. Fenton (Eds.), Live research: Methods of practice led inquiry in research . Nerang: Queensland, Ladyfinger.
• Merleau-Ponty, M. (1945). Phénoménologie de la Perception . Paris, France: Editions Gallimard.
• Merleau-Ponty, M. (2005). Phenomenology of perception ( D. Landes , Trans.). London, U.K.: Routledge.
• Merton, R. (1968). Social theory and social structure . New York, NY: Free Press.
• Miller, L. , & Whalley, J. (2010). Case Study 11: Partly cloudy, chance of rain. In J. Freeman (Ed.), Blood, sweat and theory: Research through practice in performance . Faringdon, U.K.: Libri.
• Noblit, G. , Flores, S. , & Nurillo, E. (2004). Postcritical ethnography: Reinscribing critique . New York: Hampton Press.
• Patel, L. (2013). Youth held at the border: Immigration, education and the politics of inclusion . New York, NY: Columbia University Teacher’s College Press.
• Piaget, J. (1936). Origins of intelligence in the child . London, U.K.: Routledge and Kegan Paul.
• Popper, K. (1963). Science: Conjectures and refutations. Online lecture transcript .
• Potter, J. (2015). The whiteness of silence: A critical autoethnographic tale of a strategic rhetoric . Qualitative Report , 20 (9), 7.
• Reik, R. (2014). Arts education in a culture of performativity: A case study of what is valued in one Queensland school community . (Doctoral dissertation), Griffith University, Brisbane.
• Riley, S. R. , & Hunter, L. (Eds.). (2009). Mapping landscapes for performance as research . London, U.K.: Palgrave Macmillan.
• Rosenhan, D. (1973). On being sane in insane places . Science , 17 (January), 250–258.
• Shannon-Baker, P. (2016). Making paradigms meaningful in mixed methods research . Journal of Mixed Methods Research , 10 (4).
• Sohn, L. (2015). Ethnographic case study of a high school science classroom: Strategies in STEM education . (Doctoral dissertation). Texas A&M University, Corpus Christi, Texas.
• Spender, D. (1980). Talking in class. In D. Spender & E. Sarah (Eds.), Leaming to lose: Sexism and education . London, U.K.: Women’s Press.
• Valenzuela, A. (1999). Subtractive schooling: U.S.–Mexican youth and the politics of caring . Albany: SUNY.
• van Katwyk, T. , & Seko, Y. (2017). Knowing through improvisational dance: A collaborative autoethnography . Forum: Qualitative Social Research , 18 (2), 1.
• Willis, P. (1977). Learning to labour . New York, NY: Columbia University Press.
• Wittgenstein, L. (1953). Philosophical investigations ( G. Anscombe , Trans.). Oxford, U.K.: Blackwell.
• Woo, Y. (2008). Engaging new audiences: Translating research into popular media. Educational Researcher , 37 (6), 321–329.

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Methodology

• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on September 5, 2024.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

• Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

• Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
• Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

• Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
• Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
• Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
• Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
• Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
• Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
• Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

• Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
• Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

• Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
• Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
• Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
• Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

• Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
• Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
• Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
• Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
• Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

• Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
• Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
• Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
• Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
• Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
• Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

• Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
• Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
• Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
• Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
• Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
• Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

• Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
• Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
• Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
• Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
• Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
• Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Use of theory in qualitative research

Research without theory is blind, and theory without research is empty. (Bourdieu & Wacquant, 1992: p. 162)

“Theory is integral to the practice of qualitative research in health” (Liamputtong & Ezzy, 2004: p. 13). It is necessary for sense-making, to interpret and explain seemingly disparate data. Theory is necessary to move beyond descriptions to explanations of phenomena, such as why some health professionals and community members discriminate against people with certain conditions (e.g., obesity and smoking), but not other conditions. Different theories offer different “lenses through which to look at complicated problems and social issues” and help move the focus from the particular to the general (Reeves, Albert, Kuper & Hodges, 2008). Theory helps to provide new insights into or ways of understanding an issue. It increases the utility, rigour, and credibility of research findings and it facilitates the development of new concepts and their generalizability [1] or transferability.

There are two ways in which qualitative researchers think about using theory: (1) as a way of theorizing the project or study as a whole; the general theoretical lens through which the researcher approaches the topic, study and study design, methodology and method; and (2) as a way of analyzing and interpreting the data, pulling it together into study “findings” and fashioning it into a story, an analytic whole, a theorization. Consequently, theory appears in different places throughout the research process. Studies are always guided by a theoretical perspective, whether this is explicitly stated or not (Sandelowski, 1993).

Theory does not always refer to grand theories like phenomenology or poststructuralism; assumptions and initial conceptualizations that we have when we enter the research process and the general perspectives of our disciplines are kinds of theory, too. For example, occupational therapists see “occupations,” jobs and everyday activities, as paramount to processes that lead to both health and ill-health. Our assumptions about how the world works, the kinds of research questions we ask, the way we present a research problem, and the methods we choose are all suggestive of theoretical or paradigm stances. Sandelowski (1993) asserts that theories

include the disciplinary paradigms in the arts, sciences, and humanities that direct or inform both the inquiry process, including the presentation of findings, and the abstract schemas (including what is commonly referred to as concepts, conceptual models, and frameworks) describing, organizing, and interpreting the target phenomena that constitute the subjects/objects of individual research projects in a substantive area. (p. 214)

• Unlike statistical findings that are generalized to populations, generalizability in qualitative research refers to concepts generated as having wider resonance beyond the initial context of the study or having relevance in another context (Green and Thorogood, 2004; Schofield, 2002). ↵

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Affiliation.

• 1 Department of Psychiatry, Li Ka Shing Knowledge Institute, Centre for Faculty Development, and Wilson Centre for Research in Education, University of Toronto, Toronto, Ontario, Canada. [email protected]
• PMID: 18687730
• DOI: 10.1136/bmj.a949

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• Open access
• Published: 09 September 2024

A qualitative study of providers’ perspectives on cross-institutional care coordination for pancreatic cancer: challenges and opportunities

• Matthew J. DePuccio 1 , 5 ,
• Karen Shiu-Yee 1 ,
• Natasha A. Kurien 1 ,
• Angela Sarna 2 ,
• Brittany L. Waterman 3 ,
• Laura J. Rush 1 ,
• Ann Scheck McAlearney 1 , 4 &
• Aslam Ejaz 2 , 6  

BMC Health Services Research volume  24 , Article number:  1041 ( 2024 ) Cite this article

Metrics details

Despite calls for regionalizing pancreatic cancer (PC) care to high-volume centers (HVCs), many patients with PC elect to receive therapy closer to their home or at multiple institutions. In the context of cross-institutional PC care, the challenges associated with coordinating care are poorly understood.

In this qualitative study we conducted semi-structured interviews with oncology clinicians from a HVC ( n  = 9) and community-based hospitals ( n  = 11) to assess their perspectives related to coordinating the care of and treating PC patients across their respective institutions. Interviews were transcribed, coded, and analyzed using deductive and inductive approaches to identify themes related to cross-institutional coordination challenges and to note improvement opportunities.

Clinicians identified challenges associated with closed-loop communication due, in part, to not having access to a shared electronic health record. Challenges with patient co-management were attributed to patients receiving inconsistent recommendations from different clinicians. To address these challenges, participants suggested several improvement opportunities such as building rapport with clinicians across institutions and updating tumor board processes. The opportunity to update tumor board processes was reportedly multi-dimensional and could involve: (1) designating a tumor board coordinator; (2) documenting and disseminating tumor board recommendations; and (3) using teleconferencing to facilitate community-based clinician engagement during tumor board meetings.

Conclusions

In light of communication barriers and challenges associated with patient co-management, enabling the development of relationships among PC clinicians and improving the practices of multidisciplinary tumor boards could potentially foster cross-institutional coordination. Research examining how multidisciplinary tumor board coordinators and teleconferencing platforms could enhance cross-institutional communication and thereby improve patient outcomes is warranted.

Peer Review reports

Introduction

Although pancreatic cancer (PC) is the 11th most common cancer in the U.S., it ranks third in cancer-related deaths, with a 5-year survival rate of only 9% [ 1 , 2 ]. Several recent clinical trials have shown improvements using both systemic (i.e., chemotherapy) and surgical treatments [ 3 ] for this disease, and these advancements are reflected in numerous evidence-based treatment guidelines [ 4 , 5 ]. However, more than one-half of patients with PC do not receive stage-specific, guideline-concordant care, resulting in worse mortality and morbidity compared to patients who do receive guideline-concordant care [ 6 , 7 , 8 ]. Previous research suggests that PC patients treated at low-volume centers are less likely to receive guideline-concordant care, which contributes to worse outcomes [ 9 ]. Furthermore, there is a well-established correlation between higher treatment volume and improved outcomes for patients with PC [ 10 , 11 ].

These findings have sparked calls for greater regionalization of PC care at high-volume centers (HVCs) [ 12 ]. While regionalization of care can allow for a “one-stop shopping” experience where patients receive care from multiple cancer specialists and subspecialists within a single institution, it can also be problematic for patients who do not live near a HVC [ 11 ] or who prefer to receive certain aspects of their cancer treatment (e.g., chemotherapy, radiation) closer to home [ 13 ]. For example, these patients may undergo preliminary tests in community-based settings before being referred to a HVC, [ 14 ] and this requires coordination between high-volume center providers (HVCPs) and community-based providers (CBPs) to reduce the risk of redundant diagnostic testing that can contribute to increased costs, delayed treatment, and patient dissatisfaction [ 15 , 16 , 17 ].

However, the inherent complexities associated with multi-institutional care coordination [ 18 ] are poorly understood. To expand our knowledge about the challenges and facilitators of coordinating the care of patients with PC between HVCPs and CBPs, we conducted a qualitative study to elicit the perspectives of both HVCPs from an urban academic medical center and CBPs in surrounding rural counties regarding the coordination of oncologic services for patients with PC to identify opportunities to further improve cross-institutional care coordination.

Participant selection

We used a purposeful sampling approach [ 19 , 20 ] to identify and recruit clinicians with prior experience treating or managing patients with PC because they could speak in depth about the coordination of PC care. HVCPs were board-certified oncologists recruited from medical, surgical, and radiation oncology departments within a large Midwestern academic medical center ( n  = 9) that met the criteria for hospital and surgeon volume for pancreatic resection of cancer (response rate = 69.2%). CBPs were recruited from health systems in rural counties and included board-certified oncologists ( n  = 9) and nurse practitioners ( n  = 2) who care for patients with PC (response rate = 68.8%); rural counties were identified as defined by the U.S. Department of Agriculture [ 21 ]. CBPs were recruited based on their participation in the [Blinded for Peer Review], a state-wide network of community-based hospital partners specializing in oncologic services. CBPs were contacted if they referred at least 1 patient to the HVC within the past 5 years; those with highest referrals were contacted first. A study recruitment letter was emailed to oncology clinicians by the study PI describing the purpose of the study and asking if they would participate voluntarily in an interview. We aimed to recruit a diverse group of clinicians that represented the different specialists along the cancer care continuum for PC care thereby enabling us to improve understanding of the varied challenges and facilitators of PC care coordination from multiple perspectives. The Ohio State University Institutional Review Board approved this study.

Clinician interviews

We developed a semi-structured interview guide to elicit information regarding the co-management and care coordination of PC patients across hospitals. In particular, we asked how HVCPs and CBPs shared information, made referrals, and used health information technology to plan follow-up care, report on patient progress, and inform cancer treatment decision-making (semi-structured interview guide available upon request).

Data collection

The first author conducted one-on-one interviews with clinicians using Zoom™, an online video conferencing platform, during Spring through Fall of 2020. One interview included two participants. Participants were allowed to choose if they wanted to have a face-to-face (i.e., video and audio on) or audio-only interview. All participants provided informed verbal consent prior to participation. Interviews lasted approximately 30 min (range = 23–45 min) and were audio-recorded and transcribed verbatim. We interviewed nine HVCPs and 11 CBPs as shown in Table  1 .

Data analysis

We analyzed the interview transcripts using both deductive and inductive approaches to allow for the categorization of data based on the interview guide (deductive), as well as identification of emergent themes (inductive) [ 22 ]. A preliminary coding dictionary was created by [Blinded for Peer Review] based on the questions in the interview guides and themes that emerged during the initial review of interview transcripts. The same two authors then independently applied the codebook to the first nine interview transcripts and met frequently to compare coding processes and address coding discrepancies, refine codebook definitions, and discuss new themes. [Blinded for Peer Review] then coded the remaining transcripts using the refined codebook to ensure coding consistency. This coding was supervised by the first author who has years of qualitative research experience and qualitative methods training, and overseen by a senior investigator [Blinded for Peer Review], a qualitative methods expert. We reached saturation [ 23 ] with respect to the themes that emerged based on the consistency of comments across institution types (i.e., HVCP vs. CBP). We used the ATLAS.ti qualitative data analysis software (version 6.0; Scientific Software Development GmbH; Berlin, Germany) to support our analysis.

Coordination challenges

Across HVCP and CBP interviews, participants commented on the challenges associated with PC care coordination; specifically, (1) closed-loop communication and (2) patient co-management. Below, we explore these two themes in greater detail, with additional supporting quotations presented in Table  2 .

Closed-loop communication

Participants described challenges with obtaining updated medical records and treatment plans from other institutions and lack of a shared electronic health record (EHR) system. First, with respect to not exchanging medical record updates, participants felt clinicians could do better keeping track of how patients responded to treatment or what was accomplished during clinical visits. As one participant noted, “And [the CBP] didn’t record a comment in the notes [about] how [the patient’s] clinical symptoms changed with treatment, so that, that gets me a little frustrated” (HVCP). Second, not sharing an EHR was perceived to have a negative impact on HVCP-CBP communication. One clinician explained:

I was saying, communication is harder when providers don’t share the same [electronic health record] system, right? So, you can’t just send an email on your [HVC] email address and you don’t have everybody’s cell phone. And calling doctors’ offices to get a hold of people is extremely cumbersome and often not successful (HVCP).

Given this aforementioned challenge, one clinician also highlighted the need to receive timely updates, “You know, if everyone’s on the same EMR [Electronic Medical Record], if something went to the inbox of the provider, either the referring provider or like an alert or something, I think that would also be helpful” (HVCP).

• Patient co-management

Participants also described challenges associated with PC patient co-management. The major challenge reported was the communication of recommendations between clinicians across institutions and their patients. For example, one participant explained how conflicting recommendations could create confusion for patients:

So, you might get somebody saying one thing and somebody else saying another thing, and ultimately maybe the difference isn’t even that large. But in the patient’s mind, if they’re getting different messages, I think that creates some level of uncertainty… (CBP).

Some participants commented on having to rely on patients to relay treatment recommendations and messages to other clinicians as patients’ care needs evolved. One participant noted, “I reiterate that this is either what I would do or what this is currently what’s recommended and then [the patient] takes that back to their local provider…” (HVCP). Another clinician offered a similar view, reflecting on the challenges of co-managing a PC patient with clinicians working in a different institution:

Every phone call had very detailed instructions of what to do and then eventually when [the patient] came back for me to make a judgment about the response, we didn’t have appropriate scanning again. We didn’t have appropriate lab tests despite all that effort from both the patient and the [HVC] staff. So I’m not really sure what to do honestly (HVCP).

Strategies to improve coordination: multidisciplinary tumor boards

In light of these challenges, participants identified strategies to improve cross-institutional coordination for PC patients. Participants’ suggestions primarily focused on augmenting multidisciplinary tumor boards—conferences to discuss cancer cases and exchange knowledge and ideas—with (1) a coordinator role, (2) meeting documentation and dissemination, and (3) teleconferencing to facilitate CBP engagement during multidisciplinary tumor boards. In the reporting of our findings, we distinguish among institutional affiliations (i.e., HVCP vs. CBP) because clinicians’ perspectives about these three strategies differed by location.

Tumor board coordinator

HVCPs noted that having a designated tumor board coordinator would help address communication challenges between HVCPs and CBPs. For example, having a liaison take notes and share the tumor board’s recommendations with CBPs could ensure that the pertinent information was communicated. One clinician described how this could look in practice,

Maybe having one person, and it could be the person who organizes the tumor board each week […] documenting each case and what the right recommendation is. And then having that individual be the point person to communicate the record, those recommendations, making sure that is not missed (HVCP).

HVCPs also described how this coordinator role could facilitate the sharing of information discussed at tumor board meetings, to remind CBPs to perform specific tests or scans on PC patients. As one clinician explained,

But then if you have a coordinator at the tumor board who is a liaison, then we can quickly say, ‘Hey, like patient ABC at tumor board need scans done locally, need this done locally.’ That could be something that we could add and update our tumor boards (HVCP).

Tumor board documentation and dissemination

CBPs described the potential advantage of having HVC tumor board discussions documented and forwarded to them. Participants indicated that these documents could assist with updating CBPs about the treatment plans that were developed during tumor boards and what HVCPs recommended in terms of co-managing PC patients. One clinician said,

I wonder if [the tumor board discussion] would be something that could ever go into a formal documentation of, ‘Hey, this is what we discussed, this is the conclusion of the tumor board,’ so that it’s the board directly, or streamline or send the providers who are co-managing these patients… (CBP).

Another clinician explained how documentation of tumor board discussions would facilitate patient co-management,

And maybe having like a formal tumor board type document that has that recommendation, so that doctors in the community, who may not see pancreatic cancer as much, have more of a footing to stand on and might feel more comfortable treating patients. And, then I think that would help deliver the standard that [HVC] is trying to provide (CBP).

Tumor board teleconferencing

Several CBPs indicated they would be interested in using teleconferencing to participate in in HVC-based tumor boards to better understand what other clinicians were thinking and to make decisions regarding the patients they co-managed. One participant expressed their willingness to be a virtual tumor board participant,

So, maybe just having a link into the individual tumor boards down there [at the HVC], where you can get the opinion of all the experts in the room real time and not have to worry about like, getting the information faxed and stuff like that. Being part of the actual discussion […], and just being able to add on patients that you mutually share […]. The communication in that room will be very direct and nothing will get lost (CBP).

Participants identified teleconferencing tools such as Zoom™ as another potential facilitator of HVCP-CBP coordination. One CBP noted how these tools could improve coordination,

It would be pretty cool to get invited to [the HVC pancreatic cancer tumor board]… The navigator would say, ‘Hey, your patient’s being discussed, you know, three days from now.’ And you can call in to a Zoom meeting and listen in or even give some input about how hard it is [for the patient] to come up there […] And I think that would elevate the coordination of care pretty significantly (CBP).

An enabling condition: building rapport

Participants noted that building rapport with clinicians in other institutions is an enabling condition necessary for optimizing PC care coordination. For example, having face-to-face meetings and having an opportunity to share personal contact information reportedly enabled communication. For instance, one participant explained how these meetings affected coordination:

[The HVC surgeon] came up to our facility and met us personally, took a tour around, basically gave us their cell phone number and so, we just text them. We send images, patient history, and then we fax information to the office. And they’ll arrange an office visit when that’s possible (CBP).

A HVCP also explained how face-to-face meetings allowed them to foster relationships and how it improved clinician communication:

I think they’re much more likely to communicate with you if they’ve ever met you. So, I mean a lot of the people I’ve actually went and met and so then just, you know, fostering those relationships. I would say once you’ve called them once or twice and keep them up to date about how their patients are doing, they’re very thankful and appreciative of that (HVCP).

Just as face-to-face meetings were noted to contribute to better communication because clinicians could “actually have a name and a face and a phone number” (CBP), sharing information in a timely manner also encouraged relationship building. One participant explained, “just making sure that all [the HVCP’s] recommendations and information is communicated with the referring provider and in a timely fashion is a good way to foster relationships” (CBP).

In our qualitative study of cancer specialists who treat or manage patients with PC, we identified themes around the challenges of and strategies to improve cross-institutional PC care coordination. Participants reported poor communication and limited information sharing across institutions as barriers to effective PC care coordination. To address these barriers, clinicians at both HVCs and community-based hospitals identified strategies to promote coordination via improvements to multidisciplinary tumor board infrastructure and processes as well as by strengthening relationships between HVCPs and CBPs.

Similarly, extant literature suggests that optimal care coordination [ 24 ] improves outcomes for patients undergoing multidisciplinary treatment for cancer. Specifically, in a recent systematic review and meta-analysis, the authors found optimal cancer care coordination led to improvements in 81% of measured outcomes; these included improvements in screening, patient-reported experiences with care, and quality of end-of-life care [ 25 ]. In this vein, our findings highlight some of the challenges that HVCPs and CBPs encounter co-managing rural PC patients that may contribute to less optimal care coordination. For example, we found both HVCPs and CBPs reported similar difficulties with respect to coordinating care for PC patients because their respective institutions did not share a common EHR system; thus, hindering closed-loop communication. This is critical, as effective communication and cooperation across the multidisciplinary team was also identified as a key component to effective care coordination in similar studies [ 26 ]. Challenges with effective two-way communication were thought to directly impact patients by requiring them to act as the intermediary between clinicians. In this context, lack of communication between clinicians may lead to duplicated tests, delayed time-to-treatment, or other adverse outcomes related to cancer care [ 15 , 16 , 17 ]. For these reasons, it is essential to highlight the need for improved communication across institutions to improve healthcare delivery efficiency, patient safety, and outcomes.

It is also notable that clinicians identified both an enabling condition and facilitators of care coordination that involve enhancements to multidisciplinary tumor boards. Unlike one-on-one provider meetings or consultations, tumor boards [ 27 ] are “dedicated conferences where multiple care teams meet to discuss the management of patients with cancer to agree upon diagnostic, treatment, and surveillance plans and to coordinate patient care.” Several types of providers are invited to log into a video conference remotely and participate, including cancer specialists and other providers and allied health professionals to address the care planning needs of complex patients. In addition to addressing deficiencies in exchanging treatment plans and records, co-participation in tumor boards was seen as a potential process improvement option. Often, tumor boards are limited to clinicians at a single institution. With the emergence of videoconference technology, there have been several studies showing the benefit of cross-institutional tumor board meetings that can be held virtually [ 28 , 29 ]. For example, a recent review found virtual tumor boards for lung cancer patients encouraged interaction among large referral cancer centers and community hospitals [ 29 ]. These findings are similar to a case study that found CBPs valued being involved in the tumor board discussion, and the meetings served as an opportunity for clinical trial recruitment [ 30 ]. Further research that examines the impact of community-based clinician participation in tumor boards on care coordination and patient outcomes is warranted. Moreover, in addition to providing a multidisciplinary evaluation for PC patients, virtual tumor boards may serve as a platform to promote relationship-building between HVCPs and CBPs. These conferences can offer opportunities for clinicians to discuss the co-management of critical aspects of a patient’s care [ 31 ]. Given our findings, it will be important to explore whether and to what extent familiarity amongst HVCPs and CBPs predicts communication timeliness and quality within the context of cross-institutional management of patients with PC in future research.

There are limitations to our study. First, our research involved clinicians directly (employed) or indirectly (provide referrals for) associated with a single institution, limiting the generalizability of our findings to other clinicians (e.g., primary care physicians), non-clinicians (e.g., social workers, psychologists), and health care systems (e.g., the National Health Service). For instance, we did not interview primary care or other allied health professionals who play a central role in planning the care of patients undergoing treatment for PC [ 32 ]. Therefore, the application of our findings may be limited to cancer specialists. Nonetheless, our study included clinicians across all cancer specialties and several different institutions enabling us to comprehensively evaluate clinicians’ perspectives across a wide range of practice settings in this region. Second, our study focused on cross-institutional coordination specific to PC care and may not represent challenges faced by clinicians treating or co-managing patients with other cancers. Patients with PC, however, face complex treatment decisions, [ 33 ] and thus the current study may provide useful information for clinicians who must overcome similar barriers when coordinating complex care for patients across multiple institutions. Finally, although we cannot be certain of the extent to which COVID-19 influenced coordination between HVCPs and CBPs, we do know that the HVC paused in-person outreach with CBPs when social distancing protocols were in effect. These restrictions likely made it difficult for HVCPs and CBPs to build rapport, but they may have had a negligible impact on HVCP-CBP coordination as telephonic and other electronic means of communication were already commonly used.

Effective care coordination is a vital part of caring for patients with PC who, for various reasons, receive concurrent treatment at community-based practices and HVCs. Problematic communication and information exchange between HVCPs and CBPs seriously challenge cross-institutional care coordination and may impact the quality of care patients receive [ 25 , 34 ]. Taking steps to improve efficiency in communication may help facilitate the development of cohesive treatment plans and promote coordination. Future efforts should leverage existing communication tools and provide opportunities for collaboration and relationship building across care teams and institutions.

Data availability

The data generated and analyzed during this study are not publicly available to protect the confidentiality of study participants. De-identified data from this study will be made available on a per case basis (as allowable according to institutional IRB standards) by emailing Dr. Aslam Ejaz, MD, MPH ([email protected]).

Abbreviations

Community-based provider

Electronic health record

High-volume center

High-volume center provider

• Pancreatic cancer

Rawla P, Sunkara T, Gaduputi V. Epidemiology of pancreatic Cancer: global trends, etiology and risk factors. World J Oncol Feb. 2019;10(1):10–27.

Article   Google Scholar  

Shaib YH, Davila JA, El-Serag HB. The epidemiology of pancreatic cancer in the United States: changes below the surface. Aliment Pharmacol Ther Jul. 2006;1(1):87–94. https://doi.org/10.1111/j.1365-2036.2006.02961.x .

Nevala-Plagemann C, Hidalgo M, Garrido-Laguna I. From state-of-the-art treatments to novel therapies for advanced-stage pancreatic cancer. Nat Rev Clin Oncol Feb. 2020;17(2):108–23. https://doi.org/10.1038/s41571-019-0281-6 .

Tempero MA, Malafa MP, Al-Hawary M, et al. Pancreatic adenocarcinoma, Version 2.2017, NCCN Clinical Practice guidelines in Oncology. J Natl Compr Canc Netw Aug. 2017;15(8):1028–61. https://doi.org/10.6004/jnccn.2017.0131 .

Sohal DPS, Kennedy EB, Cinar P, et al. Metastatic pancreatic Cancer: ASCO Guideline Update. J Clin Oncol Aug. 2020;5:JCO2001364. https://doi.org/10.1200/jco.20.01364 .

Visser BC, Ma Y, Zak Y, Poultsides GA, Norton JA, Rhoads KF. Failure to comply with NCCN guidelines for the management of pancreatic cancer compromises outcomes. HPB (Oxford) Aug. 2012;14(8):539–47. https://doi.org/10.1111/j.1477-2574.2012.00496.x .

[Blinded for Peer Review].

Jaap K, Fluck M, Hunsinger M, et al. Analyzing the Impact of Compliance with National guidelines for pancreatic Cancer Care using the National Cancer Database. J Gastrointest Surg Aug. 2018;22(8):1358–64. https://doi.org/10.1007/s11605-018-3742-9 .

Birkmeyer JD, Siewers AE, Finlayson EV, et al. Hospital volume and surgical mortality in the United States. N Engl J Med. Apr 2002;11(15):1128–37. https://doi.org/10.1056/NEJMsa012337 .

Finks JF, Osborne NH, Birkmeyer JD. Trends in hospital volume and operative mortality for high-risk surgery. N Engl J Med Jun. 2011;2(22):2128–37.

Beal EW, Bagante F, Paredes A, et al. Index versus non-index Readmission after Hepato-Pancreato-biliary surgery: where do patients go to be readmitted? J Gastrointest Surg Apr. 2019;23(4):702–11. https://doi.org/10.1007/s11605-018-3882-y .

Aquina CT, Probst CP, Becerra AZ, et al. High volume improves outcomes: the argument for centralization of rectal cancer surgery. Surg Mar. 2016;159(3):736–48. https://doi.org/10.1016/j.surg.2015.09.021 .

Latchana N, Davis L, Coburn NG, et al. Population-based study of the impact of surgical and adjuvant therapy at the same or a different institution on survival of patients with pancreatic adenocarcinoma. BJS Open Feb. 2019;3(1):85–94. https://doi.org/10.1002/bjs5.50115 .

Article   CAS   Google Scholar  

Hopstaken JS, van Dalen D, van der Kolk BM, et al. Continuity of care experienced by patients in a multi-institutional pancreatic care network: a pilot study. BMC Health Serv Res May. 2021;3(1):416. https://doi.org/10.1186/s12913-021-06431-2 .

Albano D, Bilfinger T, Feraca M, Kuperberg S, Nemesure B. Dec. A multidisciplinary Lung Cancer Program: does it reduce Delay between diagnosis and treatment? Lung . 2020;198(6):967–72. https://doi.org/10.1007/s00408-020-00404-8

Enomoto LM, Fenstermaker J, Desnoyers RJ, et al. Oncology Navigation decreases time to treatment in patients with pancreatic malignancy. Ann Surg Oncol May. 2019;26(5):1512–8. https://doi.org/10.1245/s10434-019-07157-6 .

Beesley VL, Janda M, Burmeister EA, et al. Association between pancreatic cancer patients’ perception of their care coordination and patient-reported and survival outcomes. Palliat Support Care Oct. 2018;16(5):534–43. https://doi.org/10.1017/s1478951517000608 .

Noyes K, Monson JRT, Rizvi I, Savastano A, Green JSA, Sevdalis N. Regional Multiteam systems in Cancer Care Delivery. J Oncol Pract. 2016;12(11):1059–66. https://doi.org/10.1200/jop.2016.013896 .

Article   PubMed   PubMed Central   Google Scholar  

Creswell JW, Plano Clark VL. Designing and conducting mixed methods research. 3rd ed. SAGE; 2017.

Palinkas LA, Horwitz SM, Green CA, Wisdom JP, Duan N, Hoagwood K. Purposeful sampling for Qualitative Data Collection and Analysis in mixed method implementation research. Adm Policy Ment Health Sep. 2015;42(5):533–44.

U.S. Department of Agriculture. Rura-Urban Continuum Codes, Published. December 10, 2020. https://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx . Last accessed: August 08, 2022.

Armat MR, Assarroudi A, Rad M, Sharifi H, Heydari A. Inductive and deductive: ambiguous labels in qualitative content analysis. Qual Rep. 2018;23(1):219–21. https://doi.org/10.46743/2160-3715/2018.2872 .

Hennink MM, Kaiser BN. Saturation in Qualitative Research. In: Atkinson P, Delamont S, Cernat A, Sakshaug JW, Williams RA, eds. SAGE Research Methods Foundations . 2019.

Agency for Healthcare Research and Quality. Care Coordination. Published. August 2018. https://www.ahrq.gov/ncepcr/care/coordination.html . Last accessed: August 08, 2022.

Gorin SS, Haggstrom D, Han PKJ, Fairfield KM, Krebs P, Clauser SB. Cancer Care Coordination: a systematic review and Meta-analysis of over 30 years of empirical studies. Ann Behav Med Aug. 2017;51(4):532–46. https://doi.org/10.1007/s12160-017-9876-2 .

Walsh J, Young JM, Harrison JD, et al. What is important in cancer care coordination? A qualitative investigation. Eur J Cancer Care (Engl). Mar 2011;20(2):220–7. https://doi.org/10.1111/j.1365-2354.2010.01187.x .

Davis CH, Ho J, Stephenson R et al. (2022). Virtual tumor board increases provider attendance and case presentations. JCO Oncol Pract. Aug 2022;18(10):e1603-10.

Stevenson MM, Irwin T, Lowry T, et al. Development of a virtual multidisciplinary lung cancer tumor board in a community setting. J Oncol Pract May. 2013;9(3):e77–80.

Gebbia V, Guarini A, Piazza D, et al. Virtual multidisciplinary tumor boards: a narrative review focused on Lung Cancer. Pulm Ther Dec. 2021;7(2):295–308.

Shea CM, Teal R, Haynes-Maslow L, et al. Assessing the feasibility of a virtual tumor board program: a case study. J Healthc Manag May-Jun. 2014;59(3):177–93.

Google Scholar  

Rose DE, Tisnado DM, Tao ML, et al. Prevalence, predictors, and patient outcomes associated with physician co-management: findings from the Los Angeles women’s Health Study. Health Serv Res Jun. 2012;47(3 Pt 1):1091–116.

Abma IL, Roelofs LCG, van der Kolk MB, et al. Roles of general practitioners in shared decision-making for patients with cancer: a qualitative study. Eur J Cancer Care (Engl) Jul. 2022;31(4):e13594.

Walczak S, Velanovich V. Improving prognosis and reducing decision regret for pancreatic cancer treatment using artificial neural networks. Decision Support Systems . 2018/02/01/ 2018;106:110–118. https://doi.org/10.1016/j.dss.2017.12.007

Peikes D, Chen A, Schore J, Brown R. Effects of care coordination on hospitalization, quality of care, and health care expenditures among Medicare beneficiaries: 15 randomized trials. JAMA Feb. 2009;11(6):603–18. https://doi.org/10.1001/jama.2009.126 .

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The authors would like to thank the providers who volunteered to participate in this study.

The authors did not receive funding for the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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MJD was responsible for conceptualization, methodology, formal analysis, investigation, validation, writing, review, and editing. KSY was responsible for formal analysis, data curation, validation, visualization, writing, review, and editing. NAK was responsible for investigation, validation, writing, review, and editing. AS was responsible for project administration, writing, original draft, review and editing. BLW was responsible for conceptualization, writing, review, and editing. LJR was responsible for project administration, writing, review, and editing. ASM was responsible for conceptualization, methodology, supervision, resources, writing, review, and editing. AE was responsible for conceptualization, methodology, funding acquisition, writing, review, and editing.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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Harnessing the power of poetry in academic research – the author’s use of poetry as a tool for analysis

Holly Bennion, PhD graduate at Durham University 9 Sep 2024

This blog post focuses on my approach to using poetry as an analytical tool in a recent empirical study. There is an exciting body of research highlighting the potential for incorporating poetry into the various stages of the research process. Writing and sharing poems can be an effective data collection method, whereby poems are constructed by/with participants to explore their stories, feelings and memories. Poetry can also be used as an analytical/interpretative lens – for example, Carr (2003) created poems to document the experiences of family members of hospitalised relatives, transforming interview transcripts into poetry. Researchers can also use poetry to disseminate educational research and extend the tone and scope of research communication. The growing emergence of poetry in research, underpinned by arts-based research, is also connected to theoretical insights by postmodern, poststructural and feminist theories, which invites transformative and inclusive possibilities for research that goes beyond hegemonic and traditional forms of knowledge (Cutts & Sankofa Waters, 2019).

My PhD research explored children’s experiences and perspectives of belonging and school inclusion. I explored the interconnectivity in discourses on self-identification, otherness and school inclusion in multilingual and multicultural spaces. The methods included focus groups, children’s artwork, co-analysis with participants, and dance and drama workshops. As part of the data analysis process, I chose to experiment with poems. This process involved going back and forth between the transcriptions, the NVivo coding, and looking closely at the participants’ artwork and what they said about it.

To begin the process, I experimented with free-verse poetry, whereby I attempted to use poetry to identify connections between participants’ comments, further identify themes and keywords, and document my own reflections and feelings as I delved into the data.

Then, I began experimenting with structure and specific words and phrases. I used linguistic devices such as repetition to illustrate aspects that the participants felt strongly about or things they mentioned frequently. I experimented with using short, snappy lines or long, stream-of-consciousness lines to imply the tone of voice and the atmosphere of the workshops. I selected six poems to include in my thesis. Below is one example, which takes verbatim the words of the participants:

Something for you

It belongs to me and

I own it, just mine, not sharing

I may share it sometimes

My life, my bed

The first part of this poem reflects Aasab’s comment: ‘belonging is something for you, it’s like a surprise for you and we have to keep it’. I was interested in her view of belonging as a ‘surprise’. The exclamation mark was used to convey her excited tone of voice. The repetition of ‘my’ – ‘my life, my bed, my things’ – was utilised to highlight how participants often distinguished between what is ‘mine’ and ‘yours’.

‘Through poetry, I was liberated from the structured form of academic writing; I could experiment with themes, form, language, tone and imagery to interpret and represent the children’s comments about belonging and school inclusion.’

The notion of material possessions and human–object relationships was significant in the findings. Furman and colleagues (2007) note that poetry can be a powerful tool for communication through the playfulness of metaphor, alliteration and visual elements. Through poetry, I was liberated from the structured form of academic writing; I could experiment with themes, form, language, tone and imagery to interpret and represent the children’s comments about belonging and school inclusion. I found that poetry as an analysis tool gave me enthusiasm for and confidence in my data.

Reflecting on my research approach, I advocate that poetry can serve as a valuable analysis tool for research, and it can be utilised as part of a multi-level approach. Poetry can be a powerful tool for communicating the researcher’s reflections and interpretations of the data and representing the voices of participants in engaging ways. Importantly, I was not seeking to create a single narrative through the poetry. Poetry is open to interpretation; it is evocative and invites emotional engagement. Like my data collection methods – which invited collaboration, imagination and contradictions among participants – the poetry was an interesting tool that enabled multiple narratives, opinions and clarifications for the researcher and audience.

To conclude, I quote poet and academic Neil McBride (2009, p. 43):

‘[Poetry] questions, it leaves frayed edges and loose writes. It draws out the hidden, the spiritual, the underlying rhythms of life that we swamp with information, noise and news channels.’

Holly will be presenting at the  BERA Conference 2024 and WERA Focal Meeting on Monday 9 September at 12:45pm for a symposium panel on ‘Migration and Education across the Four Nations of the UK’. 

Carr, J. (2003). Poetic expressions of vigilance. Qualitative Health Research , 13 (9), 1334–1331. https://doi.org/DOI: 10.1177/1049732303254018

Cutts, Q., & Sankofa Waters, M. (2019). Poetic approaches to qualitative data analysis. Education Publications , 145. https://doi.org/10.1093/acrefore/9780190264093.013.993   

Furman, R., Langer, C., Davis, C. S., Gallardo, H. P., & Kulkarni, S. (2007). Expressive, research and reflective poetry as qualitative inquiry: A study of adolescent identity. Qualitative Research , 7 (3), 301–315. https://doi.org/10.1177/1468794107078511

McBride, N. (2009, December 3). Poetry cornered. Times Higher Education , 1 (925), 42–44.   https://www.timeshighereducation.com/features/poetry-cornered/409334.article

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Empirical validation of a brick-centric learning design methodology and its implementation through the Eduscript Doctor pedagogical scenario kit

• Open access
• Published: 09 September 2024

Cite this article

You have full access to this open access article

• Emmanuel Burguete   ORCID: orcid.org/0000-0003-0573-3484 1 ,
• Bernard Coulibaly   ORCID: orcid.org/0000-0002-4862-829X 1 &
• Vassilis Komis   ORCID: orcid.org/0000-0001-6909-2765 2  

To design and script courses, practitioners often collaboratively use simple and tangible tools such as Post-it notes. In light of this, research and development were conducted to develop Eduscript Doctor, an analogic tool that would retain the inductive potential of Post-it notes while structuring the pedagogical scripting process. This Design-Based Research was carried out in three stages: the initial design of the scripting methodology and the tool (3 researchers), their improvement with the participation of practitioners (11 centers), and then an external evaluation (3 teams). The latter stage took the form of a qualitative empirical study on the tool’s utility and usability by examining three MOOCs. The results of the qualitative study showed that the tool was generally useful and usable, facilitating an in-depth analysis of the scripting of the three MOOCs. However, some negative aspects emerged from the interviews, such as the tool’s apparent complexity at first glance, the long time required to store the pieces after use, and the lack of digital backup for the produced models. Among the results of this study, the foundations of a new Learning Design theory centered around the concept of “bricks” also emerged. Although it still requires further research to be stabilized, improved, and validated, a high level of abstraction carried by this new theory will be necessary to consider the tool’s future developments. In conclusion, the results of this initial study on the kit seem promising, but much more research is needed to better understand its uses, methodology, and potential audiences.

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• Artificial Intelligence
• Digital Education and Educational Technology

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1 Introduction

Whether they are teachers, trainers, or professional experts, educational practitioners face the challenge of designing and planning learning situations that are suitable for a diverse range of audiences and educational contexts (Ordu, 2021 ; Yang et al., 2023 ). These courses are sometimes complex and multimodal and can be co-designed, in part or in whole, with the help of a third party such as another teacher, a instructional designer or even sometimes on large-scale projects by an entire teaching team. Such collaboration requires in-depth exchanges and compromises to determine the structure and planning of education.

To achieve this, some teams use simple Post-its that they stick on a board to discuss their course creation and visualize its granularity (Burguete & Urrego, 2023 ). These small pieces of paper can represent a succession of learning units with their content, or any other information related to the training. We questioned this phenomenon, especially since there are now a variety of digital and analogic tools designed to facilitate the design process, which seem far more structured than these simple pieces of paper (Komis et al., 2013 ). Due to the lack of data on the practice of using Post-its in the literature, we hypothesized at the start of our research that the tangible, inductive, collaborative, and non-digital nature of Post-its was absent or at least insufficiently present in existing solutions to satisfy certain design teams. Therefore, we aimed to create a new tool meeting these criteria in the form of an analogic pedagogical scripting kit. However, the inductive nature of Post-its did not seem sufficiently structured to create effective training based on criteria such as engagement, motivation, retention, or learning performance. Consequently, we sought to incorporate the concept of microlearning, which is recognized in the literature for its effectiveness on these same evaluation criteria (Alias & Razak, 2024 ; De Gagne et al., 2019 ; Taylor & Hung, 2022 ).

Thus, in a Design Based Research (DBR) approach (Wang & Hannafin, 2005 ), we developed and implemented into several versions of the kits a new modeling language based on the concept of bricks, itself inspired by granularization and microlearning. This visual language, which takes the form of tangible pieces arranged on a board, allows for the observation of the links and distribution of activities and educational resources in the form of learning units. The aim is to guide and optimize the design and analysis process of educational scenarios.

In this production, our primary objective is to empirically demonstrate the utility and usability of this new pedagogical scenario kit through a qualitative study. In this study, we chose to test MOOCs. They have the advantage of being easily accessible, but they often suffer from low pedagogical quality (Margaryan et al., 2015 ), low learner engagement (Bote-Lorenzo & Gómez-Sánchez, 2017 ; Depover et al., 2017 ; Tcheng Blairon & Cristol, 2020 ), and high attrition rates.

To do this, we will first present the other existing analogic tools as well as the concepts of granularization and microlearning that led us to create a new scripting methodology centered on the brick. We will then describe this new methodology and how it is implemented in the kit. Next, we will present the research and development of the kit and then the empirical evaluation of its utility and usability through the modeling of three distinct MOOCs. Finally, we will describe and discuss the foundations of a new Learning Design “theory” based on the concept of bricks and the new research avenues we will pursue to continue studying the tool.

2 Related work

2.1 two existing analogical kits.

Among the pedagogical scripting tools, there is, to our knowledge, no study or literature review that provides an exhaustive reference or broadly examines their uses. Our research on the existing state of the art led us to discover six digital solutions (LearnSpirit, Learning Designer, OAS, Parcooroo, PedagoMaker, and Modulo) and two analogic kits consisting of printed cards (ABC Learning Design and Learning Battle Cards). Since our goal was to create a new analogic tool using an inductive approach similar to that of Post-its, in this article we focused only on these latter two tools to identify and understand their main specificities.

ABC Learning Design is a free downloadable tool that created in 2015 by Nataša Perović and Clive Young of University College London (UCL) ( https://abc-ld.org/ ). This academic product (Perović & Young, 2020 ) is, according to its authors, widely used in Europe and has been the subject of numerous publications listed on their website. It helps facilitate about 90-minute workshops in a dynamic and engaging way. Participants are teams of teachers who collaborate to think together about the design or analysis of teaching activities sequences. The kit consists of three distinct elements. First, printed maps representing the six learning modalities from Diana Laurillad’s “Conversational Framework” theoretical model. On the back, these cards present concrete examples of activities to be organized. In addition, the kit includes a work plan permitting the cards to be arranged according to a defined time structure. Finally, a dedicated sheet provides a clear view of the hybridization level and the respective importance of the different learning modalities. It is cooperative in nature and access is free. Besides, the advantage of this tool is its ease of use by teams during workshops. It seems to be more suitable for a novice audience of students or casual trainers rather than training experts because of its 90-minute workshop format.

The second tool we have identified is a commercial product called Learning Battle Cards ( https://store.learningbattlecards.com/ ). This tool was created in 2011 by Polish Sławomir Łais to, according to his website, “close the gap between instructional design and design thinking”. The kit consists of a set of 110 cards, printed on both sides, representing various learning methods and their uses. It is possible to purchase an additional Canvas to position the cards and thus facilitate visualizing training. Like ABC Learning Design, this approach represents a tool-driven design methodology designed to guide the user in creating or re-engineering courses. The major advantage of this method is its playful nature and that it can present an abundant variety of methods and activities, which can be particularly interesting to trainers looking for new ideas. So, just like the ABC Learning Design, this kit is based on pre-printed activity cards that guide the user in what we call a deductive approach, as opposed to the much more open and heuristic Post-it practice.

In conclusion, the operating principles of these two existing solutions seemed sufficiently different from our project to allow us to proceed. The idea of offering a pedagogical scripting kit with an inductive model seemed new and relevant to enhance the creativity and expertise of designers. However, a structuring theoretical framework was lacking for the kit, which would enable both the efficient design and analysis of training programs. This is why we decided to integrate the concepts of granularization and microlearning into a new methodology, considering both their advantages and limitations.

2.2 Granularization and microlearning

The benefit of breaking down and distributing learning over time has been known for a long time, notably since Ebbinghaus’ work on memorization (Ebbinghaus, 1885 ). It is now well established in cognitive psychology that distributed learning is superior to massed learning for memorization because it incorporates rest periods that prevent neuronal “exhaustion” and facilitate consolidation (Lieury, 2015 ).

However, the concept of granularization is not an autonomous concept, although some authors have attempted to define it (Littlejohn & Shum, 2003 ). There is a great variability in the size of segments and even in the terminology used depending on the research disciplines. For example, in microlearning, which we will discuss in more detail in this subsection, Eibl ( 2007 ), a researcher in education sciences, defined granularization in terms of breaking down content into small, autonomous units linked by specific learning objectives. In cognitive psychology, this principle of granularization is frequently used but appears under different terms. To facilitate learning, understanding, or memorization, the size of the object resulting from this idea of segmentation varies according to the developed concepts. For example, the concept of “segmentation” (Clark & Mayer, 2016 ) allows courses to be divided into smaller parts. The concept of “chunking” (Miller, 1956 ) is directly related to working memory and involves very small objects like groupings of numbers. Moreover, many current studies based on cognitive load theory also support the idea of granularizing content to facilitate learning (Sweller, 1988 ). Authors such as Alias and Razak ( 2024 ) or Lee ( 2023 ) consider cognitive load theory as one of the main theoretical underpinnings behind the effectiveness of microlearning.

According to Theo Hug, microlearning is a recent concept that appeared in the early 2000s and is still poorly defined, mainly due to a lack of research in education sciences (Hug, 2007 , 2022 ). Its development is linked to the deployment of various information and communication technologies driven by Web 2.0 (Buchem & Hamelmann, 2010 ). Carla Torgerson offers a definition based on a synthesis of several authors’ work. For her, microlearning is an educational experience that is short, focused and effective (Torgerson, 2021 , p. 20). In this sense, she aligns with Eibl ( 2007 ), who advocated for setting precise educational objectives for training units, notably using Bloom’s taxonomy. This strategy had the main advantage of defining the size of learning units and making them autonomous while keeping the possibility of linking them. Similarly, Yahaira Torres Rivera indicates that some authors draw a parallel between Lego bricks and microlearning, which consists of ““of joining small pieces to form a figure […]. Something similar happens in microlearning, where brief pieces of information are connected to achieve learning about a topic.” (Rivera, 2022 , p. 30, author’s translation).

Thus, the concept of microlearning could define the final level of the granularity process as focused, short, and effective educational experiences. In our case, in practice, a learning unit could be represented by a Post-it and associated with others to form a coherent mono or multimodal pedagogical script. However, in a broader modeling context, the inherent short nature of microlearning quickly appeared as a limitation for producing or analyzing certain training programs. Therefore, in the next chapter, we propose to adapt the concepts of granularization and microlearning into a new scripting methodology based on the concept of “bricks”.

3 Description of the scriptwriting methodology and the main principles of the pedagogical scenario kit

3.1 a brick-based pedagogical design methodology.

To produce a methodology that would guide the design of an a priori training (prescriptive scenario) or its a posteriori analysis (descriptive scenario) to carry out a pedagogical diagnosis, we first sought means to that end and looked at the concepts of granularization and microlearning. Their common characteristics such as small size, short duration, and their potential for multimodality (Fidan, 2023 ; Kohnke et al., 2023 ) seemed ideal for distributing learning and optimizing training (Celik & Cagiltay, 2023 ; De Gagne et al., 2019 ; Kapp & DeFelice, 2019 ; Leong et al., 2021 ). However, we quickly realized these characteristics, which have long been known, particularly in cognitive psychology, to be effective for a number of outcomes such as memorization or attention (Ebbinghaus, 1885 ; Kelley & Whatson, 2013 ; McBride & Cutting, 2019 ; Toppino et al., 1991 ), were not sufficient to model all existing forms of courses. Indeed, many training courses such as university lectures, often characterized by massive content, could not be easily segmented. Therefore, we have refocused our thinking on adjusting these characteristics to make them compatible with all types of training. With this in mind, we identified three key variables: the number of tracks (from one to many), their sizes (reduced to massive) and their durations (short to long). These variables constitute a more flexible and adaptable attempt at modelling, considering the diversity of training structures and contents. As a result, granularization and microlearning, which we initially considered as a means to script, have, in our methodology, been adapted rather as a goal to be achieved during design, in order to facilitate the distribution of learning and reduce the duration of activities.

We realized it was very important each piece content should be able to model not only moments of formal teaching, but also informal learning periods. This approach aims to make our model capable of representing the diversity of teaching and learning formats.

In addition, as our modeling approach is based on a temporal sequence, we also wanted to be able to represent breaks and resting moments. These elements, although apparently non-educational, are nevertheless, as we saw earlier, of utmost importance in the process of memorization and assimilation of knowledge.

The need to contextualize a training course in time and space prompted us to give kit users the possibility to define different modalities for each piece, by specifying its synchronous or asynchronous, face-to-face, or remote natures, as well as the activity’s collaborative or autonomous nature. It should be noted that, for each piece, the duration to carry out the activity can be defined a priori by the teacher or left to students’ discretion, especially in an asynchronous and remote context.

The choice of the term “brick” aims to embody, in a precise and versatile way, our model fundamental elements. We first explored various existing expressions such as Learning Unit, Learning Object, Learning Nugget, Educational Capsule, Quick Learning, Snackable Learning, Bite-sized Learning, Nano Learning, Tiny Courses, Spaced Learning, Rapid Learning, among others that are widely used in the literature. Although these terms reflect similar pedagogical approaches, often characterized by brevity, specificity, and ease of assimilation, they did not fully correspond to all the dimensions we wished to encompass. Some were too specific to particular fields, such as the association of Learning Object with computer science, while others lacked the flexibility to represent the diversity of practices. That is when the term “brick” emerged as the most appropriate choice. As Yahaira Torres Rivera pointed out ( 2022 ) with the Lego game, the brick metaphor encompasses modularity, flexibility of assembly, and the ability to build something solid from fundamental elements of all sizes. These bricks are universal, as is our pedagogical approach, which aims to be adaptable to a variety of educational contexts, ranging from formal to informal. Moreover, the use of this term transcends the connotations specific to a particular field, providing linguistic flexibility that perfectly matches the diversity inherent in our approach. Thus, the choice of the term “brick” is not just a semantic decision, but a strategic deliberation to encapsulate the versatility, solid foundation, and ability to assemble inherent in each of our pedagogical approach elements.

Now we have detailed the context of the kit creation and conceptual bases, we propose to move on to describing how the educational scenario kit works.

3.2 How the educational scenario kit works Footnote 1 : the principle

The kit Eduscript Doctor comes in the form of a box that contains several pieces to be assembled and arranged on a plan. It requires erasable color markers to write information on the different pieces. The content is divided into two distinct parts, with parts of the tray being found systematically and main and complementary pieces varying in number and location depending on the design (Fig.  1 ).

Overview of the Eduscript Doctor pedagogical scenario kit (Prototype 2.4)

Unlike the other kits, it deliberately does not offer any activities, so as not to limit the designer to the specific proposals integrated into the tool, and thus encourage his creativity.

In accordance with the major guidelines previously mentioned for creating the tool, the user is invited to follow an inductive approach using the Post-it practice as a reference, with pieces to be filled in. However, our intention was to adjust the design experience towards more than just a blank sheet of paper, with a view to facilitating the creative process. In our approach, the brick, which is our generic Learning Unit, is equivalent to an optimized Post-it. In Fig.  2 , each part is provided with several essential pieces of information.

Information to note about each skill representing an activity and possible links

First, a unique code is used to identify each activity. In addition, it is necessary to specify the activity’s duration, type (active or passive), the associated learning objectives, the learning modality (synchronous or asynchronous, face-to-face or distance, individual or collaborative), and the learner’s role (actor, spectator, or passive). Possible links to other pieces, identified or not by a code, complete this information, offering the possibility to enrich activities with additional resources, to view reminders, or access other activities. The brick part of the kit can be found in Appendix 1 – Table  7 , ID 1. We observe that defining a precise objective makes the brick autonomous and that, if its duration is also short, this unit corresponds to Carla Torgerson’s definition of microlearning as a focused, short, and effective educational experience.

In the context of course scripting, multiple bricks and their targeted objectives can complement a set of more general objectives that will be defined at the level of a piece of the kit dedicated to sessions (Appendix 1 – Table  6 , ID 2) or more broadly on a large piece representing a sequence (Appendix 1 – Table  6 , ID 1).

To further facilitate the design process, we created, in addition to the general-purpose brick mentioned earlier, three other main pieces with the same characteristics but specialized (Appendix 1 – Table  7 ). The first is dedicated to communicating educational objectives to learners (blue piece, Fig.  3 ), the second to all types of assessments (green piece, Fig.  3 ), and the third to learning how to use an artifact (instrumentation process (Rabardel, 1995 ) (Appendix 1, Table  7 , ID 4).

Principle of multiple linkages between two sessions different activities and resources

With these four main pieces more or less associated and linked, the objective was to lead the designer to communicate educational objectives to learners, promote the use of assessments, particularly formative, visualize the distribution of learning, visualize the type of learner engagement (active or passive), and finally manage and make visible the links between activities with recall or call pieces (Appendix 1 – Table  8 , ID 1 and 2).

As far as links are concerned, the principle is based on assigning a code to each Learning Unit or brick, identified in Fig.  3 by letters. The kit’s coding system will be more complex, so as to better locate each of the pieces in the sequence and sessions.

We observe that in activity G of session 1, a reminder of activities B and C is carried out using a dedicated piece. At the end of sessions 1 and 2, evaluation activities show up in green and the content to be evaluated is clearly marked out (GH and GOP). It should be noted it is possible to establish links between sessions 1 and 2 as in activity N, thus allowing recalls from one session to another (D in session 1 and KL in session 2 in N). In addition, for the activities dedicated to the definition of the pedagogical objectives represented by the blue pieces, the links offer the possibility to specifically identify the content that will be highlighted, as for activity J. In our case, the result of assessment I will modify session 2 learning objectives, thanks to the link from I to J.

Finally, in Fig.  4 , we can see that an activity can be composed of one or more resources or become a resource for another activity using a link. Several complementary and optional components are integrated into the kit to remind the user that they can proactively (before) and retroactively (after) include evaluations, motivational elements, and feedback in an activity (module) (Appendix 1 – Table  8 ).

Principle of modelling an activity consisting of resources or one or more other activities

In this example, we can see the activity scheduled after the break (red piece (Appendix 1 – Table  8 , ID 8)) includes resources related to motivation, as found at the beginning of the activity (purple piece (Appendix 1 – Table  8 , ID 6)), proactive feedback (yellow piece (Appendix 1 – Table  8 , ID 5)) and then, at the end of the activity, a retroactive evaluation (green piece (Appendix 1 – Table  8 , ID 4)). It continues with another activity that also includes a retroactive assessment.

In conclusion, faced considering the possibility of creating a new methodological tool that meets this dual requirement of orientation and creativity stimulation during the scriptwriting process, we have set ourselves a threefold research objective. First, so as to design a scripting methodology that favors a heuristic approach based on an adaptation of granularization and microlearning concepts. Then, to create an analogicalscriptwriting tool that would embody this new methodology through a well-suited visual language, whose main operating principles we have already outlined. Finally, as a last objective, evaluate theses usages of this tool in ordinary contexts to assess its strengths and limitations.

To achieve these objectives, we conducted a design process continued in usage (Goigoux, 2017 ) similar to DBR (Renaud, 2020 ; Wang & Hannafin, 2005 ). This approach unfolds in three sequential steps. The first step involves the initial design of the tool and its methodology. The second step is dedicated to their improvement with the participation of practitioners. The third step focuses on the external evaluation of the tool. In this final phase, our article is limited to studying the utility and usability of the kit by modeling a series of three different MOOC-type training cases. Our research question is: “Is the Eduscript Doctor pedagogical scenario kit useful and usable for designing MOOCs?” We then formulate the following main hypotheses to assess utility and usability respectively: firstly, the scripting kit enables a clear visualization of the structure of a MOOC, thus facilitating the evaluation of its pedagogical design. Secondly, we postulate that the kit is suited to an audience of instructional designer.

4 Methodology

4.1 research & development of eduscript doctor.

A research and development (R&D) process for the tool took place from December 2021 to May 2023, following an agile similar to DBR approach (Wang & Hannafin, 2005 ). The design began with the creation of an initial series of prototypes in a Fablab, using recycled products. Once the first manufacturing process was stabilized, 26 examples were developed and tested in 11 different centers in France, including universities, adult education centers and tennis clubs. Each center has signed a Material Transfer Agreement and has completed at least 3 h of training on how to use the kit, either online or one-on-one.

The informal feedback obtained during training sessions, as well as interviews and suggestions for modifications received via email, have been carefully considered in developing the kit. Subsequently, a more formal questionnaire comprising 22 open and closed questions was sent to all teams to assess usage, covering utility, usability, and acceptability (Béguin & Cerf, 2004 ; Renaud, 2020 ) (Table  1 ).

From January to March 2023, 22 responses from unique users or teams were collected. Based on the various comments, further exchanges via email or videoconference took place to improve the tool. The main critiques were related to the kit’s usability. For example, the tokens related to cognitive, motor, and emotional educational objectives positioned above the main pieces were extremely long to put away in the dedicated bags. Consequently, these tokens were directly integrated into the main pieces. The taxonomies used to define the educational objectives were difficult to master, and some pieces had pictograms that were hard to understand. To address this, a “‘Memo” piece was added that includes a modified version of Bloom’s taxonomy for the cognitive field (Anderson & Krathwohl, 2001 ; Bloom et al., 1956 ), Berthiaume and Daele’s taxonomy for the motor and emotional fields ( 2013 ), and legends for the various pictograms, as detailed in Appendix 1, Table  6 , ID 6.

Lastly, as a significant improvement, the organization of the pieces was enhanced using a thermoformed plastic tray. Due to the reduction in the number of pieces and the use of new materials (polypropylene) to produce the pieces, the weight of the kit was significantly reduced by approximately 57% between version 1.7 and the final version 2.4 (from 6.61 lbs to 2.87 lbs).

Thus, in September 2023, a stable version of the kit (v. 2.4) in French and then in English was created after 14 intermediate versions that took all these parameters into account.

The name “Eduscript Doctor”, chosen in September 2023 to designate this tool, was carefully selected to capture and embody the core academic values of this analogical instrument dedicated to pedagogical scripting.

To test and exemplify the use of the pedagogical scenario kit, it was necessary to consider the possibility of modeling any type of training, ranging from the simplest teaching scenario (massed unimodal) to the most complex (distributed multimodal). In this study, our choice of the type of training to focus on MOOCs due to their ease of access but primarily because of their numerous critiques for low educational quality (Margaryan et al., 2015 ), leading to low engagement (Bote-Lorenzo & Gómez-Sánchez, 2017 ; Depover et al., 2017 ; Tcheng Blairon & Cristol, 2020 ) as well as high attrition rates (Sun et al., 2019 ). As a result, the modeling of three MOOCs that had not been previously designed with the tool seemed relevant to us to initially assess its utility and usability.

4.2 Conduct of the study

A call for projects was launched on internet on 14 October 2022 to find 3 teams willing to test the kit for future re-engineering of their MOOC. Three teams quickly came forward to participate in the research protocol. Participation involved receiving training on the kit (either remotely or in person) and then testing the kit on their MOOC in a second phase.

The three teams wanted to model their MOOC with a more or less re-engineering objective (Table  2 ). The majority of those trained in using the kit were instructional designers (or similar professionals) as well as audio-visual technicians who had participated in the scripting.

The training was divided into two distinct parts. The first part consisted of presenting the kit research and development, the link between the kit, pedagogical scripting and microlearning. Workshops were organized to enable the creation of increasingly complex and multimodal scenarios by gradually using the different parts of the kit (Appendix 1 ). In the second part of the training, the focus was exclusively on the scripting of their MOOC with dedicated support.

An initial modeling was carried out using the French 1.7.2 version of the kit, but was updated for the article in the September 2023, 2.4 version and then translated into English. Durations in the code dictionary are calculated based on the types of resources used or empirically determined. As for the text, reading time was set via online tool Textconverter.io with the “voice-over” and “Normal” playback rhythm settings. Videos total watch time was used. An acceptable average duration was defined by the team for evaluations or other activities that do not have a fixed time.

It is important to point out that all three teams also took part in the research and development of the kit after this study, which means that, thanks to their active participation, they were familiar with the evolution of the parts.

To evaluate the utility and usability of the kit, a qualitative approach based on observations and non-directive interviews during the training and modeling was used. The evaluation criteria were selected from the questions in Table 1 of the questionnaire. Only questions 5 and 6 on utility were not suitable for our evaluation context.

In the next chapter, we detail the results of the modeling of three MOOCs developed using the pedagogical scenario kit by the three design teams. Then, we provide a synthesis of the observations and non-directive interviews conducted with the three teams to evaluate the utility and usability of the kit and its methodology.

Two different platforms are used to disseminate 3 MOOCs whose scripts we will describe. The first is that of Team 1 for the MOOC “Guidance education” (Fig.  5 ), and the second that of Teams 2 and 3 for the other two MOOCs “Everything you need to know about itching” and “Adolescent development”. In both platforms, it will always be necessary to keep in mind the modeling represents a path logic even if, in the end, this path is not followed in its linearity or in its entirety by a typical learner.

Screenshot of the general organization of the MOOC “ Guidance education ”

Modelling these different training courses is carried out in its entirety using the 2.4 English version of the pedagogical scenario kit, with precision and without any synthesis. They offer a linear and temporal graphical representation of the different possible learners’ paths extracted from the platforms. In this study, it is important to remember the 3 models presented are only the result of a retrospective analysis carried out with the teams and that the scripting methodology was not used to create them.

The three MOOCs were ranked from the simplest to the most complex. Each scenario is followed by a simplified code dictionary for readability. In Appendix 2 , a complete code dictionary for each MOOC (Appendix 2 – Tables  9 , 10 and 11 ) lists each Learning Unit, any objectives, durations and some information on the activities. The precise description of each of the activities and their content is not included in the article, in order to focus it more on form than substance. Nevertheless, the pedagogical scenario obviously has a very strong impact on the proposed disciplinary content, since it must be suited by designers to allow constructive alignment (Biggs, 1996 ). The goal is to ensure that assessments and learning objectives are well aligned with the learning activities implemented.

5.1 First MOOC: a resource library

The MOOC Guidance education is presented on the Team 1 website with three different spaces that have been identified in Fig.  5 with 3 colored areas. The training is always available to learners and all year round. On the right, in blue, can be found the table of contents that can be navigated by clicking on the links. At the top, in orange, a frieze allowing the user to locate himself in the course, using grey tiles (Figs.  5 and 6 ).

Choice of the division of the MOOC into sessions by the teaching team

And finally, in green, the course itself offering an activity or several resources, depending on the navigation in the table of contents or in the timeline.

The pedagogical team considered there was not a single two-hour session, but the division of a sequence into several sessions. For this reason, Fig.  6 depicts 7 sessions leading to the issuance of a certificate, with the first session, S0, corresponding to the training presentation.

MOOC 1 has been fully modeled into four distinct and chronological parts, respectively illustrated in Figs.  7 , 8 , 9 and 10 , to facilitate its interpretation as a single, cohesive entity. The same approach will be adopted for describing the other two MOOCs.

Sequence and sessions 0 and 1 of the “Guidance education” MOOC

Sessions 2 and 3 of the “Guidance education” MOOC

Sessions 4 and 5 of the “Guidance education” MOOC

Session 6 of the “Guidance education” MOOC

In the modeling in Fig.  7 , the sequence banner indicates the sequence number, the MOOC title, a 2-hour training duration, a division into 6 sessions as well as cognitive, motor and emotional objectives (BBA) (Appendix 1, Table  6 , ID 6) on the sequence, which were determined a posteriori by the pedagogical team. Objectives were also assigned to the different activities during modelling, using the tool to show their educational autonomy. The learning activities panel shows 8 items, 4 of which are active and 4 passive. With the help of a video and text, session 0 (before the start of the MOOC) sets objectives with a presentation of the training. It makes 4 links using the “Recall – Call” pieces (Appendix 1 – Table  8 , ID 1 and 2) to a Facebook community, the sites TrouveTaVoie and Inspire , plus an explanation of how to obtain the certification. This last piece makes a link with code Sq 1 S X U X, to indicate the certificate is obtained for the entire training, i.e., Sq 1, since the S session and the U unit are not filled in. It should be noted that the concept of brick, granularization and microlearning are easily applied to this MOOC, since each activity resulting from a broader content is short and identifiable with a specific autonomous content and that, therefore, it is possible to associate a code, as well as a duration, to identify them.

For the rest of the modeling (Figs.  8 , 9 and 10 ), we have chosen to dissociate the sessions, using letters a and b to differentiate the courses and the files (resources) made available. Sometimes, activities do not have a duration since they are symbolic, such as SQ1 S0 U2 and SQ1 S0 U5 (Fig.  7 ) to make the link with social networks and the final certificate, respectively. In Session 1a, we can see links between Session 0 and Session 1b (resources).

Sessions 1a to 5a (Figs.  7 , 8 and 9 ) have the same pattern with, firstly, two passive activities consisting of videos and texts and, secondly, a passive activity with a podcast and text. Each of the passive activities links to dedicated resources.

Only session 6 (Fig.  10 ) is different in the way activities are organized, by proposing a synthesis along with new resources.

The code dictionary (Table  3 (Appendix 2 – Table  9 )) enables you to visualize the presence of 50 main pieces and visualize the sequence and sessions durations. It should also be noted the activities proposed in the training contain only resources and that they do not integrate any collaborative activities into the scripting. We can also see that reading and viewing the content of the Learning Units takes learners a minimum of 2 h and 5 min, if they follow the entire sequence. Remember the training time indicated in the banner in Fig.  5 was 2 h.

For these various reasons, it turns out this initial MOOC does not directly promote the active engagement of a learner in a real learning experience. Therefore, we felt it was more appropriate to classify it more as a resource library than as a course per se.

5.2 MOOC: a transmissive pedagogy

The MOOC platform interface for teams 2 and 3is always divided into three main areas, as shown in the image below: horizontal menu (1), course tree (2), navigation bar (3).

Figure  11 shows there are several navigation zones. In the red box (1) there are several tabs that are also configurable by the teaching team and therefore different depending on MOOCs. Access to the course, the forum (discussion tab) and the student’s progress (grades obtained in the course) is done at this level.

Screenshot of a MOOC with a dedicated page for discovering the platform

Two other areas we bring up with green (2) and yellow (3) boxes are specifically dedicated to the course. The left-hand side (2) enables you to visualize the teaching tree in the form of a breakdown of the disciplinary content that is presented either by week or by modules or sequences, according to the terminology used by the teaching teams.

It can be observed that Team 1’s previous platform (Fig.  5 ) is generally simpler and more linear in its organization with fewer tabs compared to Fig.  11 . This organization has implications for the modeling of courses as it allows designers to more easily reveal connections between various elements such as forums and informational emails. This approach will be utilized in the third MOOC to highlight advanced community management strategies.

The MOOC “Everything you need to know about itching” which is offered in the “Health” category was available on internet from 5 December, 2022 to 17 April, 2023. On the course presentation page, it was announced it would be broadcast for 6 weeks, that it would require a 12-hour effort and a work rhythm of about 2 h per week. This information is listed on the sequence banner with the sequence number, the MOOC title and sequence objectives a priori determined by the team (Fig.  12 ). It is also noticeable that the objectives of the sessions and Learning Units are identified, even though they were a posteriori defined by the team during analysis with the tool.

Week 1 of the “Everything you need to know about itching” MOOC

The first week of training begins with access to a module entitled “ To get started before taking this MOOC ” which we have coded as “Session 1a” to differentiate it from “Session 1b” exclusive to the course (Fig.  12 ). Session 1a includes the start of the training email with a regulation strategy (yellow piece (Appendix 1 – Table 8, ID 5)), a number of explanations necessary for using the environment and its operation (orange piece (Appendix 1 – Table  7 , ID 4) as well as an optional questionnaire to identify learners’ profile (green piece (Appendix 1 – Table  7 , ID 3)).

Compared to the other weeks (Figs.  13 , 14 and 15 ), it should be noted that session 1b (Fig.  12 ) has the particularity of not offering a summative evaluation. Weeks 2 to 6 (Figs.  13 , 14 and 15 ) are then all organized in the same way with an email at the beginning of the session, session objectives (blue piece (Appendix 1 – Table  7 , ID 2)), course videos with text (between 2 and 4 videos), an automated quiz-type assessment and then an optional forum, considered as a collaborative activity. The 7th session is not to be considered as an additional training week. It is dedicated to taking an evaluation questionnaire and how to obtain an open badge. It should be noted that learners are encouraged to complete the questionnaire, hence the motivation piece (Appendix 1 – Table  8 , ID 6) that is attached to the green piece relating to the assessment.

Weeks 2 and 3 of the “Everything you need to know about itching” MOOC

Weeks 4 and 5 of the “Everything you need to know about itching” MOOC

Weeks 6 and 7 of the “Everything you need to know about itching” MOOC

The code dictionary (Table  4 and Appendix 2 – Table  10 ) includes 50 different activities, including assessments, for a total of 4 h and 28 min of writing time. This duration is 2.7 times smaller than the 12 h of learning time planned by the teaching team, i.e., a ratio of almost 1 to 3 of the estimated learning time. The activities panel shows 6 activities, 4 of which are active and 2 passive.

Although evaluations are scheduled at the end of the MOOC, the activities offered are mainly video resources (activity number 2) to be watched without any real strategy to guide the learner towards an active attitude. That is why this course has been categorized as a MOOC of a transmissive nature.

5.3 Third MOOC: from transmissive pedagogy to a more active pedagogy (community management)

The MOOC “Adolescent development” offered in the “psychology” and “sociology” categories was accessible for the last session from 2 October 2018 to 4 December 2018 (Figs.  16 , 17 , 18 , 19 and 20 ). The course presentation page quoted an 8-week training time, an effort of around 16 h if putting in about 2 h per week.

Week 1 of the “Adolescent development” MOOC

Weeks 2 and 3 of the “Adolescent development” MOOC

Week 4 of the “Adolescent development” MOOC

Week 5 of the “ Adolescent development ” MOOC

Weeks 6 and 7 of the “Adolescent development” MOOC

The first training week was divided into sessions 1a and 1b to facilitate the separation of the courses from particular real or symbolic resources (Fig.  16 ). Namely, the MOOC presentation page; the email at the beginning of the MOOC; how the certification and the platform work; the presence of a forum; a Padlet and then specific actions such as “Let’s get acquainted”, “Motiv’ Tuesdays” which summarize what is covered, the “Monday recap”, which is a reminder of what has been covered and finally the optional questionnaire at the beginning of the MOOC. Weeks 1b, 3, 4, 5 (Figs.  16 , 17 , 18 and 19 ) are made up of instructional videos, comic strips and, at the end of the week, testimonies from teenagers, with text. Weeks 2 and 6 (Figs.  17 and 20 ) are organized in the same way, but without the comic strips. All activities with videos link to the forum and all course videos are followed by formative assessments to ensure learners have understood. These evaluations are also summative since they are geared towards obtaining the training certificate (Fig.  20 ). Each week, learners are sent two emails, except for the 6th and 7th week (Fig.  20 ), when they get sent only one. In week 3 (Fig.  17 ), a symbolic and non-lasting social media activity (Sq1 S3 U3) is offered, which is linked to the activities that follow. Each week, a “Transcripts” activity is offered in isolation before the “Teenagers’ words” activity. The last week (Sq1S7, Fig.  20 ) is atypical compared to the others. It is dedicated to the conclusion of the training. Again, an email is sent; how to obtain the certificate under conditions; the end of the MOOC questionnaire as well as a link to an optional conference.

The MOOC offers 76 different activities with a total duration of 5 h and 52 min (Table  5 and Appendix 2 – Table  11 ).

It is worth noting that, to calculate the duration of activities incorporating a video followed by a formative evaluation, the team arbitrarily decided to add 2 min to videos durations, to take into account evaluation time. Nevertheless, we can see the entire course is still about a ratio of 1 to 3 compared to the 16-hour learning time, planned by the teaching team. The activities panel shows 12 activities, 4 of which are active and 8 passive.

To compensate for such massive use of resources (videos and a few comic strips), designers tried to make learners active and encourage their engagement, with the help of formative assessments, a forum, a Padlet and numerous email reminders. This is why, unlike MOOC number 2, we prefer to classify this MOOC not as a MOOC with a purely transmissive pedagogy, but rather as a hybrid, integrating elements of both transmissive pedagogy and active pedagogy.

After studying the design of the 3 MOOCs produced by all 3 teams, we will present the main results of the qualitative study aimed at evaluating the utility and usability of the pedagogical scripting kit.

5.4 Synthesis of the kit usefulness and usability assessment

First, during the MOOCs training and modeling by all three teams, we observed a difference in professional experience. Team 1 was generally older and more experienced in instructional design compared to Teams 2 and 3, which were made up of younger practitioners. Consequently, expectations from the kit were different. Team 1 had a greater desire to evaluate their MOOC’s quality, while Teams 2 and 3 seemed more focused on using the kit to evaluate themselves through the quality of their work. Thus, perceived usefulness (Q4, Table 4) was very different. For Q5, regarding the nature and order of the proposed tasks, the teams agreed on a way to proceed since the kit itself does not impose a specific scripting strategy.

Regarding the comparison with existing tools, almost all members of the three teams were at least familiar with the ABC Learning Design kit, while the Learning Battle Cards kit was less well-known. Those trained in ABC Learning Design, especially in Team 1, had never tried to model an existing course with the tool and therefore could not compare its uses. Regarding Q6, and the relevance of the timing for using the tool, all teams managed to model almost the entirety of their MOOC in 3 h. Only Team 1, whose members debated a lot about ideas for improvements as they went along, had not completely finished modeling the last session, even though, retrospectively, it was the smallest MOOC to model.

Regarding usability, the tool appeared particularly suitable (Q10) for this audience, almost exclusively composed of instructional designers. In our study, the use of the different parts of the kit was carried out without real difficulty, and it was not often necessary to intervene to remind them of the training on the tool during modeling (Q13). As with Q5, question 11 – concerning tool flexibility and need to be adapted or modified by users – was heavily influenced by group discussions. For example, some team members took the initiative to create and share mind maps with the group to organize their ideas. Some wanted to arrange the tables in the room differently to better visualize and discuss the kit’s modeling. A member of Team 1 used extra sheets of paper to write down learning units contents. Indeed, in version 1.7, it was not yet possible, unlike in the current version (2.4), to directly write information on the main pieces.

Nevertheless, despite a generally positive assessment, several difficulties arose with questions 12 and 14, which concern understanding the kit’s functioning and the workload to use it, respectively. For many team members, the initial moments of discovering the kit were met with high apprehension. Indeed, the number of kit parts and the fact that the modeling takes the form of a code that initially had no meaning for them was a real cause for concern. Some Teams 2 and 3 members said their first impression was that the tool was too abstract and not user-friendly. According to them, this feeling was amplified by the kit’s appearance, which resembles a board game, though it is not one. It was only at the end of the training, after assimilating the new language, that this negative feeling largely dissipated. However, in Team 3, some wished to see the kit evolve towards a more playful approach, while in Team 2, some wanted concrete examples of activities to help them find new ideas.

Regarding the workload to use the tool (Q14), it is important to note that training is mandatory to use the kit, which in our context was not an issue since it was part of the evaluation process. However, some Teams 2 and 3 members expressed concerns about the kit’s use by other professional categories. They found some aspects of the kit too complex, particularly the use of multiple taxonomies (cognitive, motor, emotional), as well as the time required for modeling. They felt it would not be compatible with the busy schedule of a secondary school teacher, who must prepare numerous lessons, as it would require too much training and preparation time. Conversely, they noted that such a tool would be indispensable in complex training contexts such as MOOCs, to create and analyze their future productions.

Finally, at the end of the various modeling sessions, during the kit’s storage phase, all three groups complained about not being able to save their work digitally. They pointed out that having to erase, store, and then potentially reproduce the same modeling was time-consuming and a waste of time, besides. They also mentioned the need for enough space in their office to leave the modeling in place if they had neither time nor wish to store it. Conversely, some members saw that as an extra advantage, as it allowed them to keep the training in view to discuss it with colleagues or return to it more easily and regularly. Others directly came up with the idea of photographing their work to save it and then exchange it with colleagues in digital form.

After detailing the main results of this research and development, the next chapter will be devoted to discussing the advantages and limitations of the scripting kit and its methodology.

6 Discussion

In this article, we have highlighted that some designers prefer using simple Post-it notes for collaboratively designing their courses, despite the availability of digital and analog tools that could assist them in so doing. By analyzing existing analog tools, we found they do not allow their users to engage in an inductive logic approach. To address this gap, we undertook research and development to create a new analogic tool aimed at facilitating an inductive approach, encouraging collaboration, and optimizing the instructional design process. Several prototypes of pedagogical scripting kits were developed, along with a new scripting methodology centered on the concept of bricks. We then studied the kit usefulness, usability and methodology through a qualitative study involving three teams modeling their MOOCs.

In this chapter, we will leverage the modeling of the 3 MOOCs by different teams to discuss the intrinsic value and limitations of using the scripting kit to describe such courses. From a methodological perspective, we will then discuss the results of the empirical study on the kit usefulness, usability and methodology by teams. Finally, we will see that it was possible to extract several regularities from this modeling, allowing us to tentatively envision a new Learning Design theory centered on the concept of bricks.

6.1 Advantages of and limitations to the use of the scriptwriting kit when describing the 3 MOOCs

In this research, three MOOCs were modelled in their entirety by the design teams, using Eduscript Doctor (prototype v. 2.4). This tool’s modelling principle is to represent all the theoretical learning paths composed of various activities and that can also be in asynchronous training, such as optional or compulsory MOOCs, be they linear or not. In the MOOCs studied, learners can choose: either move from one activity to another as they wish, although a specific path is provided for them. The journey is therefore not an exact reflection of learners’ navigations and therefore of their actual learning experiences. Their experiences can vary, depending on their needs, learning pace, interests, and interactions with content. This difference between modeling a virtual learning path and the actual learner’s experience may be seen by some as a limitation of this type of modeling tool. However, we should not confuse modelling multiple paths with navigation once again. Sometimes, different paths are planned by designers, whether they are alternative, own choice, progressive, complementary, or even optional. In this case, it would have been necessary to represent them in their entirety with the kit, using new aggregates in the modeling. In the 3 MOOCs studied, a single pathway is offered to all learners. However, other choices could have been made by teams such as hybrid pathways, remedial pathways after a diagnostic assessment, differentiated pathways with micro-credentials, etc.

In order to model training courses with the kit, we adopted an approach that breaks down the content into sequences, sessions and Learning Units, using a granularization method. This terminology is commonly used to structure courses in the French education system, which vindicates its extensive use. However, as demonstrated by the examination of the three MOOCs studied, these terms do not always correspond to the terminology commonly used by training designers. Thus, it is relevant to perceive this division into Sequences, Sessions, and Units rather as a practical strategy to artificially segment content. Segmentation is essential for encoding and describing the various contents and relationships between different activities but is not truth in itself.

Regarding the formulation of training objectives, we have, in the kit, identified a description to the effect that they can be set at three levels (Chap. 3.2). First, we have an overall definition of the objectives for the entire sequence, which in this article represents MOOCs in their entirety. Then, we defined session objectives, which mark the first step of dividing the content into aggregates. Finally, we set pedagogical objectives for each Learning Unit. In the latter case, assigning learning objectives to short Learning Units helps steer the design towards optimized microlearning, also known as Nuggets Learning, providing a short, focused, and effective educational experience (Burguete & Urrego, 2023 ). Although this requires an investment in time at design stage, it may be a good idea to set learning objectives in advance for at least two of the initial levels. This improves accuracy, allows for better planning of progress, and most importantly, informs learners of their goals, which tends to increase their engagement. In the case of these three MOOCs, the objectives of the two lowest levels (sessions and Learning Units) were sometimes a posteriori defined, using the tool during modeling by the design teams. Although artificial, this approach is nevertheless useful in the reflexive analysis to highlight designers’ educational strategy during the course design phase, even though learners have not been informed of it.

Modelling the 3 MOOCs makes it possible to know the nature of the activities offered in the courses, whether active or passive. Because of the codes that identify each of the activities, we can see the missing or existing links between the course different parts. For example, we realize the content is always new in all 3 MOOCs and that there are no activities outside the summative assessments that invite learners to carry out retrieval efforts. From the Call or Recall pieces (Appendix 1 – Table  8 , ID 1 and 2), we can also see there are resources that are little or not at all exploited in training, such as those related to the transcriptions highlighted in MOOC 3 (Sq1S3U10, Fig.  17 ) or the forum in MOOC 2 (Sq1S1aU4, Fig.  16 ). Regarding the content offered, we can see training course modeling is not limited to identifying only directly educational content, but also integrates links with other resources such as emails (Sq1S1aU2, Fig.  16 ), certificates or open badges (Sq1S7U3, Fig.  20 ), a Padlet (Sq1S1aU9, Fig.  16 ), social networks (Sq1S3U3, Fig.  17 ) or any other object, whether real or symbolic. All this information makes it possible to visualize community management strategies and identify or plan precisely which parts will be evaluated or highlighted (emails, teasers, social networks, remediation, etc.). To do this, as in MOOCs 2 and 3, it is relevant in the same session to separate the elements that correspond to the course from those that fit into it into aggregates. This is why sessions a and b have been artificially created to bring better visibility to the different joints. Thus, while the course activities appear isolated in the modeling, frequency (numbers) analysis, activities nature (red or green color coded) and their regularity (pattern) becomes easy to carry out. If red is in the majority, we can deduce that the course is more resource-oriented. Conversely, if green is the majority, we will conclude the course is more activity-oriented. Likewise, with the help of numbers, we will be able to visualize the varied or monotonous nature of the content offered. However, in the context of a course focused on (red) resources such as instructional videos, for example, it will always be possible to offer learners a strategy to turn them up into spectators (seated surfers) or into actors (surfers standing in a wave) and therefore act on their behaviors to foster engagement. Because of the main pieces color coding, we can see, for example, that there is no summative assessment in session 1b of MOOC 2 (Fig.  12 ), whereas there is systematically one in all the other sessions. Learners might conclude this training week should be considered as less important than the others. In addition, regarding the nature of the activities and their positioning within the course, it should be noted that in MOOC 3, comic strips aimed at arousing learners’ emotions and questions are placed at the end of each session, after the course main content. Modelling raises the relevant issue of whether it is possible to move these comic strips up to the sessions beginning, to allow learners to better benefit from the teaching that will follow. That way, learners would have the opportunity to find answers to the questions raised by the comic strips and could also discuss them afterwards with their forum peers.

Regarding the overview of learning activities (Appendix 1 – Table  6 , ID 3), which is used to identify the various passive and active activities, please note it is not the number of activities that is proof of diversity in a training course, but rather the frequency of use of these very activities. Indeed, though we can see there are many different activities in all 3 MOOCs, the educational video is the most commonly used. It is therefore essential to properly analyze the modeling with the color codes and numbers of the different activities as well as the time or pace the different activities pop up at.

Although it does not have to be completed, the code dictionary (Appendix 2 – Tables  9 , 10 and 11 ) has the added benefit of making it possible to check whether some activities are too long and whether their completion time is compatible with learners’ learning time. In MOOC 1, we see the activities total duration corresponds to the training duration announced by the design team, which justifies considering the MOOC more as a resource library than as a course per se. On the contrary, the duration of MOOCs 2 and 3 courses is multiplied by three by teams to integrate the learning time. This ratio of 1 to 3 is often used empirically by designers to calculate an online course duration.

Now that we have detailed and discussed the results of the different sorts of modeling, we can move on to discussing the usefulness and usability of the scripting kit as perceived by teams.

6.2 Kit usefulness, usability and methodology assessments

The results of this qualitative evaluation are generally positive in terms of both usefulness and usability. However, these results should be considered cautiously due to a major selection bias among the study participants. Most participants were instructional designers, likely more willing, motivated, and interested in the pedagogical scripting tool than other professionals randomly selected from other universities or training centers. It is important to note that the kit is also intended to be used individually or in teams by trainers who are not specialists in instructional design or by students in training in this field. Therefore, further studies will be necessary to assess its use in more varied contexts.

Moreover, due to an insufficient budget, particularly for manufacturing and providing an adequate number of kits for an extended period, our study is hampered by its small number of participating teams and the inability to conduct long-term follow-up. This limitation prevented a thorough evaluation of the kit’s usefulness and usability, as the assessment was conducted at a specific moment in time.

Regarding criticisms about the kit apparent complexity, we believe this is primarily related to its inductive nature, which is inherently less informative. As a result, in the training that precedes the use of the tool, we chose to first explain the granularization and microlearning concepts before introducing the tool. Future studies will need to confirm that this strategy effectively alleviates initial apprehensions about the tool.

Finally, regarding the storage of the kit after use, significant efforts have been made with version 2.4 to facilitate the storage of the pieces in the box. However, it still takes some time to erase the writings and store the pieces. We believe that an alternative digital version of the tool on a computer might not be a good idea however, as it would remove the tangible and possibly collaborative aspects that are the tool’s strengths, similar to the practice of using Post-its. Nevertheless, a digital version that complements rather than replaces the tool could capture the scripts and, in some cases, allow them to be further developed on a computer or whiteboard. This would eliminate the need to photograph scripts to save them.

As a conclusion to these last two parts concerning the 3 MOOCs modeling and discussing the results of the qualitative study as to the kit usefulness and usability, we can validate at least the first of our two main hypotheses. Indeed, the kit has proved to be useful as it “allows a clear visualization of the structure of a MOOC, thereby facilitating the evaluation of its pedagogical design”. However, although the kit was widely usable by the educational teams, our qualitative data do not allow us to assert that the kit is suitable for an audience of instructional designers due to the selection bias associated with team recruitment and the absence of quantitative data. Thus, further studies will need to confirm this last hypothesis.

Now that we have discussed the results of all sorts of modeling and teams’ feedback on the kit usefulness and usability, the next sub-chapter will highlight the need to develop an abstraction of the brick-centered scripting methodology in the form of a Learning Design theory.

6.3 Regularities and possible abstraction of results towards creating a learning design theory centered on the concept of bricks

Improving the kit methodology during R&D and using it during this experimental study, let us highlight several design regularities around the brick concept. We were able to define 8 general principles that enabled us to raise the possibility of going beyond the threshold of a simple methodology towards the more abstract one of a Learning Design theory centered on the concept of bricks. In our next investigations on the kit, we plan to continue our reflection on this theory, since we recognize it still warrants many tests and adjustments, indeed. By doing this, we will be able to further perfect the scriptwriting methodology used in Eduscript Doctor, and even develop new tools. Here are the premises of a new theory presented in the form of 8 major temporary principles that allow for an abstraction of the scriptwriting methodology based on the concept of bricks.

1st principle: the brick as a training unit

All teaching and learning devices and, more broadly, all formal, non-formal or informal educational experiences can be represented in the form of one or more isolated building block(s) or in the form of aggregates.

2nd principle: the brick as a container with its contents

As a container, one or more brick(s) can act as the support of all existing pedagogical models, in an exclusive way or by associating them. The container can be “filled” with educational content, but it can also be empty – without educational content.

Content can be predetermined by the designer and team, developed by the learner autonomously or collaboratively, co-designed by all stakeholders, or imposed on learners in an unprogrammed educational situation. To this end, the content of the brick can be at least a resource or activity in which the learner(s) will behave either actively (as spectators or actors), or passively, if they feel no need or desire to learn.

3rd principle: The brick can be self-contained

When a brick is an autonomous educational object, it is self-sufficient. In this context, it must proactively or retroactively provide at least one targeted pedagogical objective. It may or may not be linked to other bricks.

4th principle: The brick is identified to become unique

Each brick (self-contained or not) will need to be identified with a code, so it can be described. On the one hand, this will make it possible to identify this brick in space and time during a script, but also to be able to reuse it as a Teaching and Learning Resource (TLR) or as an Open Educational Resource (OER).

5th principle: Bricks can be connected to other bricks

When several bricks appear in isolated forms or, on the contrary, in the form of one or more aggregates, the identification of each of the bricks with a code makes it possible to make links between them as a “call” from one brick to another or as a “recall” of a previous brick. A code can also be used to identify bricks aggregates, to make connections between an aggregate and a brick or between a brick and an aggregate.

6th Principle: A real or symbolic brick

A brick can represent a partial or complete teaching and learning situation as well as any concrete or symbolic object such as a tool, an instrument, a strategy or a concept, a theory. In this second case, the brick will necessarily be represented in isolation, but it will necessarily be related to another brick.

7th Principle: Brick duration

Not all bricks have a duration, as they can contain concrete or symbolic objects that will be integrated with a link into another brick. However, all other bricks that are activities or resources will have durations that can be defined either from an average activity or consultation time, or from an estimated presence time or, then again, an estimated learning time. Depending on the learning situation, a brick may have various durations, either minimum, or maximum, or fixed or variable.

8th Principle: Designing the content of a brick

The use of the brick concept does not necessarily imply dividing disciplinary content or defining pedagogical objectives. The design can be carried out by at least one teacher or trainer (top-down approach) or by at least one learner (bottom-up approach). In addition, a brick can represent either massed or distributed learning, depending on bricks durations and numbers.

7 Conclusion

This study has explored a new methodological approach of pedagogical scripting by highlighting the use of a pedagogical scripting kit, called Eduscript Doctor, to support it. Through the process of creation and analysis of this new methodology, we examined the benefits and challenges as to applying it, especially in the context of the 3 MOOCs studied. The empirical evaluation of the kit revealed that it was generally useful and usable by design teams in the context of MOOCs, offering tangibility, practicality, flexibility, and reflexivity in the design process.

Although further studies in different contexts and possible audiences are necessary to confirm the possible uses of the pedagogical scripting kit, the initial results of this research lead us to believe that Eduscript Doctor is a promising solution. It proves to be both concrete and pragmatic in terms of the design and analysis of educational scripting, valuable for both practitioners and researchers in the field of education and training sciences.

The methodology proposed in this article focuses on the notion of “brick”. It also presents an interesting perspective for the design and planning of any type of teaching and learning method and material outside the pedagogical scenario kit. It has the advantage of freeing itself from the constraints of duration and size associated with the concept of microlearning, while preserving the essential characteristics of its architecture. The Eduscript Doctor kit, although in analogic form, proved invaluable to the design teams of the three MOOCs presented, providing essential tangibility, practicality, flexibility and reflexivity in the design process.

A number of regularities have emerged from this empirical study, which suggests the possibility of producing a new theory of Learning Design that would allow, once fully validated, to improve the power of the tool even more thoroughly.

Data availability

All the data used in the study are already available in full in the article.

Code availability

Nothing to specify.

To avoid burdening the article with a detailed kit description, this paragraph briefly presents the fundamentals of the tool to help understand how it works. However, for a more in-depth exploration of the actual pieces used later in the experimental section, links to Appendix 1 have been incorporated, describing each of these parts.

Alias, N. F., & Razak, R. A. (2024). Revolutionizing learning in the digital age: A systematic literature review of microlearning strategies. Interactive Learning Environments , 0 (0), 1–21. https://doi.org/10.1080/10494820.2024.2331638

Article   Google Scholar  

Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives . Longman.

Google Scholar  

Béguin, P., & Cerf, M. (2004). Formes et enjeux de l’analyse de l’activité pour la conception des systèmes de travail. Activites , 1 (1), 54–71. https://doi.org/10.4000/activites.1156

Berthiaume, D., & Daele, A. (2013). Comment clarifier les apprentissages visés par un enseignement ? In D. Berthiaume, & N. R. Colet (Eds.), La pédagogie De L’enseignement supérieur: Repères théoriques et applications pratiques (pp. 55–71). Peter Lang.

Chapter   Google Scholar  

Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education , 32 (3), 347–364. https://doi.org/10.1007/BF00138871

Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of Educational Goals . Longmans). David McKay.

Bote-Lorenzo, M. L., & Gómez-Sánchez, E. (2017). Predicting the decrease of engagement indicators in a MOOC. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference (pp. 143–147). https://doi.org/10.1145/3027385.3027387

Buchem, I., & Hamelmann, H. (2010). Microlearning: A strategy for ongoing professional development. eLearning Papers, 21 (7), 1–15.

Burguete, E., & Urrego, V. (2023). Contextes et stratégies de médiatisation des MOOC de France Université Numérique: Influences sur la conception et la scénarisation pédagogique. Review of Science Mathematics and ICT Education , 17 (2), 89–109. https://doi.org/10.26220/rev.4527

Celik, B., & Cagiltay, K. (2023). The undervalued variable in massive Open Online Course (MOOC) research: An analysis and conceptualization of readiness for online learning in MOOCs. Education and Information Technologies , 28 (9), 11569–11588. https://doi.org/10.1007/s10639-023-11662-3

Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning . Wiley. Fourth edition.

Book   Google Scholar  

De Gagne, J. C., Park, H. K., Hall, K., Woodward, A., Yamane, S., & Kim, S. S. (2019). Microlearning in health professions education: Scoping review. JMIR Medical Education , 5 (2), e13997. https://doi.org/10.2196/13997

Depover, C., Karsenti, T., & Komis, V. (2017). Pour comprendre les MOOCs: Nature, enjeux et perspectives . Presses de l’Université du Québec.

Ebbinghaus, H. (1885). Über das gedächtnis: Untersuchungen Zur Experimentellen psychologie . Duncker & Humblot.

Eibl, T. (2007). What size is micro? Using a didactical approach based on learning objectives to define granularity. In T. Hug (Ed.), Didactics of microlearning: Concepts, discourses, and examples (1st ed., pp. 125–138). Waxmann.

Fidan, M. (2023). The effects of microlearning-supported flipped classroom on pre-service teachers’ learning performance, motivation and engagement. Education and Information Technologies , 28 (1), 12687–12714. https://doi.org/10.1007/s10639-023-11639-2

Goigoux, R. (2017). Associer Chercheurs Et praticiens à la conception d’outils didactiques ou de dispositifs innovants pour améliorer l’enseignement. Éducation et Didactique , 11 (3), 135–142. https://doi.org/10.4000/educationdidactique.2872

Hug, T. (2007). Didactics of microlearning: Concepts, discourses and examples . Waxmann.

Hug, T. (2022). Microlearning formats in Crisis? Theses in the field of Tension between Corona-Induced Short-Term solutions, Apodictic Rhetoric’s of no Alternatives and Perspectives Open to the future. Microlearning: New approaches to a more effective higher (pp. 125–140). Springer.

Kapp, K., & DeFelice, R. (2019). Microlearning: Short and sweet . ATD.

Kelley, P., & Whatson, T. (2013). Making long-term memories in minutes: A spaced learning pattern from memory research in education. Frontiers in Human Neuroscience , 7 , 589. https://doi.org/10.3389/fnhum.2013.00589

Kohnke, L., Foung, D., & Zou, D. (2023). Microlearning: A new normal for flexible teacher professional development in online and blended learning. Education and Information Technologies . https://doi.org/10.1007/s10639-023-11964-6

Komis, V., Tzavara, A., Karsenti, T., Collin, S., & Simard, S. (2013). Educational scenarios with ICT: An operational design and implementation framework. In R. McBride & M. Searson (Eds.), Proceedings of SITE 2013 Society for Information Technology & Teacher Education (pp. 3244–3251). Association for the Advancement of Computing in Education (AACE).

Lee, Y. M. (2023). Mobile microlearning: A systematic literature review and its implications. Interactive Learning Environments , 31 (7), 4636–4651. https://doi.org/10.1080/10494820.2021.1977964

Leong, K., Sung, A., Au, D., & Blanchard, C. (2021). A review of the trend of microlearning. Journal of Work-Applied Management , 13 (1), 88–102. https://doi.org/10.1108/jwam-10-2020-0044

Lieury, A. (2015). Psychologie cognitive . Dunod.

Littlejohn, A., & Shum, S. B. (2003). Reusing online resources: A sustainable approach to elearning. Journal of Interactive Media in Education , 2003 (1), 1. https://doi.org/10.5334/2003-1-reuse-01

Margaryan, A., Bianco, M., & Littlejohn, A. (2015). Instructional quality of massive Open Online courses (MOOCs). Computers & Education , 80 , 77–83. https://doi.org/10.1016/j.compedu.2014.08.005

McBride, D. M., & Cutting, J. C. (2019). Cognitive psychology: Theory, process, and methodology . SAGE.

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review , 63 (2), 81–97. https://doi.org/10.1037/h0043158

Ordu, U. B. A. (2021). The role of teaching and learning aids/methods in a changing world . Bulgarian Comparative Education Society.

Perović, N., & Young, C. P. L. (2020). ABC LD – a new toolkit for rapid learning design. EDEN Conference Proceedings , 1 , 426–437. https://doi.org/10.38069/edenconf-2020-ac0041

Rabardel, P. (1995). Les Hommes et les technologies; Approche cognitive des instruments contemporains . Armand Colin.

Renaud, J. (2020). Evaluate the usability, usefulness and acceptability of a didactic tool during the continuous design process in use. Case of a tool for teaching the reading of digital documentary texts. Éducation et Didactique , (14–2), 65–84. https://doi.org/10.4000/educationdidactique.6756

Rivera, Y. T. (2022). Diseño de microlearning: guía para crear cursos en línea y contenidos educativos mediante la técnica de microaprendizaje . Independently published.

Sun, Y., Ni, L., Zhao, Y., Shen, X., & Wang, N. (2019). Understanding students’ engagement in MOOCs: An integration of self-determination theory and theory of relationship quality. British Journal of Educational Technology , 50 (6), 3156–3174. https://doi.org/10.1111/bjet.12724

Sweller, J. (1988). Cognitive load during problem solving: Effects on Learning. Cognitive Science , 12 (2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

Taylor, A., & Hung, W. (2022). The effects of Microlearning: A scoping review. Educational Technology Research and Development , 70 (2), 363–395. https://doi.org/10.1007/s11423-022-10084-1

Tcheng Blairon, C., & Cristol, D. (2020). MOOC, engagement et apprentissage: L’ingénierie pédagogique Au service de L’apprenance . l’Harmattan.

Toppino, T. C., Kasserman, J. E., & Mracek, W. A. (1991). The effect of spacing repetitions on the recognition memory of young children and adults. Journal of Experimental Child Psychology , 51 (1), 123–138. https://doi.org/10.1016/0022-0965(91)90079-8

Torgerson, C. (2021). What is microlearning? Origin, definitions, and applications. In J. R. Corbeil, B. H. Khan, & M. E. Corbeil (Eds.), Microlearning in the digital age: The design and delivery of learning in snippets (pp. 14–31). Routledge.

Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development , 53 (4), 5–23. https://doi.org/10.1007/bf02504682

Yang, M., Lowell, V., Long, Y., & Farmer, T. (2023). Designing for accessibility in online learning: A design case. Journal of Postsecondary Education and Disability , 36 (1), 75–87.

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All authors contributed to the study conception and design. The first draft of the manuscript was written by Emmanuel Burguete and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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All three of this study authors disclose a potential competing interest in relation to the research subject matter. All are recognized as the inventors of the Eduscript Doctor kit, a central focus of this research. Their involvement in this tool development and conceptualization may present a conflict of interest, given their direct connection to the product being studied and evaluated. Please note that, while the authors hold a vested interest in the Eduscript Doctor kit, all efforts have been made to conduct the research with the highest standards of academic integrity and objectivity. However, readers and reviewers should consider this competing interest when evaluating the conclusions and recommendations presented in the study. This declaration is made in the spirit of transparency and to uphold ethical research practices principles.

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Appendix 1: description of Eduscript Doctor’s exhibits

Appendix 2: complete code dictionary of the 3 moocs, rights and permissions.

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Burguete, E., Coulibaly, B. & Komis, V. Empirical validation of a brick-centric learning design methodology and its implementation through the Eduscript Doctor pedagogical scenario kit. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-13011-4

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DOI : https://doi.org/10.1007/s10639-024-13011-4

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