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Powerful Tools for Mapping a Research Literature

Professor Courtney Page Tan , Assistant Professor of Human Resilience in the Department of Security and Emergency Services at Embry-Riddle Aeronautical University, has compiled a list of powerful literature mapping tools. You can use these tools to increase the scale and scope of the literature for your projects. Many provide stunning graphical displays of search results (Edward Tufte would approve).

Connected Papers lets you explore connected papers in a visual graph, beginning with a starter paper you select. You can start with a DOI, URL, or paper title. Purposes: (1) Get a visual overview of a new academic field; (2) Make sure you haven’t missed an important paper; (3) Create the bibliography to your thesis; and (4) Discover the most relevant prior and derivative works.

scite_ Smart Citations for Intelligent Research . Smart Citations allow users to see how a scientific paper has been cited by providing the context of the citation and a classification describing whether it provides supporting or disputing evidence for the cited claim. They claim a database of over 23 million full-text articles.

Open Knowledge Maps . Calling themselves a “visual interface to the world’s scientific community,” their tool allows you to start with a few keywords to search for literature on a topic. Results display the main areas at a glance, and papers related to each area. In addition to giving you an overview of the area, it helps you identify important concepts. They highlight open access papers in their search results.

Local Citation Network . You input an article using its DOI or a scanned copy containing DOIs and the program shows you suggested articles for you to follow up.

They explain that “This web app aims to help scientists with their literature review using metadata from Microsoft Academic and Crossref . Academic papers cite one another, thus creating a citation network (= graph) . Each node (= vertex) represents an article and each edge (= link / arrow) represents a reference / citation. Citation graphs are a topic of bibliometrics, for which other great software exists as well .

This web app visualizes subsets of the global citation network that I call “local citation networks,” defined by the references of a given set of input articles. In addition, the most cited references missing in the set of input articles are suggested for further review.”

Citation Gecko Gecko is designed to help you find the most relevant papers to your research and give you a more complete sense of the research landscape. Users start from a small set of ‘seed papers’ that define an area you are interested. Gecko will search the citation network for connected papers allowing you to quickly identify important papers you may have missed.

PRISMA Flow Diagram Generator . This is the most complex of the tools. It generates a graphical representation of the flow of citations reviewed in the course of a Systematic Review. Click here for an example.

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LITERATURE REVIEW SOFTWARE FOR BETTER RESEARCH

“Litmaps is a game changer for finding novel literature... it has been invaluable for my productivity.... I also got my PhD student to use it and they also found it invaluable, finding several gaps they missed”

Varun Venkatesh

Austin Health, Australia

As a full-time researcher, Litmaps has become an indispensable tool in my arsenal. The Seed Maps and Discover features of Litmaps have transformed my literature review process, streamlining the identification of key citations while revealing previously overlooked relevant literature, ensuring no crucial connection goes unnoticed. A true game-changer indeed!

Ritwik Pandey

Doctoral Research Scholar – Sri Sathya Sai Institute of Higher Learning

Using Litmaps for my research papers has significantly improved my workflow. Typically, I start with a single paper related to my topic. Whenever I find an interesting work, I add it to my search. From there, I can quickly cover my entire Related Work section.

David Fischer

Research Associate – University of Applied Sciences Kempten

“It's nice to get a quick overview of related literature. Really easy to use, and it helps getting on top of the often complicated structures of referencing”

Christoph Ludwig

Technische Universität Dresden, Germany

“This has helped me so much in researching the literature. Currently, I am beginning to investigate new fields and this has helped me hugely”

Aran Warren

Canterbury University, NZ

“I can’t live without you anymore! I also recommend you to my students.”

Professor at The Chinese University of Hong Kong

“Seeing my literature list as a network enhances my thinking process!”

Katholieke Universiteit Leuven, Belgium

“Incredibly useful tool to get to know more literature, and to gain insight in existing research”

KU Leuven, Belgium

“As a student just venturing into the world of lit reviews, this is a tool that is outstanding and helping me find deeper results for my work.”

Franklin Jeffers

South Oregon University, USA

“Any researcher could use it! The paper recommendations are great for anyone and everyone”

Swansea University, Wales

“This tool really helped me to create good bibtex references for my research papers”

Ali Mohammed-Djafari

Director of Research at LSS-CNRS, France

“Litmaps is extremely helpful with my research. It helps me organize each one of my projects and see how they relate to each other, as well as to keep up to date on publications done in my field”

Daniel Fuller

Clarkson University, USA

As a person who is an early researcher and identifies as dyslexic, I can say that having research articles laid out in the date vs cite graph format is much more approachable than looking at a standard database interface. I feel that the maps Litmaps offers lower the barrier of entry for researchers by giving them the connections between articles spaced out visually. This helps me orientate where a paper is in the history of a field. Thus, new researchers can look at one of Litmap's "seed maps" and have the same information as hours of digging through a database.

Baylor Fain

Postdoctoral Associate – University of Florida

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How to Master at Literature Mapping: 5 Most Recommended Tools to Use

This article is also available in: Turkish , Spanish, Russian , and Portuguese

After putting in a lot of thought, time, and effort, you’ve finally selected a research topic . As the first step towards conducting a successful and impactful research is completed, what follows it is the gruesome process of literature review . Despite the brainstorming, the struggle of understanding how much literature is enough for your research paper or thesis is very much real. Unlike the old days of flipping through pages for hours in a library, literature has come easy to us due to its availability on the internet through Open Access journals and other publishing platforms. This ubiquity has made it even more difficult to cover only significant data! Nevertheless, an ultimate solution to this problem of conglomerating relevant data is literature mapping .

Table of Contents

What is Literature Mapping?

Literature mapping is one of the key strategies when searching literature for your research. Since writing a literature review requires following a systematic method to identify, evaluate, and interpret the work of other researchers, academics, and practitioners from the same research field, creating a literature map proves beneficial. Mapping ideas, arguments, and concepts in a literature is an imperative part of literature review. Additionally, it is stated as an established method for externalizing knowledge and thinking processes. A map of literature is a “graphical plan”, “diagrammatic representation”, or a “geographical metaphor” of the research topic.

Researchers are often overwhelmed by the large amount of information they encounter and have difficulty identifying and organizing information in the context of their research. It is recommended that experts in their fields develop knowledge structures that are richer not only in terms of knowledge, but also in terms of the links between this knowledge. This knowledge linking process is termed as literature mapping .

How Literature Mapping Helps Researchers?

Literature mapping helps researchers in following ways:

• It provides concrete evidence of a student’s understanding and interpretation of the research field to share with both peers and professors.
• Switching to another modality helps researchers form patterns to see what might otherwise be hidden in the research area.
• Furthermore, it helps in identifying gaps in pertinent research.
• Finally, t lets researchers identify potential original areas of study and parameters of their work.

How to Make a Literature Map?

Literature mapping is not only an organizational tool, but also a reflexive tool. Furthermore, it distinguishes between declarative knowledge shown by identifying key concepts, ideas and methods, and procedural knowledge shown through classifying these key concepts and establishing links or relationships between them. The literature review conceptualizes research structures as a “knowledge production domain” that defines a productive and ongoing constructive element. Thus, the approaches emphasize the identity of different scientific institutions from different fields, which can be mapped theoretically, methodologically, or fundamentally.

The two literature mapping approaches are:

• Mapping with key ideas or descriptors: This is developed from keywords in research topics.
• Author mapping: This is also termed as citation matching that identifies key experts in the field and may include the use of citations to interlink them.

Generally, literature maps can be subdivided by categorization processes based on theories, definitions, or chronology, and cross-reference between the two types of mapping. Furthermore, researchers use mind maps as a deductive process, general concept-specific mapping (results in a right triangle), or an inductive process mapping to specific concepts (results in an inverted triangle).

What are Different Literature Mapping Methods?

The different types of literature mapping and representations are as follows:

1. Feature Mapping:

Argument structures developed from summary registration pages.

2. Topic Tree Mapping:

Summary maps showing the development of the topic in sub-themes up to any number of levels.

3. Content Mapping:

Linear structure of organization of content through hierarchical classification.

4. Taxonomic Mapping:

Classification through standardized taxonomies.

5. Concept Mapping:

Linking concepts and processes allows procedural knowledge from declarative information. With a basic principle of cause and effect and problem solving, concept maps can show the relationship between theory and practice.

6. Rhetorical Mapping:

The use of rhetoric communication to discuss, influence, or persuade is particularly important in social policy and political science and can be considered a linking strategy. A number of rhetorical tools have been identified that can be used to present a case, including ethos, metaphor, trope, and irony.

7. Citation Mapping:

Citation mapping or matching is a research process established to specifically establish links between authors by citing their articles. Traditional manual citation indexes have been replaced by automated databases that allow visual mapping methods (e.g. ISI Web of Science). In conclusion, citation matching in a subject area can be effective in determining the frequency of authors and specific articles.

5 Most Useful Literature Mapping Tools

Technology has made the literature mapping process easier now. However, with numerous options available online, it does get difficult for researchers to select one tool that is efficient. These tools are built behind explicit metadata and citations when coupled with some new machine learning techniques. Here are the most recommended literature mapping tools to choose from:

1. Connected Papers

a. Connected Papers is a simple, yet powerful, one-stop visualization tool that uses a single starter article.

b. It is easy to use tool that quickly identifies similar papers with just one “Seed paper” (a relevant paper).

c. Furthermore, it helps to detect seminal papers as well as review papers.

d. It creates a similarity graph not a citation graph and connecting lines (based on the similarity metric).

e. Does not necessarily show direct citation relationships.

f. The identified papers can then be exported into most reference managers like Zotero, EndNote, Mendeley, etc.

2. Inciteful

a. Inciteful is a customizable tool that can be used with multiple starter articles in an iterative process.

b. Results from multiple seed papers can be imported in a batch with a BibTex file.

c. Inciteful produces the following lists of papers by default:

• Similar papers (uses Adamic/Adar index)
• “Most Important Papers in the Graph” (based on PageRank)
• Recent Papers by the Top 100 Authors
• The Most Important Recent Papers

d. It allows filtration of results by keywords.

e. Importantly, seed papers can also be directly added by title or DOI.

a. Litmaps follows an iterative process and creates visualizations for found papers.

b. It allows importing of papers using BibTex format which can be exported from most reference managers like Zotero, EndNote, Mendeley. In addition, it allows paper imports from an ORCID profile.

c. Keywords search method is used to find Litmaps indexed papers.

d. Additionally, it allows setting up email updates of “emergent literature”.

e. Its unique feature that allows overlay of different maps helps to look for overlaps of papers.

f. Lastly, its explore function allows finding related papers to add to the map.

4. Citation-based Sites

a. CoCites is a citation-based method for researching scientific literature.

b. Citation Gecko is a tool for visualizing links between articles.

c. VOSviewer is a software tool for creating and visualizing bibliometric networks. These networks are for example journals, may include researchers or individual publications, which can be generated based on citation, bibliographic matching , co-citation, or co-authorship relationships. VOSviewer also offers text mining functionality that can be used to create and visualize networks of important terms extracted from a scientific literature.

5. Citation Context Tools

a. Scite allow users to see how a publication has been cited by providing the context of the citation and a classification describing whether it provides supporting or contrasting evidence for the cited claim.

b. Semantic Scholar is a freely available, AI-powered research tool for scientific literature.

Have you ever mapped your literature? Did you use any of these tools before? Lastly, what are the strategies and methods you use for literature mapping ? Let us know how this article helped you in creating a hassle-free and comprehensive literature map.

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• Published: 02 September 2024

Spatial processing

Mapping future locations

• Katherine Whalley 1  

Nature Reviews Neuroscience ( 2024 ) Cite this article

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Medial entorhinal cortex (MEC) grid cells contribute to navigation by encoding information about an animal’s current position and self-motion. Ouchi and Fujisawa now report the discovery of MEC grid cells that predict an animal’s future position.

The authors recorded from rat MEC neurons as the animals participated in a task requiring them to move back and forth along linear trajectories between pairs of reward ports within an open field. They revealed a subset of MEC neurons — which they termed ‘predictive grid cells’ — that exhibited grid fields (firing fields arranged as a hexagonal grid across the environment) that represented their future projected position along the current trajectory. This predictive grid coding was preserved across other behavioural tasks, including random foraging.

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Ouchi, A. & Fujisawa, S. Predictive grid coding in the medial entorhinal cortex. Science 385 , 776–784 (2024)

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• Published: 16 January 2024

Fintech research: systematic mapping, classification, and future directions

• Qianhua Liu 1 ,
• Ka-Ching Chan   ORCID: orcid.org/0000-0002-8756-2991 1 &
• Ranga Chimhundu 1  

Financial Innovation volume  10 , Article number:  24 ( 2024 ) Cite this article

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This systematic mapping study provides a comprehensive review of current Fintech publications, analyzing the current state, maturity level, and future directions of Fintech research. Reviewing 518 Fintech articles across four academic databases from 2008 to 2021, we find a significant increase in Fintech studies, especially in Quartile 1 and Quartile 2 journals. Fintech and banking, Fintech development, and Fintech adoption are the most popular research areas, and articles in these areas are increasing. We propose a classification scheme for Fintech studies across five dimensions. Our study provides a unique perspective on the subject, enabling researchers and practitioners to re-evaluate the direction and scope of future Fintech research.

Introduction

Fintech, which is an abbreviated form of financial technology, is a term that refers to the modern relationships between Internet-related technologies and business activities in the financial services industry (Suryono et al. 2020 ). Fintech has a wide range of meanings. In business, Fintech is broad enough to describe a complete supply chain. Fintech is defined as the provision of technology to financial service providers (Dorfleitner et al. 2017 ), as well as the provision of financial products or innovative financial services (Ratecka 2020 ) characterized by sophisticated technology (Knewtson and Rosenbaum 2020 ). Fintech can also refer to companies that provide innovative digital solutions for financial services (Laidroo et al. 2021 ). Moreover, Fintech is used to describe a series of new business models that have significant impacts on the financial market and supply of financial services (Li and Xu 2021 ). Fintech can even refer to an industry that applies technology to improve financial activities (Schueffel 2016 ). In the academic context, Fintech is a cross-disciplinary subject that combines finance, technology, and innovation management (Leong and Sung 2018 ). It is possible to define Fintech as initiatives (Nicoletti et al. 2017 ) that introduce new products and technologies (Goldstein et al. 2019 ) and reduce information asymmetry in the financial industry (Li and Xu 2021 ). Fintech can also be used as an inclusion mechanism that empowers financially underprivileged individuals to gain access to the traditional financial industry. As a business and an academic term, Fintech has been applied in various contexts (Schueffel 2016 ). However, due to its nature, Fintech is Internet-based and financial-related in all contexts.

The diversity of Fintech development has resulted in its investigation across various disciplines. Thakor ( 2020 ) identified the following four areas of focus in Fintech and banking: (1) credit, deposits, and capital-raising services; (2) payments, clearing, and settlement services; (3) investment management services; and (4) insurance. They viewed Fintech as a disruptive innovation for traditional banks, especially for banks in the payment sector. Sangwan et al. ( 2019 ) undertook a thematic review of Fintech articles based on three themes—(1) industrial, (2) entrepreneurial, and (3) legal. They found that Fintech has had the most significant impact on the financial market in terms of capital and information asymmetry. Furthermore, Sangwan et al. ( 2019 ) stated that Fintech promises immense potential for further study by various stakeholders. In recent years, a few mapping studies have been performed in the Fintech field. Khan et al. ( 2022 ) analyzed 91 Fintech articles across five databases. They explored the barriers to and development of Fintech in the Gulf Cooperation Council regions and found that Fintech is a promising area for research due to its potential to provide various financial services worldwide. Ahmi et al. ( 2020 ) conducted a bibliometric analysis of Fintech research based on the Scopus database and identified basic research trends in Fintech. They suggested that although Fintech is a relatively new term, it highlights the significance of technology in the financial services industry. However, these mapping studies provided limited information on general Fintech research. Therefore, a comprehensive Fintech mapping study is required to systematically analyze the current research state and serve as a basis for future studies.

A lack of consensus among scholars and practitioners on the definition and theoretical foundations of Fintech has led to its multidimensional development across a range of meanings (Milian et al. 2019 ). Currently, the most common classification of Fintech research is in the business dimension. Suryono et al. ( 2020 ) classified Fintech research based on business models. They divided Fintech research into Fintech in general; payment, clearing, and settlement; risk management and investment; market aggregators; crowdfunding; peer-to-peer (P2P) lending; cryptocurrency; and blockchain. Takeda and Ito ( 2021 ) classified Fintech into the following four types according to company development and values derived from innovation: existing financial institutions, new entrants, new value-added, and improved efficiency. Additionally, they noted that among the articles reviewed, those addressing the new value-added by new entrants were the most numerous, whereas those examining improved efficiency by existing financial institutions were the least. Gomber et al. ( 2017 ) introduced the concept of the digital finance cube from the perspective of business administration and function. They divided Fintech into the dimensions of business functions (i.e., financing, investments, and payments), technology and technological concepts (i.e., blockchain, social networks, and near-field communication), and institutions (i.e., Fintech companies and traditional service providers). However, they viewed Fintech as an element of digital finance and did not identify frequency of studies in each dimension to present the current research state. Previous studies have demonstrated a lack of systematic dimensional differentiation in Fintech research.

Fintech, which primarily comprises startups that develop innovative services targeting specific finance-related functions, is still in its early stages of development. However, its growing prominence in the financial industry and the ongoing debates in the field have made it necessary to review and analyze Fintech research to consolidate existing knowledge and identify strategic areas for future innovation and development. Analyzing past and existing work is crucial for understanding anticipated trends in Fintech, as argued by Goldstein et al. ( 2019 ). Therefore, this study aims to bridge the gap by summarizing and analyzing current Fintech research to encompass the diverse research strands of Fintech and synthesize a comprehensive view of present and future Fintech studies. Using a comprehensive Fintech classification scheme, this study presents a systematic mapping review of Fintech studies to analyze the existing literature in both its current state and development trend and propose future research directions by answering the following research questions (RQs):

RQ1. What is the current state of Fintech research?

Rq2. what is the current maturity level of fintech research, rq3. what types of fintech does fintech research involve, rq4. what are the potential future directions of fintech studies.

The four RQs stem from the research motivation stated above. RQ1 and RQ2 aim to establish a fundamental understanding in the development of broad Fintech research. RQ3 aims to provide a systematic review of the existing types of Fintech and propose a classification scheme for Fintech studies. Finally, RQ4 aims to discuss the potential future directions of Fintech research based on the results of RQ1–RQ3.

Compared with previous studies, this systematic mapping presents a comprehensive view of Fintech research with detailed numerical data. Unlike similar mapping studies in the field, this study not only provides a simple research trend but also analyzes the situation in depth to assess the maturity level and future directions. It contributes to the literature by (a) describing the current state of Fintech studies by presenting statistical data on general trends, productive authors, and active countries in global Fintech studies; (b) identifying the maturity level of current Fintech studies by investigating the general index of research focus; (c) synthesizing the different types of Fintech into five dimensions to clarify the Fintech framework and enhance the understanding of this emerging research area; and (d) undertaking an in-depth analysis to explore future directions of Fintech studies. The study also ensures the quality of the results by considering the impact of the selected articles.

Methodology

Systematic mapping review.

A systematic mapping review is a study that collects existing literature on a specific topic (Bates et al. 2007 ) and identifies the linkages between literatures (Cooper 2016 ) for further reviews (Grant and Booth 2009 ) and categorizes them according to predefined keywords to create a coded database of literature (Bates et al. 2007 ). Unlike systematic literature reviews, systematic maps are primarily concerned with structuring a research area (Petersen et al. 2015 ) and focus on the characteristics of articles (Cooper 2016 ).

The results of the systematic mapping serve a range of functions (Bates et al. 2007 ). In addition to providing an overview of a particular topic (Kitchenham et al. 2011 ), they provide the basis for an informed decision about whether to undertake an in-depth review and synthesis of all or a subset of the studies (Grant and Booth 2009 ). A systematic mapping review can also establish whether these studies will help answer the RQs and address pragmatic considerations about the resources available to complete the review (Grant and Booth 2009 ). This mapping study applies the process described in the Social Care Institute for Excellence (SCIE) Systematic mapping guidance (Clapton et al. 2009 ; Petersen et al. 2008 ).

Mapping process

Appendix 1 presents the visual workflow of the mapping process in this study. The research process consists of four stages—exploration and preliminary work, search strategy design, research execution, and coding and analysis. The research aims were first defined. Then, the existing scope of Fintech literature was identified, followed by capturing the broad and diverse research strands using a broad definition of Fintech. As the scope of this study aims to provide a thorough exploration of Fintech research, the RQs were developed from multiple dimensions. Therefore, general and broad search strings were chosen to gather sufficient articles across various disciplines. The search strings were refined and modified through iterative test searches until a satisfactory result was obtained.

A list of articles was collected from four databases based on the inclusion criteria outlined in Table 1 . To eliminate duplicates, Endnote was initially used, followed by manual content checks. Next, a set of exclusion criteria was applied to filter out additional articles. The screening process and results of each phase are presented in Fig.  1 . Finally, the selected articles were classified, aggregated, visualized, and mapped in a way that addresses the RQs (O’donovan et al. 2015 ). The process of constructing the scheme and extracting data underwent multiple iterations to achieve optimal results. To distinguish the authors of the selected articles from the current authors (Riccio et al. 2020 ), the authors of this study are referred to as “assessors”.

Screening process

Research questions

This study aims to determine the existing scope of Fintech literature and establish a foundation for future research in the field. To achieve this, the RQs were formulated to capture the diverse articles related to Fintech.

This RQ aims to provide an up-to-date snapshot of Fintech research to determine the current state of research in the field through a cross-sectional study of four key aspects—authorship, country, article type, and impact. By examining these factors, this question seeks a static view of Fintech research and identify trends and patterns that can inform future research in this rapidly evolving field. The impact of articles will be considered alongside other aspects in this analysis.

The investigation of maturity level positions Fintech research in a dynamic state. Studying the maturity of Fintech research provides researchers with stronger intuitive insights into the development of the field. This question explores the current research focuses to identify concentrated research content and business activities in the industry.

The definitions of Fintech are often inconsistent and ambiguous (Schueffel 2016 ), which hinders a comprehensive understanding of innovative practices and developments in the industry. To address this issue, this RQ aims to broaden the scope of Fintech beyond its typical categorization by business models (Dorfleitner et al. 2017 ). By exploring diverse types of Fintech in the broadest sense, this question aims to provide a more comprehensive and nuanced understanding of the Fintech landscape.

To provide practical guidance for future research, this RQ aims to identify emerging areas in primary studies and the focus of scholars to obtain the potential research opportunities in Fintech.

Database selection

In this article, four well-known digital databases were employed for a comprehensive and quality coverage of the research area. The databases are the Association for Computing Machinery (ACM) Digital Library, Institute of Electrical and Electronics Engineers (IEEE) Xplore, Scopus, and Web of Science (WoS).

Both the ACM Digital Library and IEEE Xplore are science-related databases that mainly cover technical articles related to Fintech. The ACM Digital Library is employed for its extensive full-text articles and bibliographic literature that covers computing and information technology. IEEE Xplore provides a large number of indexed conference proceedings that allow the identification of emerging trends in research at an earlier stage (Chigarev 2021 ).

As a large database of abstracts and citations, Scopus offers a rich advanced search feature. It contains articles published in peer-reviewed journals by multiple publishers (Riccio et al. 2020 ). In addition, its multidisciplinary aspect allows researchers to easily search multiple disciplines (Burnham 2006 ). Although Norris and Oppenheim ( 2007 ) argued that Scopus is weak in the coverage of foreign journals and does not currently include social science articles published before 1996, this study is limited to articles written in English and published since 2000. As the largest data source in this study, Scopus was chosen to ensure that a wide variety of research domains are included (de Sousa Borges et al. 2014 ). WoS is a widely recognized proprietary database for peer-reviewed journal content (Mikki 2009 ). Therefore, WoS was used as a trustworthy source of quality studies, providing a depth of coverage.

Search string strategy

A systematic mapping study is generally considered less stringent (Kitchenham et al. 2011 ) as it usually focuses on the big picture and covers a large number of relevant articles in the field of study. This study employed a search string strategy of the research titles and keywords using the following keywords: “Fintech”, “Financial Technology”, “Fin Tech”, and “Fin-tech”. This strategy mainly returned articles with a higher-level and business-oriented focus rather than those with a technical or engineering focus. Additionally, articles that solely focus on blockchain and cryptocurrencies were excluded from this study. The search strings were created by combining the keywords and inclusion criteria, as presented in Table 1 .

As each database’s search facility is different, the primary search strings had to be transformed into the native syntax of each database (O’donovan et al. 2015 ). An example of a search query for the Scopus database is presented in Table 2 .

Screening of research

The screening process for this mapping study is illustrated in Fig.  1 , and the search was performed on December 14, 2021. A total of 976 Fintech-related articles were initially identified from the four selected databases, with 207 duplicates were removed using Endnote, primarily from Scopus and WoS. An additional 106 duplicates were removed manually, including pre-published papers, based on the exclusion criteria. This was done to ensure the clarity and practicality of the results.

The 663 nonduplicated articles were processed using the exclusion criteria presented in Table 3 . Only articles that directly focus on Fintech or are associated with Fintech practices or concepts are included, and studies that do not meet this criterion (28 articles) were excluded. To ensure a reliable understanding of the selected articles, this mapping study considers only those that are available in full text or have abstracts that provide sufficient information. The impact of each article has been considered, and for journal articles to be included, the journal must have a quartile rank (based on information from the SCImago database) or be listed in the WoS Master Journal List. Journals that are not assigned a quartile rank but are included in the Scopus database (usually new journals) are also included in this study. Regarding conference papers, they must be published in the Computing Research and Education Association of Australasia (CORE) conference list (“CORE Rankings Portal” 2016 ) or in either an ACM or IEEE conference proceeding. The impact criterion excluded 94 articles from this mapping study.

During the second round of screening, it was found that three articles had excessive recycled content under different titles by the same authors, and one article was a book that was misclassified by the databases. Therefore, the final number of articles included in this mapping study is 518.

Data abstraction and synthesis

To answer the RQs, the extracted data were synthesized through a data synthesis process (Li et al. 2015 ). In the data extraction step, the assessors thoroughly read, analyzed the relevant studies, and extracted all necessary information into a spreadsheet (Riccio et al. 2020 ). Afterward, the data were then grouped and synthesized for further frequency, network, and cooccurrence analyses.

The structures for answering each RQ were designed during the initial screening. For RQ1, the current state of Fintech studies is answered by classifying the statistical data of primary Fintech studies into four aspects—authors, countries, type of articles, and publication impact. Appendix 2 presents the detailed structure of data extraction. To answer RQ2, the maturity level of Fintech research was examined through an analysis of research focus and levels of activity.

In terms of RQ3, this study explored diverse types of Fintech beyond business models. Although the commonly used Fintech classification is based on business models and service types, this article refined the generalized “Fintech” by categorizing it into (1) Fintech industry; (2) Fintech business; (3) Fintech platforms, systems, and apps; (4) Fintech services and Fintech as a tool; and (5) Fintech technology. The classification was developed based on observations made from the selected articles. Furthermore, a frequency analysis of each type of Fintech was conducted to provide a comprehensive understanding of the level of activity in each category.

To address RQ4, we conducted a comprehensive evaluation of the selected articles and examined the limitations and future directions identified by the authors. Through this process, we identified gaps in the current literature and provided insights for future studies. In addition, we offered our own perspectives on the research priorities in the field.

The datasets used and analyzed during the current study are available in the Mendeley repository ( https://doi.org/10.17632/gd4hc7ym7r.3 ). Following the above systematic process, the results of this mapping study are presented below.

Results and analysis

This section presents a synthesis of the data extracted from the primary studies. A total of 518 primary studies conducted from 2008 to 2021 were analyzed to answer the four RQs. The data analysis involved a qualitative content analysis, where the assessors identified and analyzed key themes, categories, and dimensions based on the data. The assessors used their own judgment and interpretation to group and categorize the data, considering the frequency and coverage of the selected articles both geographically and thematically (Meçe et al. 2020 ). By synthesizing and organizing the findings, a comprehensive and extensive understanding of Fintech was obtained, providing valuable insights and perspectives for future research.

RQ1 What is the current state of Fintech research?

The earliest article on Fintech identified in this study was in 2008, but there was a gap until 2016. From 2016 to 2017, there was a 73% increase in the number of articles (from 11 to 19). Since 2018, there has been a significant increase of 195%, with a total of 56 articles. In 2019, there was a stable rise of 5% (from 56 to 59 articles). The number of Fintech articles continued to surge, reaching a peak in 2021 with a total of 202 articles.

To ensure the quality of the articles included in the study, their impact was considered. During the initial screening, 94 articles from journals and conferences papers were excluded as they did not meet the impact criterion (EC3). The distribution of the included articles by year and impact criteria is presented in Table 4 . Among the journal articles, 151 were published in Q1 journals, 122 in Q2, 85 in Q3, and 59 in Q4. Additionally, although 33 journal articles were not assigned a quartile ranking by SCImago, they were included in the study because they were indexed by WoS or Scopus.

The selected conference proceeding papers totaled 68, with 23 appearing in the CORE conference list, 13 in IEEE or ACM conferences, and 32 in the WoS list or Scopus list or assigned a quartile ranking in the SCImago database. While the largest increase in the number of articles occurred in 2021, most of the increase was observed in Q1 and Q2 articles.

Regarding authors

Out of the 518 selected articles, 1381 unique authors contributed to them. The top productivity level of authors was four Fintech articles each. Among these prolific authors, three of them published all their Fintech articles in Q1, WoS journals, or in more prestigious conferences, such as CORE, IEEE, and ACM. These authors can be considered the most productive in terms of publishing high impact Fintech research. In particular, the first author in Appendix 3 has published four high impact articles, which also achieved very high citation rates per year. The top productive authors with three or more articles are presented in Appendix 3 .

Countries of publications

A total of 82 countries were involved in Fintech publications, with international collaborations accounting for 25.67% (135 out of 518). Table 5 presents the top ten countries ranked by the number of Fintech articles and the number of articles in high impact journals (Q1 and WoS). China leads with 102 articles, followed by the US with 60 articles and Indonesia with 46 articles.

Type of articles

The primary studies selected for this review were limited to published journal articles and conference papers. Of the 518 studies, 450 (86.87%) were journal articles and 68 (13.13%) were conference papers, as depicted in Fig.  2 . Research articles were the most common type of journal article, comprising 68.22% (307 articles). Perspective, opinion, and commentary articles accounted for 16.67% (75 articles), while review articles accounted for 7.56% (34 articles).

Distribution of article types

Tables 6 and 7 present the most prominent journals and conferences for publishing Fintech research, respectively. Journals that have published more than five articles and conferences that have published more than three papers are included.

Table 8 presents a comparison of popular research areas in journal articles and conference papers. The analysis indicates that journal articles tend to focus on macro-level discussions of Fintech development, while conference papers are more oriented toward technology aspects.

Publication impact

Among the journal articles, 142 were published in Q1-ranked journals and listed in the WoS Master Journal List, which accounted for 31% of the total primary studies. Articles with more than 50 citations per year are summarized in Appendix 4 . The number of citations per year was calculated based on citation data from Google Scholar, with all citation windows calculated from the first available year to 2022 rather than the official publication year.

RQ2 What is the current maturity level of Fintech research?

The maturity level of Fintech research was evaluated based on the research focus and levels of activity. The research focus was analyzed in the following two ways: (1) by a matrix of research lenses and areas and (2) by conducting a keyword analysis of titles and abstracts using VOSviewer. Both approaches indicate that Fintech is a low maturity research sector that falls between technology triggers and the peak of inflated expectations (Steinert and Leifer 2010 ). The business lens reveals that Fintech research primarily focuses on startups and financing, indicating that the industry is still in a nascent stage with low maturity compared with other industries.

In the first approach, four research lenses (business, socioeconomical, technological, and political regulatory) were identified. The business lens examines the management and operations of firms as well as their development on a microeconomic scale. The socioeconomical lens focuses on macro-level social and economic development on a national, regional, or global scale. The technological lens covers the technological side of Fintech, including system development, Blockchain, and artificial intelligence (AI), etc. Finally, the political regulatory lens includes studies on national policy or regulations related to Fintech. It is possible for one study to fit into multiple lenses when it addresses multiple aspects.

The research areas were identified, summarized, categorized, and synthesized through three rounds of screening and are presented in Appendix 5 . In the first screening, the assessors thoroughly read the articles and identified the detailed research focus of each study. Then, the detailed research focus was abstracted and categorized into a general research area. In the second round, the assessors read the articles again to ensure they fit into the correct research area(s). The research areas were then synthesized into broader categories, including introduction and overview of Fintech; interaction between Fintech and industries; interaction between Fintech and institutions; interaction between Fintech and small and medium-sized enterprises (SMEs); management; innovation and development of Fintech; Fintech adoptions; Fintech ecosystems; Fintech user and service analysis; risks and issues of Fintech; sustainability; social-related areas; macroeconomy; credit systems; security; Fintech system development and maintenance; technologies in Fintech; regulation; and governance.

The third round of screening involved reading all the primary studies and assigning them to each research lens, while ensuring they are placed in the correct research category. To present the patterns in the table, the highest frequency in the research lens of each research area is highlighted in Appendix 5 . In Appendix 6 , a cooccurrence network analysis is presented to better understand the interdisciplinary relationships between different research areas and how they interact with each other. Additionally, in Appendix 7 , a cooccurrence matrix on research lenses is presented to indicate research density and centrality, providing a clear picture of the prevalence and importance of different research lenses in the selected articles.

Figure  3 depicts the outcomes of the keyword analysis using VOSviewer—an online bibliometric network visualization tool. The node size denotes the frequency of appearance in the title and abstract fields of Fintech research, with larger nodes indicating higher frequency. The analysis highlights that banking, regulation, challenge, lending, use, and adoption are the most frequently occurring words in Fintech research. The proximity of two nodes indicates their relatedness, with closer nodes indicating a stronger relationship. The analysis identifies the following four clusters: the red cluster presents keywords in the business lens, the green cluster indicates keywords in the socioeconomical lens, the yellow cluster highlights keywords in the technological lens, and the blue cluster presents keywords in the political regulatory lens. Some studies fit into multiple clusters as they discuss multiple aspects.

Keywords analysis

The keyword analysis revealed three key research areas with the highest frequency—Fintech and banking (represented by “banking” in Fig.  4 ), customer adoption of Fintech (represented by “adoption” in Fig.  5 ), and Fintech development (represented by “Fintech development” in Fig.  6 ).

Linkage of banking

Linkage of adoption

Linkage of Fintech development

In addition, keyword analysis provides insights into the relationships between different keywords. For example, in Fig.  4 , the keyword “banking” is closely related to “business”, “financial markets”, “access”, and “sustainable development”. This observation can be supported by the work of Kou et al. ( 2021 ), which suggests that banks invest in Fintech to achieve a competitive advantage in the financial market. Figure  5 depicts that the keyword “adoption” is closely related to “trust”, “Fintech service”, “benefit”, “ease (of use)”, and “intention (of use)”. In Fig.  6 , the keywords “regulation”, “regulator”, “financial inclusion”, “access”, and “challenge” are closely related to “Fintech development”. This suggests that Fintech development is heavily influenced by challenges related to regulatory policies and financial inclusions.

RQ3 What types of Fintech does Fintech research involve?

The difficulty of defining the exact boundaries of Fintech is evident in the vague definitions that have been presented in the literature (Lai and Samers 2021 ). Although Fintech is often categorized based on its distinctive business models (Dorfleitner et al. 2017 ), it encompasses a wide range of financial technology-related aspects. The objective of RQ3 was to create a clear and robust classification system for all types of Fintech for understanding the latest innovations and emerging developments in this rapidly evolving field to provide a foundation for future research.

To classify the diverse types of Fintech mentioned in the selected articles, the assessors read, abstracted, and coded them. They were organized into five distinct dimensions, as presented in Appendix 8 . The classification presented in this study adopts an industry structure framework, encompassing not only the various segments within the Fintech industry but also the regulators and supervisors overseeing it. Within this framework, the dimension of “Regulation and supervisions” oversight and compliance is explored, with topics such as regulatory sandboxes, regulatory challenges, and legislative issues frequently discussed. In addition, the category of “Fintech in general” captures broader conceptual discussions surrounding the industry, including its definition and overview, as well as its associated risks and general issues. This multidimensional classification allows for a comprehensive and nuanced understanding of the Fintech landscape and its components.

The classification scheme also identified the frequency of Fintech types discussed in the primary studies. As a single study may cover multiple types of Fintech, the numbers may overlap across categories. The number of the units and sub-units are not in an inclusion relationship but only the frequency with which each unit appeared in the selected articles. The five main Fintech categories are described below.

Fintech industry

In this study, the Fintech industry is categorized as a macro dimension (113 articles) that includes various Fintech firms and encompasses the entire supply chain of Fintech services for commercial and retail customers. Although some scholars argue that Fintech is not yet recognized as an independent industry (Wójcik 2020 ) but rather a branch of the general financial industry (Pollari 2016 ), to identify the logical flow of diverse types of Fintech, in this study, it is considered an industry rather than a segment of the financial industry.

Fintech firms

A total of 58 articles were identified that discussed Fintech firms in general. The Fintech industry comprises Fintech firms that offer both business-to-business (B2B) and business-to-consumer (B2C) services, covering technology, financial services, and other aspects of Fintech. For instance, companies that provide technology to financial service providers (Dorfleitner et al. 2017 ) were classified as Fintech firms. Similarly, companies offering nonbanking financial services, such as online insurance services and mobile money services, were also considered Fintech firms. The four main topics related to Fintech firms are (1) Fintech startups, (2) investment in Fintech businesses (Fintech investments), (3) financing solutions or problems of Fintech businesses (Fintech financing), and (4) the management of Fintech firms (Fintech management).

Fintech systems, Fintech platforms, and Fintech apps

Fintech firms are responsible for the development and ownership of Fintech systems, platforms, and apps. These technological tools enable firms to offer Fintech services and tools to their clients.

This mapping study applied the definition of Fintech platforms proposed by Dhar and Stein ( 2018 ) that Fintech platforms are complete or incomplete platforms that facilitate exchange between interdependent groups, usually consumers and producers, through a combination of channel access, functionality embedded in an information technology system, and associated key business processes. Examples of Fintech platforms are Amazon and PayPal.

In contrast, Fintech systems refer to the technology systems that provide financial services to various companies, such as online accounting systems and other software-as-a-service financial solutions. Additionally, Fintech systems encompass systems that enable Fintech services. Fintech apps are mobile applications provided by Fintech firms that allow users to access their financial services.

Fintech as tools and Fintech services

“Fintech as tools” and “Fintech services” are supported by various Fintech technologies. In this study, “Fintech as tools” refers to B2B Fintech tools used by traditional financial institutions and other industry service or product providers. These institutions adopt Fintech tools to serve their customers or streamline their business operations. Some examples of Fintech tools are online banking, chatbots, and robo-advisors.

“Fintech services” are directly offered to end users and include investment services, lending, payments, and insurance. Fintech services were the most discussed in the selected research. Within the dimension of Fintech services, P2P lending and payment, transfer, and settlement were the two most frequently discussed subunits in the selected studies.

Fintech technology

Fintech technology encompasses the various technologies utilized in Fintech services, such as the Internet of things (IoT), AI, machine learning (ML), and deep learning. As the building blocks of Fintech, these technologies support other sectors in the industry. Among the technologies discussed in the sample articles, blockchain was the most frequently mentioned, followed by AI, ML, and big data. Although they are less discussed, IoT, deep learning, and cloud computing are also important technologies that should not be overlooked in Fintech research.

RQ4 What are the potential future directions of Fintech studies?

Trending topics.

The insights gained from past articles on Fintech can help us identify future research directions. Fintech development, Fintech and banking, and Fintech adoption are currently the most popular research topics in Fintech and are expected to remain so in the future. By examining the future research directions outlined in the selected articles, we identify potential areas of research in each topic.

In the area of Fintech and banking, future research is likely to focus on the integration of banking and Fintech systems. Regarding Fintech adoption, research will continue to explore end users’ continued use of Fintech services, as well as the perceived benefits and risks of such services for customers. In the field of Fintech development, there is a need for further investigation into sustainable development, including consumer protection, cross-industry cooperation, and financial regulation.

In addition, technology adoption in Fintech has the highest growth rate in articles. Based on the proposed Fintech classification scheme in this study, Fintech technologies are the fundamental units that support Fintech services. Future research in this area will continue to explore how the use of technology influences the service scope and innovation ability of Fintech services and ultimately shapes the future of the Fintech industry.

Fintech and sustainable development

The topics discussed above prompt us to reflect on the future of Fintech and its potential impact on sustainable development. The rapid advancements and innovations in Fintech can serve as a driving force for sustainable development, while the pressing need for sustainable development can provide a compelling impetus for further Fintech innovation and progress. The interplay between these two forces is complex and multifaceted and requires careful consideration by researchers, policymakers, and industry leaders.

Fintech has the potential to significantly contribute to sustainable development, and this is a promising field that warrants further investigation. Past research suggests that Fintech can promote sustainable development in many ways. First, the innovative nature of Fintech arises from the financial industry’s pursuit of sustainability with the technology being applied to financial services to reshape existing propositions (Petrushenko et al. 2018 ) and support digital financial transformation (Arner et al. 2019 ), enabling Fintech to offer a broader range of services to customers and promote financial inclusion. Second, Fintech serves as a catalyst for technology-driven sustainable development. As a technology-driven industry, Fintech integrates technology into financial services, enabling it to act as a technology enabler (Beder 1994 ) and foster sustainable development. Third, Fintech has the potential to promote sustainable development in various industries due to its role as an intermediary and final goods provider. As a platform industry (Shin and Choi 2019 ), Fintech can integrate with almost all industries, enabling sustainable development and promoting overall economic performance. Given its potential, it is crucial to continue exploring Fintech’s role in sustainable development to identify ways in which Fintech can promote sustainable development.

Exploring innovation is essential for the future of sustainable development in the Fintech industry. Sustainable development in Fintech aims to improve existing technologies for long-term development, ensuring that current needs are met without compromising the ability of future generations to meet their needs (Rogers et al. 2012 ). To achieve sustainable innovation, the application of technology in Fintech needs to be deepened and broadened. Fintech technology serves as the foundation of the industry structure and expanding its application will enrich service categories. Additionally, deepening the industry’s foresight by developing interpretative financial datasets for analyzing and predicting anomalous financial situations can aid in sustainable innovation (T. Li et al. 2021 ).

The Fintech industry relies heavily on information and communication technology to create innovative and disruptive business models in financial services (Leong and Sung 2018 ). The urgency for Fintech innovation has increased in the post-COVID-19 era, particularly in improving financial service processes. Finally, Fintech innovation will drive research into the application of Fintech in different user scenarios. While most Fintech services are currently used as a tool to complete a business loop, expanding the scope of Fintech usage across various user scenarios is essential for sustainable development. Therefore, sustainable innovation is critical to the future of the Fintech industry. By expanding the application of technology, promoting financial innovation, and researching Fintech applications in different user scenarios, the Fintech industry can achieve sustainable development.

Discussion and conclusion

This systematic mapping study provides an extensive overview of Fintech research, including its current status, maturity level, and types of Fintech. Through a systematic review of 518 Fintech articles from 2008 to 2021 across four databases, the study reveals that Fintech is an emerging research field, and the number of Fintech articles is rapidly increasing, especially in 2021. The study also found that China, the US, and the UK are leading in both the total number of articles and high impact articles. The maturity level of Fintech research is still in its early stage, and Fintech services are the most popular research area. The study proposes future research directions, such as exploring the integration of Fintech and banking systems; assessing the continued use and perceived benefits and risks of Fintech services for end users; and investigating sustainable development of consumer protection, cross-industry cooperation, and financial regulation.

Maturity level

The maturity level of Fintech studies is investigated through the research areas and lenses. The results reveal that Fintech and banking, Fintech development, and Fintech adoption are the most popular research areas, and the number of articles is increasing. Fintech is a business-related industry that combines financial and technology in both word and content. More than half of the Fintech articles fall under the purview of the business lens. However, the number of studies in the socioeconomic and political regulatory lenses is increasing, reflecting growing social and regulatory concerns, especially in financial inclusion. Regulatory sandbox in the Fintech industry is another topic that has recently attracted attention. In terms of the maturity of research, Fintech is still in its initial stage of development, positioned in the middle of technology triggers and the peak of inflated expectations (Steinert and Leifer 2010 ). Most Fintech products or business models are in their first generation from mass customisation to personalisation. Compared with other industries, the research area of Fintech in the business lens is concentrated on startups and Fintech financing, indicating that Fintech is at a low maturity level.

Types of Fintech

The classification of Fintech can be challenging due to the large volume of articles and broad coverage. The assessors proposed a vertical classification scheme based on the most commonly appearing dimensions in current studies. In the scheme, Fintech is categorized into the following five dimensions: (1) Fintech industry; (2) Fintech firms; (3) Fintech systems, platforms, and apps; (4) Fintech as tools and Fintech services; and (5) Fintech technologies. The results reveal that while Fintech research is evenly distributed across each level, Fintech services and the Fintech industry are popular research topics currently. However, Fintech services remain a top priority for future development as the value of Fintech to its users lies in improving their experience. The structure and future development of the Fintech industry will evolve depending on the future growth and innovation of Fintech services. Regardless of the level, Fintech should always aim to be a financial solution and innovation initiator that integrates financial services, enhances customer experience, adapts to regulatory change (Pollari and Raisbeck 2017 ), and fosters cooperation between different industries driven by technology.

Future research directions

Future directions for Fintech research involve exploring the integration of Fintech and banking systems, continued use, and perceived benefits and risks of Fintech services for end users, as well as sustainable development of consumer protection, cross-industry cooperation, and financial regulation. One critical area of exploration is the impact of Fintech on sustainable development and the sustainable development of the Fintech industry itself. Fintech has the potential to contribute to sustainable development through its innovative nature, technology-driven industry, and role as an intermediary and provider of final goods. Therefore, sustainable innovation is a crucial direction for the Fintech industry, requiring the expansion and deepening of Fintech technology applications, financial innovation, and the exploration of Fintech applications in various user scenarios. Specifically, the Fintech industry has the potential to play a vital role in achieving sustainable development through its innovation and technology-driven approach.

Contributions

This mapping study contributes to the Fintech literature in several ways. First, unlike most existing reviews that assess Fintech research based on a single definition, this study integrates diverse types of Fintech and provides a comprehensive analysis with numerous data and figures. Second, this study not only presents the most recent research state but also examines the maturity of Fintech research, enabling both researchers and practitioners to evaluate the direction and scope of future research. Furthermore, the study provides a comprehensive classification that considers all types of Fintech identified in selected studies and proposes a vertical classification scheme for the Fintech category. The results provide valuable research information for scholars and practitioners and support the identification of future research areas and a unique perspective on the subject.

Limitations

This study has certain limitations as it only includes highly Fintech-focused articles. Articles that are related to Fintech but do not directly focus on it, such as those that only concentrate on blockchain or cryptocurrencies, are not covered. Therefore, future studies may explore each research subject individually and in greater detail.

Availability of data and materials

The datasets used and analysed during the current study are available in the Mendeley repository. Liu, Qianhua (2022), “Fintech research: systematic mapping, classification, and future direction”. Mendeley Data, V1, https://doi.org/10.17632/gd4hc7ym7r.1

Abbreviations

Association for computing machinery

Artificial intelligence

Business-to-business

Computing research and education association of Australasia

• Financial technology

Institute of electrical and electronics engineers

Internet of Things

Machine learning

Peer-to-peer

Quartile 1, Quartile 2, Quartile 3, and Quartile 4 journals

Research question

Social care institute for excellence

Small and medium-sized enterprises

Web of science

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Acknowledgements

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The current research study was conducted as part of Liu Qianhua's PhD research project at University of Southern Queensland under the supervision of Dr. Chan Ka-Ching and Dr. Chimhundu Ranga. No other external or internal sources of funding to declare.

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QL: Substantial contributions to the conception and design of the work; Substantial contributions to the acquisition, analysis, and interpretation of data; Substantial contributions in writing the manuscript; Read, revised and approved the final manuscript. K-CC: Contributions to the conception and design of the work; Contributions to the analysis and interpretation of data; Read, revised and approved the final manuscript. RC: Contributions to the conception and design of the work; Read, revised and approved the final manuscript.

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Appendix 1: research process

The graph shows the research process followed by this mapping. Applied the process from the SCIE Systematic mapping guidance (Clapton et al. 2009 ; Petersen et al. 2008 )

Appendix 2: data synthesise structure of RQ1

Appendix 3: top productive authors

• The table presents a list of the most productive authors who have published three or more fintech papers among all the primary studies
• 1 WoS: Inclusion of Journals or Conferences in WoS Master Journal List (Y = Included; N = Not included)
• 2 Citations per year are calculated based on the first online-available year

Appendix 4: articles cited more than 50 times per year

• 1 WoS: Inclusion of Journals in WoS Master Journal List (Y = Included; N = Not included).

Appendix 5: combination of research area and research lenses

This table shows the number of papers in each research area and lens. The business lens examines Fintech on a microeconomic scale, while the socioeconomical lens focuses on macro aspects. The technological lens looks at the technology side, while the political regulatory lens examines national policies and regulations. Studies may fit into multiple lenses.

Appendix 6: co-occurrence network analysis on research areas

This network analysis depicts the cooccurrence of each research area, with node size representing the frequency of discussions. Larger nodes indicate higher frequency of discussion. The thickness of lines reflects the strength of cooccurrence relationships between research areas. The analysis highlights that Fintech and bank, innovation and development, sustainability, and social-related areas are the most frequently discussed topics in the selected articles. Fintech and bank are closely linked to innovation and development, risk and issues, and Fintech technologies, suggesting an interconnectivity between these areas.

Appendix 7: cooccurrence matrix on research lens

• This matrix presents the cooccurrence of each research lens. Most studies only focus on one research lens, indicated by the highest value in the matrix. The linkage between different research lenses can also be viewed, a larger value indicates a closer relationship between the two lenses. Notably, the business lens is intricately linked with other lenses, particularly the technological lens. In contrast, the socioeconomical lens is relatively distant from the technological lens.

Appendix 8: classification scheme of Fintech

The Fintech classification scheme presented in this table was created by the authors based on all the Fintech types that appeared in the primary studies. The Fintech types are laid out in the form of an industry structure, and the numbers in the table represent the frequency of each Fintech type discussed in the primary studies.

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Liu, Q., Chan, KC. & Chimhundu, R. Fintech research: systematic mapping, classification, and future directions. Financ Innov 10 , 24 (2024). https://doi.org/10.1186/s40854-023-00524-z

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9 Innovative Literature Mapping Tools Every Researcher Needs to Know

Staying up to date with the latest literature mapping tools for academic research is a major part of any researcher’s workflow from any domain.

Here, I present a compilation of nine cutting-edge literature mapping tools that should be on every researcher’s radar.

Literature Mapping is nothing but a plan of action when finding literature for your academic research.

During the literature review , we often switch to various methods of searching and browsing. It is a tedious job.

Academic Researchers have to face many challenges during this phase to get the relevant papers.

In general, we find some relevant academic papers from various sources through keyword searching.

After receiving articles, we look at the references or citation s of those articles.

This process guides researchers to identify interesting authors and their scholarly publications.

To alleviate the aforesaid issues and hassle-free literature maps, these citation -based literature mapping services play a pivotal role.

After taking one or more relevant seed papers and using various techniques, they recommend new ones that are similar to be integrated.

Various types of free science mapping software can automatically generate relevant related papers based on relevant seed papers .

Using the literature review mapping tools you can visualize them in a map or graph.

I n this blog post, I have compiled a list of  9 powerful and innovative literature mapping tools for academic researchers.

You can use these smart software tools to increase the scale and scope of the literature for your projects.

Below is the list of 9 most useful tools for mapping research literature:

• Citation Gecko
• OpenKnowledge Map
• Connected papers
• Local citation Network
• ResearchRabbit

List of 9 Innovative Literature Mapping Tools

No. #1  citation gecko.

It is a free open-source robust literature discovery and reviews mapping web application.

This literature discovery tool helps you identify the relevant research papers.

The web app was developed by Barney Walker, Imperial College London in 2018 to assist relevant literature discovery to academic researchers.

It has been released as open-source on Github . 

The handy research mapping digital tool allows you to build upon each other’s scholarly works. 

It uses open citation data to recommend relevant scholarly articles based on seed papers.

This literature mapping software takes some seed papers of your study of the field and identifies the relevant articles. 

Besides, it also visualizes the citation network along with its size. You can also discover literature that you may have missed.

No technical knowledge is required to construct and visualize your relevant research articles.

You can do it just by entering some seed papers in the Citation Gecko.

The following sources are used to collect the data:

Open Citation corpus and open citation index of Crossref open DOI-to-DOI Citation s.

In my previous post on how to identify relevant academic papers using the literature discovery tool , I elaborately discussed and demonstrated how to do literature mapping using the Citation Gecko.

No. #2  Inciteful

The literature mapping tool was launched in beta version on 19th December 2020. 

It is a free discovery tool that allows researchers to discover relevant academic research papers in a short time frame.

The Incitefull lets you identify the scholarly material related to the particular topics you have. 

To explore and categorize the literature the online tool uses citation s.

After taking the paper of your interest, the mapping tool surfaces the most relevant papers based on open metadata and citation s.

Academic researchers can import the BibTex file into the web app and export the BibTex file from this web app.

 This facility makes the review of the literature easy.

In my earlier post on how to find relevant Research papers to speed up your literature review , I did a deep dive.

No. #3 OpenKnowledge – A Visual Interface to the World’s Scientific Knowledge

Open Knowledge Maps (OKMaps) is a free and easy-to-understand robust web application.

 The literature mapping tool was developed as open-source and released under an MIT license.

Open Knowledge Maps is a charitable non-profit organization that was founded by Peter Kraker.

The digital tool lets you find the most relevant and credible research papers through a user-friendly graphical user interface.

Open Knowledge Maps allows you to search for the most relevant papers through Pubmed , BASE (Bielefeld Academic Search) , and OpenAIRE .

The OKMaps is one of the world’s largest visual search engines for scientific knowledge. 

The web app provides a visual web interface to the world’s scientific knowledge using knowledge maps.

You do not need to install any software for searching the most relevant scholarly publications. 

In my blog post on how to find the most relevant research papers using a visual interface , I discussed and demonstrated the literature mapping tool.

No. #4 Connectedpapers

After a long beta version, the founders have released the Connected Papers software to the public.

 The Connected Papers tool is a free and easy-to-understand smart software tool. This citation s mapping tool lets you search the relevant and credible resources.

The innovative literature mapping tool has a user-friendly graphical user interface. You do not need to install any software.

You can use it through your desktop web browser. But,  mobile browsers are not supported yet.

The working procedure of this tool is straightforward and easy to understand.

First, you just put a paper of your domain then it generates a graph that displays that part of paper space and their interconnectivity.

The graph is generated using a similarity metric based on the concepts of co citation s and bibliographic coupling.

Beyond that, it also provides additional functions to get the knowledge of “Prior works” and “Derivative works” .

In my article, I demonstrated how to make a literature map using the Connected papers.

No. #5 Litmaps (Discover Science Faster)

Litmaps is a handy interactive visualization tool for discovering scientific literature.

The project is designed and developed by the Litmaps team .

In order to visualize and explore the academic literature, the Litmaps tool is very useful for researchers.

The literature review mapping tool lets you build the interactive academic literature map of keywords, authors, or bibliographies.

Beyond that, this citation mapping tool also permits you to navigate the papers with interactive visualizations of citation graphs.

I have already blogged on how to discover scientific literature with an interactive visualization tool ( Litmaps ).

No. #6 Local Citation Network

Local Citation Network is an online free, open-source, and easy-to-use citation network graph visualizer and is available on Github . 

The research mapping tool helps you with literature review mapping.

This literature review mapping tool was developed by Tim Wölfle , physician-scientist, Imperial College London.

The citation mapping tool allows you to identify the seminal paper s by building and visualizing citation networks.

 Using citation network analysis, this tool does this work.

A Citation network is nothing but a visual network graph that lets you find and explore the influential papers using the number of citation s.

In a blog post on free visualization tools to support the literature survey , I elaborately discussed and demonstrated the Local Citation Network.

No. #7 CoCites

CoCites finds articles that are frequently cited together with an article of interest.

CoCites is developed by Dr. A. Cecile J.W. Janssens, a research professor at the Rollins School of Public Health of Emory University, USA.

It is one of the best co- citation -based tools for searching scientific articles. If the input paper has few or even no citation s then it will not act properly.

After finding articles, it gives out a ranking of the most frequently Co-cited articles.

The data source of this software is the NIH Open Citation Collection (NIH-OCC), public access, broad coverage resources .

In the full version of CoCites, you will be able to:

• Perform a co- citation search using multiple query articles
• Find recently published articles through a citation search
• Filter search results using a similarity score
• Save your search queries for re-use and search updates

No. #8  VOSviewer – Visualizing Scientific Landscapes

VOSviewer is a software tool for constructing and visualizing bibliometric networks. 

These networks may for instance include journals, researchers, or individual publications, and they can be constructed based on citation , bibliographic coupling, co- citation , or co- authorship relations.

VOSviewer Online is a web-based version of VOSviewer. It runs in a web browser and can be used to share interactive visualizations and embed these visualizations in online platforms.

No. #9  ResearchRabbit

ResearchRabbit is a free new literature mapping web app. It is free forever for academic researchers.

This discovery app unlocks a completely novel way to search for academic papers and authors.

Besides, the online tool monitors new scholarly literature, visualizes research landscapes.  

The citation -based literature mapping application lets you keep up with the latest research papers related to your collections!

Now, ResearchRabbit is out of beta version. You can use the tool to discover and visualize academic literature and its authors in new ways.

In general, the discovery tool takes one or more relevant seed papers.

 After using various methods, the ResearchRabbit recommends new ones that are similar to be added.

One of the most important features of this discovery tool is that it provides co- authorship graphs providing another dimension for the researcher to explore the literature forest and add publications by authors.

You can integrate Zotero now, Zotero extension can be used as an extension.

You can bi-directionally link your Zotero folder with ResearchRabbit collections!

Like most other above-mentioned discovery apps, you can add specific articles using DOIs/PMIDs, title search, or by importing research papers through BibTeX or RIS.

In this post, I discussed the 9 best innovative literature mapping tools for academic research you need to know when starting your literature review .

Hopefully, this blog post was useful to you! What othe r discovery and science mapping tools have you used for academic research?

I would love to hear from you. Please feel free to comment below.

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6 ways to use concept mapping in your research

Joseph Novak developed concept mapping in the 1970s and ever since, it has been used to present the construction of knowledge. A concept map is a great way to present all the moving parts of your research project in one visually appealing figure. I recommend using this technique when you start thinking about your new research topic all the way through to the end product, and once you submitted your thesis, dissertation or research article, you can use concept mapping to plan your next project. If you prefer to watch the video explaining the 6 steps, scroll down.

What is the purpose of concept mapping?

You may wonder what the purpose of a concept map is. A concept map shows the different “ideas” which form part of your research project, as well as the relationships between them. A concept map is a visual presentation of concepts as shapes, circles, ovals, triangles or rectangles, and the relationships between these concepts are presented by arrows. Your concept map will show the concept in words inside a shape, and the relationship is then presented in words next to each arrow, so that each branch reads like a sentence. What is the difference between a mind map and a concept map? A mind map is different from a concept map in that a mind map puts much less emphasis on the relationship between concepts.

How to use a concept map in your research

Don’t wait to put your concept map together until only after you have, what you consider, “all the knowledge” and have read “all the literature” (anyway, with two million research articles published each year, will that day ever come?). In the very early stages, when you start thinking about your research project, draw your concept map to get your thoughts organised. Then, as you become more and more abreast with the research out there, modify your concept map.

The process of creating a concept map is an iterative one and you will find that it feels like you have drawn and redrawn the map over and over so many times that you wonder if you are ever going to get to a final version. This process in itself is a learning experience and is vital to sort the concepts out for yourself. If you have clarity in your own head, it is easier to explain what your research is all about to someone else. In addition, including a concept map into a dissertation, thesis, or research article (where relevant) makes it easier for the reader (including the examiner or reviewer) to understand what your research project is all about. There are several instances in your research journey where a concept map will come in handy.

#1 Use a concept map to brainstorm your research topic

When you are conceptualising your research topic, create a concept map to put all the different aspects related to your research topic onto paper and to show the relationships between them. This will give you a bird’s eye view of all the moving parts associated with the chosen research topic. You will also, most probably, realise that the topic is too broad, and you’ll be able to zoom in a bit more to focus your research question better. But before you settle on a specific research question, do a bit of reading around the topic area. Your concept map will show you which keywords to search for.

#2 Use a concept map when planning the search strategy for your literature review

Jumping right into those databases to do a search for articles to include in your literature review can really take you down the deepest darkest rabbit hole. One of those where you find an appropriate article, then gets suggested a few related articles and then you find another few related articles to the related articles, and after 4 hours you can’t even remember what your actual focus was. To avoid this situation, draw your concept map first. You can use the concept map you drew when you brainstormed your research topic to give you guidance in terms of the keywords to search for. Planning your search strategy before you jump in will ensure that you remain on the well-lit path.

#3 Add a concept map to your completed literature review chapter

As you read more about your research topic, you’ll get a better idea of the relationships between the current concepts, and you’ll find more concepts to add to your concept map. Adapt your concept map as you go along, and once you have the final version of your literature review, add your concept map as a figure to your literature review chapter. This will give the reader a good overview of your literature review and it will make their hearts happy because we all know how nice it is to be rewarded with a picture after reading pages and pages of text.

#4 Use a concept map to plan your discussion

Once you completed your data analysis and interpretation, developing a concept map for your discussion will give you clarity on what to include in your discussion chapter or section.

#5 Add a concept map to your completed research project

Once you have completed your entire research project and you want to show how your findings filled a gap in the literature, you can indicate this by modifying the concept map which you created for our literature review. This is a great way to show how your research findings have added to the existing concepts related to your research topic.

#6 Use a concept map to show your research niche area

You can use a concept map to visually present your own research niche area and as your career progresses and you create more knowledge in a specific niche, you can add to your concept map.

How to make a concept map for research

Go to a place where there are very few distractions, a place that is conducive to letting those creative juices flow freely. Seeing that we all function differently, shall I rather say, a place which you perceive as having few distractions. It may be in a park, in your garden, at a restaurant, in the library or in your own study.

Take out a blank piece of paper and start thinking about your research project. Of course, you can do it on a blank page on your laptop as well. One of my students used sticky notes with each sticky note presenting a concept, and with smaller strips of sticky notes showing the relationships between concepts. You can even get all fancy and use concept mapping software. But as a start, a blank piece of paper is more than enough.

Jot down all the ideas that come to mind while you answer the following questions: What is your research about? Why is your research important? What gap does your research fill? What problem will your research solve? What influences your research outcome? Just jot all your thoughts down. Then, once you have all your thoughts on paper, see if you can identify some relationships between the concepts which you noted down. What comes before what? What is a consequence of what? What is associated with what?

Once you are happy with what you have put together, present it to a friend, preferably at a time when both of you are not in a hurry to get somewhere. At a bar with loud music may not work well, and on a first date may also not be a good idea. Explain what is going on in the concept map and give your friend a chance to ask some questions. As you explain it to someone, as well as through fielding your friend’s questions, it will start to make more sense to you, and you will most probably move some concepts around and add new ones. Repeat this process with someone else when you feel you need some more input.

If you are planning to feature your concept map in your thesis, dissertation or research article, now is the time to turn your rough concept map into something more presentable. One can easily get totally lost when it comes to choosing software to create a concept map. Some of the software out there is paid for while others give you a free version for some basic concept mapping. Be careful of that software which only gives you free access for 30 days, remember, you are going to change your concept map quite a few times as time goes on. If you prefer to use software which you are already familiar with, why not just do it in PowerPoint or Word? On the other hand, Lucidchart is really user-friendly. Watch the video below to see how easy it is to create a concept map with Lucidchart. Explore a few options and see what works for you, but be careful, this exploration can take you down that 4-hour rabbit hole and when a proposal submission deadline is looming, that rabbit hole is a dark place to be in.

We'd like to acknowledge Coffee Machine Cleaning  for the image of the coffee cup and notebook used in this blog post. 

Examples of concept maps

Here are a few examples of concept maps that show the concepts and the relationship between the concepts well. Click on the image to visit the original source. Go and enjoy developing a concept map for your research!

One last thing before you go, for more valuable content related to academic research, subscribe to the Research Masterminds YouTube Channel  and hit the bell so that you get notified when I upload a new video. If you are a (post)graduate student working on a masters or doctoral research project, and you are passionate about life, adamant about completing your studies successfully and ready to get a head-start on your academic career, this opportunity is for you! Join our awesome membership site - a safe haven offering you coaching, community and content to boost your research experience and productivity. Check it out!  https://www.researchmasterminds.com/academy . 

Example 1 Little Red Riding Hood

Example 2 Nursing Management

Example 3 Operations Management

Example 4 Cup of Coffee

Example 5 Flexibility

Example 6 Human Body Systems

Example 7 Simple Concept Map Template

If you prefer to watch the video, here it is:

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How the design and complexity of concept maps influence cognitive learning processes

Felix krieglstein.

1 Psychology of Learning with Digital Media, Institute for Media Research, Faculty of Humanities, Chemnitz University of Technology, Chemnitz, Germany

Sascha Schneider

2 Educational Technology, Institute of Education, Faculty of Arts and Social Sciences, University of Zurich, Zurich, Switzerland

3 Digital Media in Education, Department of Psychology, University of Education, Freiburg, Germany

Günter Daniel Rey

Concept maps are assumed to enhance learning as their inherent structure makes relations between information more salient. Nevertheless, research on how to design concept maps as conducive to learning as possible is still rare. In particular, the salience of spatial arrangement of thematically related concepts within the map as well as the complexity of the map were found to be central design elements that influence learning. This study aimed to examine how the structure (i.e., the salience of the spatial relationship between individual concepts) and the complexity (i.e., number of nodes per sub concept) influence learning. Accordingly, a 2 (low vs. high salience of map structure) × 2 (few vs. many nodes) between-subject design was used ( N  = 122) to examine cognitive processes while learning with a concept map. No significant learning performance differences were found. Concepts maps with a low salience of map structure increased perceptions of disorientation. A serial mediation with learning performances as dependent variable revealed that the salience of the map structure is significantly associated with disorientation and extraneous cognitive load perceptions. By this, current attempts to measure extraneous cognitive load are questioned.

Introduction

When learning complex information, it is primarily important to be able to transfer the various components into a coherent model. When learners struggle to create such relations mentally, learning may be hindered. In particular, learners with rather low prior knowledge often need further help to internalize knowledge which consists of interconnections. Hereby, different instructional methods offer the possibility to structure and present information in an easy-to-understand way. One way to organize knowledge hierarchically in a rather simple and compact way are concept maps (Cañas et al., 2015 ; Novak, 1990 ). In contrast to texts, concept maps represent visualized relationships between thematically-related information units. Therefore, the aim of this study was to gain deeper insights into how the salience of the map structure and the number of nodes per sub-concept affect cognitive learning processes.

Learning with concept maps

A concept map is defined as “a node-link diagram in which each node represents a concept and each link identifies the relationship between the two concepts it connects” (Schroeder et al., 2018 , p. 431) while concepts are illustrated in boxes or oval-shaped forms (Novak & Cañas, 2008 ). To specify the relationship between two or more concepts, connecting lines are used that can be labeled to further define this connection (Cañas et al., 2015 ). For instance, the concepts “Facebook” and “Mark Zuckerberg” could be linked with the label “founded by”. The modern idea to structure information in a concept map originates from Novak et al. in the 1970s (Novak & Gowin, 1984 ). In the literature, similar designations like knowledge maps (O’Donnell et al., 2002 ), node-link maps (Blankenship & Dansereau, 2000 ), or mind mapping (Buran & Filyukov, 2015 ) can be found which deal with the graphical representation of information. Theoretical foundations for the benefit of concept maps can be found in the assimilation theory of meaningful learning (Ausubel, 1963 ). In line with this constructivist approach, meaningful learning only occurs when new ideas and concepts are integrated into already existing knowledge structures (see also Kalyuga, 2009 ). In line with Mayer ( 2002 ), all cognitive processes related to the integration of new information into existing prior knowledge structures can be described as meaningful learning. Learners are therefore considered as active individuals who build up new knowledge on the basis of knowledge already gained (e.g., Bada & Olusegun, 2015 ). Since their development, concept maps have been examined in numerous learning settings to determine the extent to which they offer an advantage over comparable instructional methods.

In general, the learning-promoting effect of concept maps is meta-analytically supported (Nesbit & Adesope, 2006 ; Schroeder et al., 2018 ). In a recent meta-analysis by Schroeder et al. ( 2018 ), the learning-beneficial effect could be confirmed with a moderate effect size ( g  +  = 0.58). Hereby, creating concept maps ( g  = 0.72) offered a bigger benefit for learning than studying concept maps ( g  = 0.43). Concept maps can be seen as an effective learning strategy for two main reasons (Schroeder et al., 2018 ): First, concept mapping promotes meaningful learning. In line with Kalyuga ( 2009 ), integrating and organizing new elements into the learner’s knowledge structures can be defined as knowledge elaboration. This process is supported by the inherent structure of concept maps. Therefore, the concept and sub-concept look of concept maps (e.g., Europe—Germany—Federal States—Saxony) illustrates subordinate and superordinate relationships in a more comprehensible way. Compared to texts involving its grammatical structure, concept maps emphasize the macrostructure of the information more clearly (O’Donnell et al., 2002 ). In this vein, meta-analytical findings from Nesbit and Adesope ( 2006 ) revealed that students with low prior knowledge benefitted most from learning with concept maps. Second, the inherent structure of concept maps makes it possible to distribute the cognitive load across the verbal and visual channels of information processing. Thus, a cognitive overload can be avoided (Schroeder et al., 2018 ; Sweller et al., 2019 ). Moreover, it is assumed that concept mapping reduces extraneous cognitive processing due to its simpler structure than is the case when studying or writing texts. Concept maps are therefore also beneficial for learners with a low verbal ability (Haugwitz et al., 2010 ). A recent review by Machado and Carvalho ( 2020 ) also indicated that inserting concept maps into university teaching contributes to developing critical thinking skills, promotes meaningful learning, and facilitates student collaboration. In this context, concept maps find wide application in several learning topics. For instance, they are used in chemistry (Talbert et al., 2020 ), operations management (Essila et al., 2021 ), and pharmacy courses (Carr-Lopez et al., 2014 ).

Cognitive processes while learning with concept maps

While learning several processes take place within the learner. The most important are cognitive processes which determine learning success in a crucial manner. In this vein, the Cognitive Load Theory (CLT, Sweller, 2010 ; Sweller et al., 2019 ) tries to reconcile human working memory characteristics and the instructional design of multimedia learning environments. Cognitive load can be defined as the cognitive burden which is caused by the learning material in dependence on learners’ prior knowledge (Feldon et al., 2019 ). Cognitive load subsumes two additive types: intrinsic and extraneous cognitive load (Jiang & Kalyuga, 2020 ; Sweller et al., 2019 ). Intrinsic cognitive load (ICL) is determined by task complexity (i.e., the element interactivity) and moderated by learners’ domain-specific prior knowledge (Kalyuga, 2011 ). The complexity of the learning material is described with the element interactivity on a continuum between low and high. In line with Sweller ( 2010 , p. 124) an element can be defined “as anything that needs to be or has been learned, such as a concept or a procedure”. On the other hand, the prior knowledge may influence the ICL (Chen et al., 2017 ) as learners with high expertise have already formed schemata, which helps them to solve a problem without a high working memory load. Due to its relevance for learning the ICL can be equated with productive load (Kalyuga & Singh, 2016 ). In contrast, extraneous cognitive load (ECL) is the burden triggered by information-seeking processes that are caused by a non-optimal design and format of the learning material (Sweller, 2010 ). Extraneous processing may be also caused when the information is spatially or temporally distributed or not presented in a comprehensible order (van Merrienboer & Ayres, 2005 ). If working memory resources are already consumed by ECL processes, not enough resources are available to deal with the intrinsic load. The ECL can be changed actively within the design phase of the learning material (Leahy & Sweller, 2016 ). In line with Kalyuga and Singh ( 2016 ) extraneous processing is not relevant for learning and therefore unproductive.

Instructional materials, such as concept maps, also induce a certain amount of cognitive load. Orientated to previous research in the field of educational psychology, it is primarily important to avoid extraneous processing while learning with concept maps to keep free enough working memory capacities for managing the inherent task difficulty (Paas et al., 2003 ). In line with Tergan ( 2005 ), easily comprehensible concept map structures can reduce searching processes, which are detrimental to learning. In this vein, learning with concept maps can suffer from cognitive overload as well as navigational disorientation (Bleakley & Carrigan, 1994 ). Orienting on Ahuja and Webster ( 2001 ), Amadieu et al. ( 2009 ) as well as Cress and Knabel ( 2003 ), disorientation hinders learning processes in different ways: (1) The learner cannot capture how various concepts within the map are connected; (2) It is more difficult to recognize semantic relationships between the concepts, i.e., which concept is subordinate and which concept is superordinate; (3) The learner is hindered in identifying a path that will function as a guide through the map; and (4) It is sometimes tough to find already read information again. Tergan ( 2005 ) assumes that learning scenarios with “ill-structured” content required additional tools to foster learning. One approach is providing a visible hierarchical structure within the concept map (Amadieu et al., 2015 ). In line with principles of reducing extraneous processing while learning (e.g., spatial contiguity principle to prevent learning-hindering split-attention effects; Schroeder & Cenkci, 2018 ), a visible hierarchical structure within the concept map should lead to better learning performances (DeStefano & LeFevre, 2007 ; Puntambekar & Goldstein, 2007 ). Hierarchy results in a high-quality concept map and was thus expected to support learning (Cañas et al., 2015 ). For this study, an easily identifiable navigation path (adapted from Amadieu et al., 2009 ) characterizes a salient structure within the map. Therefore, a logical and comprehensible navigation through the learning material is fundamentally conducive to learning, not only in concept maps (Dias & Sousa, 1997 ).

Another possibility is the implementation of signaling (highlighting relevant information within the learning material; for a meta-analysis see Schneider et al., 2018 ) which is derived from the CLT. For example, Aguiar and Correia ( 2016 ) could show that adding colors into the concept map, in order to group similar information, reduces extraneous cognitive load. Furthermore, Schneider et al. ( 2021 ) found empirical evidence for the learning-beneficial effect of implementing organization highlighting principles in concept maps. In this vein, signaling corresponding sub-concepts within the map significantly reduced ECL perceptions. However, the simultaneous usage of these principles (e.g., combining signaling with segmentation) also had negative impacts on learning with concept maps.

To sum up, concept maps were found to have positive effects on learning (Machado & Carvalho, 2020 ; Nesbit & Adesope, 2006 ; Novak, 1990 ; Schroeder et al., 2018 ). However, empirically documented recommendations on how concept maps should be optimally designed are still rare and require further examinations (e.g., Schroeder et al., 2018 ).

The present study

This study investigated how the inherent design and complexity of concept maps can be improved in order to support cognitive processes while learning. Hereby, the effectiveness of concept maps depends to a large extent on the spatial arrangement of the individual sub-concepts, respectively the structure of the entire map. In this vein, Machado and Carvalho ( 2020 ) pointed out that students often struggle finding their way through the concept map. Consequently, it may be difficult to integrate the individual sub-concepts and their content into a coherent model.

Also, a salient structured concept map, in which related information is arranged spatially close to each other, should lead to lower ECL and disorientation perceptions. As the saliently structured concept map could promote the learner to find a meaningful reading order (Amadieu & Salmerón, 2014 ), it is assumed that learners are also more learning-efficient regarding their invested learning time. There might be learner who achieved the same score in a learning test but in a different amount of time.

To summarize, the following hypotheses were formulated:

Learners exposed to a concept map with a high salience of the map structure show …

better learning performances

lower ECL perceptions

lower perceived disorientation

higher learning efficiency

than learners exposed to a concept map with a low salience of the map structure

In line with findings concerning element interactivity (Kalyuga, 2011 ), it is assumed that each node of the map can be understood as an element. When thematically and spatially related nodes within the map are assembled to one node, this leads to a lower quantity of elements. When learners are confronted, for example, with three instead of six nodes, they might consider the whole sub-concept as a lower load. The aim is to reduce the element interactivity artificially since the amount of information to be learned remains the same. Just the presentation changes across the factor levels. In a concept map with a higher number of nodes, more separated elements must be connected and learned. Consequently, aggregating thematically related nodes should lead to better learning outcomes. Moreover, when learners are forced to learn with a lower number of nodes, the perceived ICL should decrease because of the reduced element interactivity (Sweller, 2010 ). In terms of disorientation, a lower number of nodes facilitates learning since additional integrating processes of related nodes are reduced. In a similar way, the artificial reduction lead to higher learning efficiency since less time is required to understand the learning content.

To sum up, the following hypotheses were formulated:

Learners exposed to a concept map with lower number of nodes within sub-concepts show …

lower perceived ICL

than learners exposed to a concept map with a higher number of nodes within sub-concepts.

Moreover, a mediation model is proposed under the premise that explicitly the salience of the map structure is associated with the learner's navigational disorientation (DeStefano & LeFevre, 2007 ; Puntambekar & Goldstein, 2007 ; Tergan, 2005 ). Since disorientation is negative for learning it is hypothesized that this perception leads to higher ECL ratings. Following the proposed path, extraneous processing leads to worse learning performance. For this analysis, the retention and comprehension scores were subsumed to the variable learning performance.

The effect of the salience of the map structure on learning performance is serially mediated by disorientation and extraneous cognitive load.

Design and participants

This experiment is based on a two (salience of the map structure; low vs. high) × two (number of nodes; few vs. many) between-subjects factorial design. An a-priori power analysis (using G*Power ; Faul et al., 2007 ) was conducted with a two-factorial between-subject design with two-factor levels each, a moderate effect size of f  = .25 (based on meta-analytical findings regarding concept maps and spatial contiguity; Schroeder & Cenkci, 2018 ; Schroeder et al., 2018 ), a test power of 1−β = .80 and an error probability of α = .05. This analysis recommended a minimum sample size of N  = 128. Overall, 130 students from Chemnitz University of Technology, who received either 1-h course credit or the possibility to participate in a voucher lottery, took part in this experiment. Due to technical problems, eight participants had to be excluded. The remaining 122 students (71.3% female; age: M  = 23.01; SD  = 3.04) were considered for statistical analyses. Each participant was randomly assigned to one of the four aforementioned treatment groups. Mean prior knowledge was 1.33 ( SD  = 1.19) out of 7 points what can be seen as rather low prior knowledge.

Instructional material

Two web pages were prepared for the study. The first webpage introduced the participants to the learning content with some general information about the cell and the question of how many cells in the human body exist. By clicking on the forward button, the participants were directed to the second webpage where the concept map was displayed. The concept maps used in this study were developed with the free software tool CmapTools (cf. Cañas et al., 2004 ). Hereby, the maps dealt with biological facts on the cell. More specific, the map presented components of animal and plant cells (eukaryotes) including their formation and functions. Also, prokaryotic cells were briefly stated whereby in particular, the difference between animal and plant cells was emphasized. The concept map was titled “The Cell”. All concept maps comprised of the same amount of information, only the way of presentation was varied across the experimental conditions. To avoid possible emotional design effects (Brom et al., 2018 ), the map was presented on a white background and the font color was black. Just the centrally placed title was displayed in a beige box. Based on the two experimental factors, participants randomly received one map dependent on their condition. An overview of the four concept maps used in the experiment is displayed in Fig.  1 .

Overview of the four concept maps (conditions) used in the experiment

In terms of the first independent variable, the salience of the structure of the concept map was manipulated. Specifically, a clearly arranged structure should be visible in one condition and an unclear structure in the other condition. The saliently structured concept map leads to easier navigation through the map and to a better understanding of the major and minor components and their semantic relationship. Accordingly, the structure serves as an attention guidance assistant. Lucidly presenting information makes it easier to maintain a meaningful reading order through the concept map. On the other hand, if the map has a less salient structure, it is hardly recognizable how the sub-concepts relate to each other. This is mainly favored by the fact that the individual nodes were distributed as randomly as possible across the map. As a consequence, thematically different nodes are no longer recognizable as such. The learner has to mentally structure the map himself accompanied by many search processes.

Regarding the second independent variable, the two-factor levels differed in the total number of nodes. Concept maps are characterized by the fact that for each node one idea or element is presented. In this study, in the few nodes condition, thematically related nodes (which contains information belonging together) were combined to one node (see Fig.  2 ) by summarizing corresponding nodes leading to the dissolution of individual nodes.

Extract from the concept map (left: many nodes, right: few nodes). Note . Instructional material was translated from German to English for this example

For instance, the concept “regulation of the internal cell pressure” is connected with the two sub-concepts “turgor” (linked via “is also known as”) and “stabilization of the plant” (link via “leads to”). These two sub-concepts can also be combined in one node due to their thematic proximity. By integrating any nodes that belong together, the total number of nodes could be reduced by 35% (see Table ​ Table1 1 ).

Number of nodes for sub-concept of the concept map by condition

For each measure, the reliability indicator Cronbach’s alpha (α) was calculated (Cronbach, 1951 ; Tavakol & Dennick, 2011 ) to ensure the internal consistency of the used measurements. In line with Hulin et al. ( 2001 ), an alpha-value of 0.6 or more can be considered as satisfactory.

Prior knowledge

Learners’ prior knowledge was measured because of its empirically proven influence on cognitive load perceptions and learning performances (Chen et al., 2017 ). Two different task types were used to capture this concept. First, the open-answer question “What is the difference between eukaryotic and prokaryotic cells?” was given to the participants. A list with correct answers was prepared for evaluation which was conducted by two independent raters. The inter-rater reliability (κ = .92) was almost perfect (McHugh, 2012 ). The learners could achieve a maximum of three points. For the second task, the participants were asked to assign the following cell organelles to the correct cell type in which they occur: vacuoles, mitochondria, chloroplasts, and Golgi apparatus. Accordingly, four additional points could be reached for this task, whereby a maximum of seven points was awarded in the entire prior knowledge test. Here, no inter-rater reliability was calculated since only one answer per item was correct.

Disorientation

For deeper insights on whether the learners were able to navigate through the concept map, modified items of the disorientation scale from Ahuja and Webster ( 2001 ) were used (see Table ​ Table2). 2 ). In its original version, this scale is designed to assess the effectiveness of web designs. For this experiment, seven items (α = .93) were adapted for the use of concept maps. Participants had to rate items like “The navigation between the concepts was a problem” on a 7-point scale ranging from (1) “does not apply at all” to (7) “applies completely”.

Modified Disorientation Scale (Ahuja & Webster, 2001 ) used in the experiment

These items were answered on a 7-point Likert scale ranging from 1 (“does not apply at all”) to 7 (“applies completely”)

Cognitive load

In order to evaluate the impact of the manipulated experimental conditions on learners’ cognitive processes, cognitive load was assessed with a questionnaire from Klepsch et al. ( 2017 ). In detail, the German subscales of intrinsic cognitive load (ICL; two items, α = .77, e.g. “For this task, many things needed to be kept in mind simultaneously”) and extraneous cognitive load (ECL; three items, α = .88, e.g., “During this task, it was exhausting to find the important information”) were chosen for this experiment. Each item was rated on a 7-point scale ranging from (1) “not applicable at all” to (7) “fully applicable”.

Learning performance

In order to measure the participants’ learning performance, two tests (retention and comprehension) were conducted. For retention , which can be defined as remembering (Mayer, 2014 ), 14 multiple-choice questions were created (α = .74), that questioned knowledge that was explicitly mentioned in the learning material. All questions consisted of four reply options. The number of correct answers differed among all tasks, however, at least one answer was correct. In consequence, the participants got a point if they recognized an item as correct. Besides, one point was awarded when a false item was not selected. For example, the question “What are the functions of the endoplasmic reticulum (ER)?” was given with the answer options (a) “formation of proteins”, (b) “translation of fatty acids”, (c) “signal transmission”, and (d) “storage of genetic information”. Per question, participants could receive a maximum of four points. Overall, 56 points could be maximally achieved by the participants in the retention test.

To measure comprehension , four open-format questions were formulated (α = .62). The comprehension tasks served to check to what extent learners understand the learning content and were able to apply the knowledge gained in new situations (i.e., meaningful learning; Mayer, 2002 , 2014 ). For example, two sketchy representations (an animal cell and a bacterial cell) were presented to the participants. Learners had to apply their knowledge of cell structure and components to identify the correct cell type. In another task, learners were asked to explain the possible consequences of a defective cell membrane. To be able to answer this question correctly, participants had to apply their knowledge of the functions of this cell organelle. In sum, 13 points could be reached in the comprehension test.

Instructional efficiency

In order to track how efficiently learners used their learning time, efficiency scores were calculated with the following formula (van Gog & Paas, 2008 ):

Learning time (T) and learning performance (P) were z-standardized. After calculation, the efficiency scores ranged from − 2.08 to 1.57 (higher values encode a higher learning efficiency).

Due to the Covid-19 pandemic and related social distancing interventions, the experiment was conducted online via the open-source web conferencing system BigBlueButton . Before the experiment, participants got an email with a link to the online room. The instructor informed the participants that they were to learn with a concept map. The participants were also instructed that they would have to answer questions about the learning content after the learning phase. This was to ensure that learners were aware of the goal of the investigation from the beginning. In addition, the participants were asked for informed consent, and instructed to share their screen. This screen sharing was implemented to check whether participants continuously worked with the learning material and the questionnaires and did not check other websites. No personal data was viewed or recorded. Also, participants were instructed to close all tabs except the study website. During the entire experiment, students were able to contact the experimenter either by microphone or chat message in case of problems. The experiment started with the prior knowledge test. After that, students were directed to the website with the learning material. On this website, participants could freely divide their time. Learning time was logged to analyze possible differences. The average duration was 531.34 s ( SD 339.05 s). After participants’ finished learning, the dependent variables were measured in the following order: (1) disorientation, (2) extraneous und intrinsic cognitive load, and (3) learning tests. In line with ongoing debates that multimedia learning provides rather short-term learning effects in lab experiments (Mayer, 2017 ), this study tries to examine if the learned information can still be retrieved after an intervention. For this purpose, three filler tasks with rather low cognitive load were implemented. The participants had to name the capitals of different countries, solve geometrical problems and sort confused letters into words. These filler tasks lasted about 5 to 10 min. Afterward, the learning performance was measured. At the end, the participants were asked to provide demographic information such as age, gender, and study subject. Overall, the entire experiment took between 35 and 45 min.

IBM SPSS Statistics 27 was used to analyze group differences. For data analyses, multivariate analyses of variance (MANOVAs) and univariate analyses of variance (ANOVAs) were conducted to check for group differences. Follow-up ANOVAs were only calculated if the previously performed MANOVA produced significant effects (Cramer & Bock, 1966 ). For all variance analyses, the group variables, salience of the map structure (low vs. high) and number of nodes (few vs. many) were used as independent variables. For the mediation calculation, the SPSS macro process , written by Hayes ( 2013 ), was used.

Prior knowledge was not included as a covariate since the four groups showed no significant differences ( p  = .17). Besides, there were no significant differences between the four treatment groups in terms of age ( p  = .30) and learning time ( p  = .76). Chi-squared tests revealed no differences with regard to gender ( p  = .95) and subject of study ( p  = .64). Effect sizes for group differences were only reported if they reached statistical significance. Partial eta-squared (η p 2 ) was used as effect size measure with the conventions .01 for a small, .06 for a moderate, and .14 for a large effect (Cohen, 1988 ). Correlations between all dependent variables and prior knowledge are displayed in Table ​ Table3. 3 . In addition, Table ​ Table4 4 shows the mean scores and standard deviations of all dependent variables separated into the four treatment groups.

Correlations between all dependent variables and prior knowledge

* p  < .05, ** p  < .01, *** p  < .001

Mean scores and standard deviations of all dependent variables by experimental group

The minimum and maximum of each scale are given in parentheses. Learning time is stated in seconds

Analyses of variance

To investigate possible effects of the independent variables on learning performances, a MANOVA was conducted using retention and comprehension as dependent variables. A significant main effect was found for the number of nodes, Wilk’s Λ = .94, F (2, 117) = 3.829, p  = .025, η p 2  = .06. The main effect for salience of the map structure ( p  = .381) and the interaction ( p  = .270) did not reach significance. In terms of retention, a follow-up ANOVA was not able to detect a significant effect for the number of nodes ( p  = .252). For comprehension, the effect for the number of nodes was also not significant ( p  = .155). Consequently, hypotheses 1 and 5 had to be rejected.

For the cognitive load types, a MANOVA was conducted with ICL and ECL as dependent measures. Here, no significant main effect for the salience of the map structure ( p  = .119), the number of nodes ( p  = .627) and for the interaction ( p  = .954) was found. Thus, hypotheses 2 and 6 were also rejected.

For perceived disorientation, while learning, an ANOVA was calculated. This analysis found a significant effect of the salience of the map structure; F (1, 118) = 8.938, p  = .003, η p 2  = .07. Accordingly, students in the condition with low salience of the map structure reported their disorientation while learning significantly higher than students in the condition with high salience. This result is in accordance to hypothesis 3. The effect for number of nodes ( p  = .899) as well as the interaction of both factors were not significant ( p  = .560). Accordingly, hypothesis 7 must be rejected.

To analyze learning efficiency, an ANOVA was calculated. Hereby, a significant main effect was found for the salience of the map structure; F (1, 118) = 4.208, p  = .042, η p 2  = .03. It indicates that students confronted with a low salience of structure were more efficient in terms of learning time. The main effect for the number of nodes ( p  = .956) and the interaction failed to reach significance ( p  = .100). Based on these results, the hypotheses 4 and 8 had to be rejected.

Mediation model

More complex models, such as serial mediation, can include more than one mediator (Hayes, 2013 ). For this study, two mediators (disorientation and ECL) were assumed. A serial mediation was calculated since the two constructs were measured with different questionnaires (Kane & Ashbaugh, 2017 ). In line with the statistical test assumptions of the mediation (cf. Hayes, 2018 ), it is assumed that the mediators are in a causal relationship with a temporal precedence.

The serial mediation analysis (see Fig.  3 ) showed that the salience of the map structure had a significant effect on disorientation (a 1 ; β =  − 0.53, SE  = 0.28, p  = .003). Disorientation, in turn, had a significant effect on ECL (d; β = 0.80, SE  = 0.06, p  < .001) and on learning performance (b 1 ; β =  − 0.37, SE  = 0.69, p  = .007). In addition, the effect of the salience on ECL (a 2 ; β = 0.04, SE  = 0.21, p  = .722) was not significant.

Standardized beta coefficients of the serial mediation analysis paths for the mediating effect of disorientation and extraneous cognitive load on the effect of salience of the map structure and learning performance. * p  < .05, ** p  < .01, *** p  < .001

Moreover, the path from extraneous cognitive load to learning performances was not significant as well (b 2 ; β =  − 0.12, SE  = 0.61, p  = .371). The total effect of the salience on learning performances did not reach significance (c; β =  − 0.13, SE  = 1.50, p  = .489). Interestingly, the direct effect of salience of the map structure on learning performances, controlling for disorientation and extraneous cognitive load, was significant (c’; β =  − 0.37, SE  = 1.39, p  = .031), suggesting that the inclusion of the two path variables impacts the effectiveness of the salience of the map structure in terms of learning outcomes. This serial mediation representing a causal chain between salience of the map structure, disorientation, extraneous cognitive load, and learning performances can only be partially confirmed.

General discussion

The central aim of this study was the experimental verification of two design interventions that play a significant role in the design of concept maps. For this purpose, four different versions of a concept map dealing with a biological topic were given to the participants. These maps differed in terms of the salience of structure and the number of nodes per sub-concept.

Regarding retention and comprehension, the absence of statistically significant effects of the independent variables indicates that it is irrelevant for learning whether the concept map is presented with a low or high salience of the structure or with few or many nodes. From a descriptive point of view, there is hardly any difference between the four groups in terms of the two factors. In terms of the cognitive load facets, the same conclusion can be drawn, since significant effects could not be observed. However, the assumed negative effect of perceived disorientation could be confirmed. When participants were confronted with a difficult-to-encode map (low-salience), they felt more disorientated while learning. Besides the statistical significance of this effect, the explained variance of 7%, which corresponds to a medium effect size, indicates that the map structure affects perceived disorientation notably. Furthermore, navigating between the concepts was complicated by the low salience of the map structure. The number of nodes does not influence perceived disorientation. Concerning the efficiency, learners with the rather unstructured concept map (low salience) were more efficient than learners with a high salience indicating that learners took less learning time to achieve the same performance in the test. Possibly the learning tests were “too easy” so that even short learning times resulted in good performances.

Also, the mediation model showed that a low salience of the map structure significantly affects perceived disorientation. In line with findings from hypertext research (e.g., DeStefano & LeFevre, 2007 ; Kim & Hirtle, 1995 ), rather unstructured concept maps caused feelings of disorientation. Problems mainly occur when a high level of disorientation leads to a cognitive overload while learning with concept maps. Following the causal chain, disorientation leads to significantly higher perceptions of the ECL. The high beta coefficient of .80 underlines the strength of this effect. It can be deduced that both disorientation and extraneous processing are a consequence of an inadequate structure within the concept map.

Implications

After analyzing and interpreting the results of this study, some theoretical and practical implications can be drawn.

Implications for practitioners

This study gives some practical insights into designing concept maps in educational settings. Instructional designers should place a primary emphasis on creating concept maps in a way that does not cause feelings of disorientation for the learner. It is particularly important to support learners to find a meaningful reading order through a concept map (Amadieu & Salmerón, 2014 ). If this prerequisite is met, learners will be able to construct a mental model of both the concept map inherent physical structure as well as the semantic representation (Payne & Reader, 2006 ). When learning with graphical visualization tools such as concept maps or mind maps, it should be also possible for learners with low prior knowledge to understand how the individual concepts interact.

Implications for researchers

On the theoretical side, this study gives a first impulse that disorientation can be regarded as a meaningful supplement of our current understanding of extraneous cognitive load. The current prevailing assumption is that this source of cognitive load is affected by relatively unspecific unfavorable instructional processes and design realizations. Mainly, extraneous load perceptions are recorded in experimental studies using questionnaires. Over time, several validated instruments were developed for measuring the different types of cognitive load along with the ECL (Eysink et al., 2009 ; Klepsch et al., 2017 ; Leppink et al., 2013 ). However, these measurements capture extraneous processing while learning relatively unspecific.

Just the measurement from Eysink et al. ( 2009 ) distinguishes the extraneous cognitive load into the dimensions: navigation , design of the learning task, and accessibility of information in order to address the different sources of learning-disrupting factors. Nevertheless, this instrument measures navigation with the question if working within the learning environment was rather easy or difficult. Whether the learner’s navigation impressions while learning are sufficiently captured with an unspecific single item is questionable from a psychometric view. Under the premise that navigation within the material can be seen as a fundamental prerequisite for successful learning, this factor should get more attention in future research. While empirical findings regarding the influence of the structure on concept map effectiveness are still lacking, several studies from the field of hypertext research already examined in which way structure affects learning (e.g., Dee-Lucas & Larkin, 1995 ; McDonald & Stevenson, 1998 ). Moreover, disorientation and extraneous cognitive load correlate very highly with each other. The structure in which information is organized crucially affects learning and can be changed by the instructional designer in order to prevent disorientation perceptions while learning. In this vein, the learners perceived navigational disorientation (Amadieu & Salmerón, 2014 ) could be measured when learning materials display knowledge in a certain spatially and semantic arrangement. For instance, one or more of the following items could be useful, but require factor-analytical examinations (for a beginner’s guide see Yong & Pearce, 2013 ):

• “It was difficult to get an overview of the structure of the learning material.”
• “The structure within the learning material made it difficult for me to deduce how the individual pieces of information are related”.
• “While learning I had the feeling of getting lost in the learning material.”
• “It was difficult to put the individual pieces of information together to form a big whole.”
• “The structure made it difficult to find important information quickly.”

Limitations and further directions

From a methodological point of view, it must be noted that the sample is not representative in its composition since participants were mostly female and enrolled in a media-oriented study course. A generalization to other educational settings (e.g., types of schools, school subjects, or students at a different age) is hardly possible and requires replications.

As already mentioned, creating concept maps is associated with a greater learning benefit relative to studying constructed concept maps (Schroeder et al., 2018 ). In this study, however, participants were asked to learn with prepared concept maps what needs to be considered when interpreting the results of this study. Instructing learners to follow examined design guidelines when creating concept maps on their own can help to increase their knowledge gain.

One of the main goals of this work was to reduce the element interactivity (as one component of the overall ICL) artificially by combining thematically related nodes into one node. This attempt was not successful and is intended to serve as an incentive to become more familiar with possibilities of helping learners to handle a high element interactivity. Besides, the learning material was learner-paced meaning that participants were free in their allocation of learning time. In this vein, a system-paced learning environment could have had a higher impact on the examined effects (Rey et al., 2019 ).

Besides the learner’s domain-specific prior knowledge, it is also important to consider their knowledge or ability to use the learning medium appropriately. Moreover, one can assume that prior knowledge on the use of concept maps may affect the cognitive load and therefore learning performances. When learners can rely on sufficient knowledge how to use a concept map, it may be easier for them to navigate through the learning material. Consequently, this would also have an influence on the disorientation. Future studies in the field of concept mapping should collect this variable, for example, by means of questionnaires. This would allow learners to indicate their previous experiences (i.e., prior knowledge) with this learning medium.

It must be noted that the concept maps caused high intrinsic loads since a high amount of information was presented. Above all, the condition with many nodes could create a feeling that learners need to internalize as much as possible of the nodes. To be able to accomplish this, sufficient working memory capacities are required. Since this variable was not measured in this study, it cannot be used as an explanatory factor. Further studies should measure the participants’ working memory capacity when learning materials contain memorization tasks (Wilhelm et al., 2013 ).

Biographies

is a PhD student at Chemnitz University of Technology (Professorship Psychology of Learning with Digital Media). He is interested in learning with concept maps, the design of animations and the measurement of cognitive load. He holds a master’s degree in media and instructional psychology.

is Professor for Educational Technology at the University of Zurich. His research interests include cognitive, social, affective, metacognitive and motivational processes of learning with multimedia.

is a tenure-track Professor at the University of Education Freiburg. His research interests include the influence of social processes on learning. Furthermore, he focusses on the optimization of instructional videos, as well as the promotion of cognitive activation during learning.

is a Professor of Psychology of Learning with Digital Media at Chemnitz University of Technology. His research encompasses cognitive, emotional, social, and motivational processes of learning with media.

Open Access funding enabled and organized by Projekt DEAL.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Felix Krieglstein and Sascha Schneider have contributed equally to this work.

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29 Best Mind Mapper Software for Academic Research

Academic research is hard.

Mind mapping software is the answer. With mind mapping tools, you’ll never have trouble finding what you’re looking for or organizing your thoughts again! We’ve compiled a list of the 29 best mind mapping software for academic research that will make this process easier than ever before.

Table of Contents

#1. What is Mind Mapping Software?

Half a century ago, Tony Buzan discovered that he could improve his memory by drawing images of the things he was trying to remember.

Then, add branches for each of the ideas you want to explore. As you do more research, add more branches and nodes to your map. This will help you stay organized and make sure you don’t forget any important details.

#2. How does Mind Mapping work?

The idea behind mind mapping is that if you limit your map to just one idea or concept per node, you can better retain information and keep it organized.

#3. 7 benefits of mind mapping software for Academic Research

If your research paper or dissertation is due soon, mind mapping can help you create a strong argument and organize information quickly. Here are some of the best features offered by mind map software:

A more intuitive way to review and organize information.

#4. The top 10 mind mapping software programs for academic research

Scapple – connecting the dots with drag-and-drop.

Scapple is one of the most versatile tools that I have seen. It allows you to move ANY document on your laptop to your mindmap.

Another example is that you’re not restricted to beginning your mind map with a main topic. You might, for example, begin with a little concept and work “forwards” to discover the major idea. And Scapple enables it all to happen naturally because individual nodes will only connect when you ask them to by dragging and dropping one on top of the nodes.

SimpleMind – great for mind mapping on mobile devices

Some pros of SimpleMind are that it is easy to use and can keep track of a lot of information. Some cons are that it can be challenging to add videos or links and there is no free trial. Pricing info is that SimpleMind has a one-time fee of $9.99 for the desktop app and $4.99 for the mobile app.

MindNode – great for visual thinking on ipad

Pricing: MindNode has a one-time fee of $49.99 for the Mac app and is available in the App Store for iOS devices.

Coggle – simple mind map for beginners with design

Ayoa – design for project management in mind.

Ayoa is like mind-map + WhatsApp + project management. It is a unique and innovative mind mapping and project management tool that can help you to visualize, organize, and track your projects more effectively.

InfoRapid KnowledgeBase Builder – best 3D mind mapping

Mindmeister –  great tool for brainstorming and collaboration.

It has the ability to help you work on projects, brainstorm ideas, or plan your day with its simple interface. Mindmeister can be used by individuals as well as groups of all sizes. With it, you will be able to keep track of tasks and goals without forgetting about them like other tools might do. You won’t need any expertise to use this software; it’s easy enough for anyone!

Stormboard – great for virtual collaborative and brain-storm sessions

Some pros of Stormboard are that it’s a tool for individual and group use, has a simple interface, and can be used anywhere.

Miro – best online whiteboard tool 

Miro has a one-time fee of $9.99 for the desktop app and $4.99 for the mobile app. Some pros of Miro are that it is easy to use and can keep track of a lot of information. Some cons are that it can be challenging to add videos or links.

Padlet – designed for teaching and live interactions

Some pros of using Padlet are that it is easy to use and can keep track of a lot of information. Some cons are that it can be challenging to add videos or links.

ClickUp – great for collaboration and getting things done

Pricing: ClickUp has a 14-day free trial and then plans with a $9 signup fee and $15 monthly cost.

Mindly – mobile mind mapping app with circles

Gitmind – great for free collaborative mind map maker.

GitMind is a great collaborative mind mapping software that can be used for free.

Pricing: GitMind has a 14-day free trial and then plans with a $5 signup fee and $7 monthly cost.

Mindomo – simple mind mapping app for beginners

Examples: One example of how Mindomo could be used is to map out an organizational chart to see how employees would interact with each other in order to complete certain tasks; another example is creating mind maps based on different subjects so that people can quickly find the information they need.

MindMaster/EdrawMind  – Great for Microsoft Office and management work

Some cons are that there is no free trial or version for you try before buying paid options only available.

MindManager – mind mapping tool that works with Office

Smartdraw – integrated with most work-related software.

Smartdraw is a mind map software for those who are looking for something with more options. It has a huge library of templates, Gantt Chart, and is great for management use.

Visio –  a business diagramming tool

Microsoft Visio is a versatile traditional process charting tool that can be used to create mind maps with its built-in mind mapping templates. It offers good value for the price, and some powerful features like data linking and advanced formatting. However, it can be tricky to use for beginners and doesn’t offer the collaborative features of some of the more modern mind mapping software options.

Venngage – turning mind maps into infographics

Canva – turn mind maps into great visual content .

Canva is free to use for basic features, but you can also upgrade to a paid subscription for more premium tools and options. Pros:  Wide range of templates and tools, easy to use, free for basic features. Cons: Paid subscription required for more advanced features.

Price: Free version available 

MindMup – one of the oldest mind map software

Thebrain – great for learning and visualizing thoughts and knowledge connections.

TheBrain is a unique and powerful free mind mapping software that can be used for learning and visualizing thoughts and knowledge connections.

However, there are some drawbacks; it can be slow to load large maps, and doesn’t offer any collaborative editing features.

Cons: Can be slow to load large maps No collaborative editing features

FreeMind – popular free mind mapping software

However, there are some drawbacks; it’s quite limited when compared with the top paid options, and there have been complaints about its slow performance.

Pros: Open-source tool Intuitive interface Customizable features Wide range of features for creating mind maps

Drakonhub – nostalgia looking mind mapper

It also offers some great features like color coding which allows you to categorize sections in order to bring out key points or items that need attention; drag-and-drop sorting within nodes; adding icons, drawings, photos etc.; exporting maps as PDFs (or JPGs); and saving maps to Google Drive, OneDrive etc.

Bubbl – Open Source OG map mapping tool

We all know that brainstorming can be a difficult process to navigate, and mapping your thoughts is no easy feat either. But what if there was an app for making these tasks easier?

Xmind.net – one of the oldest free mind mapper software

Xmind.net is a free mind mapping tool that has been around for over a decade and it’s still one of the most popular tools out there. It offers an intuitive interface that is customizable and easy to use. Additionally, it offers a wide range of features for creating mind maps such as text formatting; exporting in various formats; importing from other mind mapping tools etc.

Wisemapping – Open Source; Free; No-login 

Wisemapping’s interface allows the user to make maps in a variety of formats, like FreeMind or XMIND. It offers many features for customization and comes with some pre-installed templates. There are some drawbacks; it can be slow to load larger maps, and doesn’t offer any collaborative editing features.

Pros: Allows for collaboration Open Source Easy navigation Customizable maps Pre-installed templates

Cons: Slow loading time No collaborative editing features

Freeplane – Open Source – Private Maps

If you’re looking for a powerful, open-source free mind map software that is simple to use and doesn’t require an internet connection, then Freeplane is the perfect tool for you. It offers a wide range of features for customizing your maps, and comes with some pre-installed templates that you can use to get started quickly. However, it can be slow to load larger maps, and doesn’t offer any collaborative editing features.

Pros: Powerful and open source software Simple to use Doesn’t require an internet connection Comes with pre-installed templates. Powerful free form diagrams.

Compedium – Window 95 like Mind Mapper

#5. how to choose the best mind mapping software for you.

Mind maps are supposed to help you. So, don’t let it become a burden to you. In my experience with the new tool, you want to do it when you don’t have a big deadline. 

#6. How to use mind mapping software – 23 ideas for top academic performers

#7. conclusion.

Mind map is a perfect tool to use when you need to put your thoughts together quickly and easily in one place so that you can simply click around the branches and review the whole piece of information without having to scroll all over again.

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• Systematic mapping review of player safety, sport science and clinical care in lacrosse
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• http://orcid.org/0000-0002-4901-8709 Kyle Wallace 1 ,
• Samantha E. Scarneo-Miller 2 ,
• Jennifer Monnin 3 ,
• Andrew E Lincoln 4 ,
• Omar Hraky 5 ,
• Griffith Gosnell 6 ,
• Suin Jeong 6 ,
• Wilson Skinner 6 ,
• Eliana Schaefer 7 ,
• Dharmi K Desai 8 ,
• http://orcid.org/0000-0002-8775-2971 Shane V Caswell 8 , 9
• 1 Department of Orthopaedic Surgery , The University of North Carolina at Chapel Hill , Chapel Hill , North Carolina , USA
• 2 Division of Athletic Training , West Virginia University , Morgantown , West Virginia , USA
• 3 Health Sciences Library , West Virginia University , Morgantown , West Virginia , USA
• 4 Special Olympics International , Washington , District of Columbia , USA
• 5 University of Maryland at College Park , College Park , Maryland , USA
• 6 Georgetown University Medical Center , Georgetown University School of Medicine , Washington , District of Columbia , USA
• 7 Department of Orthopaedic Surgery , MedStar Georgetown University Hospital , Washington , District of Columbia , USA
• 8 George Mason University , Fairfax , Virginia , USA
• 9 Sports Medicine Assessment, Research & Testing (SMART) Laboratory , George Mason University , Manassas , Virginia , USA
• Correspondence to Kyle Wallace; kylewallace1020{at}gmail.com

Objective The objective is to comprehensively classify the types, topics and populations represented in the published lacrosse literature.

Design Mapping review. Protocol registration at Open Science Framework ( https://osf.io/kz4e6 ).

Data sources 10 electronic databases were searched from inception to 31 March 2023.

Eligibility criteria Peer-reviewed studies in English that included lacrosse were eligible. Publications without participant demographic or lacrosse-specific data were excluded.

Results We identified 498 articles pertaining to lacrosse, with 270 (54.2%) focused on player safety, 128 (25.7%) on sport science and 74 (14.9%) on clinical care. Musculoskeletal injury was the focus of 179 studies (35.9%), and the most common study design was cross-sectional (n=162, 32.5%). Most (n=423, 84.9%) originated in the USA. Over half (n=254, 51.0%) were published since 2017. 216 articles (43.4%) included female and male athletes, while 112 (22.5%) and 142 (28.5%) focused solely on female and male athletes, respectively. Collegiate athletes were the most frequent study population (n=277, 55.6%), and traditional field lacrosse was the focus of 298 (59.8%) articles. We observed that 77.1% (27/35) of quasiexperimental, 91.3% (21/23) of randomised controlled trials and 62.1% (18/29) of systematic reviews had a high or moderate risk of bias.

Conclusion The vast majority of lacrosse research originates from the USA, is in collegiate athletes, with a focus on player safety, and has a high risk of bias. With the sport’s inclusion in the 2028 Olympics and growing global participation, higher quality research studies that are more inclusive and adaptable to diverse athletic groups and changing gameplay parameters are needed.

Data availability statement

Data are available in a public, open access repository. Appendices for this manuscript are available on Open Science Framework ( https://doi.org/10.17605/OSF.IO/KNS3E ) and are linked to our original a priori protocol. All included articles in this mapping review, with data coding, are available online (appendix 1). Unfilled JBI checklists are available online (appendix 2). Completed JBI checklists for all included articles are available online (appendix 3).

https://doi.org/10.1136/bjsports-2024-108298

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Contributors All authors were an integral part of planning, collecting data, designing, writing and reviewing this manuscript. KW, primary author, is the corresponding author and guarantor.

Funding Funding for this project was provided by USA Lacrosse and MedStar Health.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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• Artificial Intelligence

Exclusive: New Research Finds Stark Global Divide in Ownership of Powerful AI Chips

W hen we think of the “cloud,” we often imagine data floating invisibly in the ether. But the reality is far more tangible: the cloud is located in huge buildings called data centers, filled with powerful, energy-hungry computer chips. Those chips, particularly graphics processing units (GPUs), have become a critical piece of infrastructure for the world of AI, as they are required to build and run powerful chatbots like ChatGPT.

As the number of things you can do with AI grows, so does the geopolitical importance of high-end chips—and where they are located in the world. The U.S. and China are competing to amass stockpiles, with Washington enacting sanctions aimed at preventing Beijing from buying the most cutting-edge varieties. But despite the stakes, there is a surprising lack of public data on where exactly the world’s AI chips are located.

A new peer-reviewed paper , shared exclusively with TIME ahead of its publication, aims to fill that gap. “We set out to find: Where is AI?” says Vili Lehdonvirta, the lead author of the paper and a professor at Oxford University’s Internet Institute. Their findings were stark: GPUs are highly concentrated in only 30 countries in the world, with the U.S. and China far out ahead. Much of the world lies in what the authors call “Compute Deserts:” areas where there are no GPUs for hire at all.

The finding has significant implications not only for the next generation of geopolitical competition, but for AI governance—or, which governments have the power to regulate how AI is built and deployed. “If the actual infrastructure that runs the AI, or on which the AI is trained, is on your territory, then you can enforce compliance,” says Lehdonvirta, who is also a professor of technology policy at Aalto University. Countries without jurisdiction over AI infrastructure have fewer legislative choices, he argues, leaving them subjected to a world shaped by others. “This has implications for which countries shape AI development as well as norms around what is good, safe, and beneficial AI,” says Boxi Wu, one of the paper’s authors.

The paper maps the physical locations of “public cloud GPU compute”—essentially, GPU clusters that are accessible for hire via the cloud businesses of major tech companies. But the research has some big limitations: it doesn’t count GPUs that are held by governments, for example, or in the private hands of tech companies for their use alone. And it doesn’t factor in non-GPU varieties of chips that are increasingly being used to train and run advanced AI. Lastly, it doesn't count individual chips, but rather the number of compute “regions” (or groups of data centers containing those chips) that cloud businesses make available in each country.

Read More: How ‘Friendshoring’ Made Southeast Asia Pivotal to the AI Revolution

That’s not for want of trying. “GPU quantities and especially how they are distributed across [cloud] providers’ regions,” the paper notes, “are treated as highly confidential information.” Even with the paper’s limitations, its authors argue, the research is the closest up-to-date public estimate of where in the world the most advanced AI chips are located—and a good proxy for the elusive bigger picture.

The paper finds that the U.S. and China have by far the most public GPU clusters in the world. China leads the U.S. on the number of GPU-enabled regions overall, however the most advanced GPUs are highly concentrated in the United States. The U.S. has eight “regions” where H100 GPUs—the kind that are the subject of U.S. government sanctions on China—are available to hire. China has none. This does not mean that China has no H100s; it only means that cloud companies say they do not have any H100 GPUs located in China. There is a burgeoning black market in China for the restricted chips, the New York Times reported in August, citing intelligence officials and vendors who said that many millions of dollars worth of chips had been smuggled into China despite the sanctions.

The paper’s authors argue that the world can be divided into three categories: “Compute North,” where the most advanced chips are located; the “Compute South,” which has some older chips suited for running, but not training, AI systems; and “Compute Deserts,” where no chips are available for hire at all. The terms—which overlap to an extent with the fuzzy “Global North” and “Global South” concepts used by some development economists—are just an analogy intended to draw attention to the “global divisions” in AI compute, Lehdonvirta says. 

The risk of chips being so concentrated in rich economies, says Wu, is that countries in the global south may become reliant on AIs developed in the global north without having a say in how they work. 

It “mirrors existing patterns of global inequalities across the so-called Global North and South,” Wu says, and threatens to “entrench the economic, political and technological power of Compute North countries, with implications for Compute South countries’ agency in shaping AI research and development.”

More Must-Reads from TIME

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• What Makes a Friendship Last Forever?
• How to Read Political Polls Like a Pro
• Long COVID Looks Different in Kids
• What a $129 Frying Pan Says About America’s Eating Habits
• How ‘Friendshoring’ Made Southeast Asia Pivotal to the AI Revolution
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Write to Billy Perrigo at [email protected]

• Biological and Environmental Research
• BER Highlights
• Biological and Environmental Research Advisory Committee (BERAC)

The Science

In most plants, fungi are found in close association (symbiosis) with their roots. These fungi, called mycorrhizae, help plants obtain water and other nutrients. Meanwhile, plants provide the fungi with carbon nutrients generated through photosynthesis. This symbiosis occurs in microscopic structures called arbuscules that help transfer nutrients between the plants and the fungi. To better understand gene expression—how genes tell cells what to do—in plant/mycorrhizae symbioses, researchers analyzed roots of a model plant colonized by fungi. They used a combination of advanced techniques to measure gene activity in tens of thousands of individual cells and to visualize gene expression in two-dimensional sections of roots. The microscopic resolution of the analysis allowed the researchers to generate a spatial map of gene expression in both the root and the fungal cells.

Symbioses between arbuscular mycorrhizae and plants occur in most ecosystems. These symbioses are important for agriculture, as the fungi provide critical nutrients to the plants. However, this interaction is restricted to a few root cells, making it difficult to study. This study’s spatial and single-cell examination of plant-fungal interactions sheds new light on this process. Understanding both sides of this symbiosis at the molecular level may enable researchers to make targeted improvements to the way plants and mycorrhizae interact. This could be applied to bioenergy crops to increase their productivity and their ability to store carbon .

The symbiotic interaction of plants with arbuscular mycorrhizal (AM) fungi is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant–fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions.

Researchers at the Joint Genome Institute (JGI), a Department of Energy (DOE) user facility, and the DOE Joint Bioenergy Institute used single-nucleus and spatial RNA sequencing to explore both Medicago truncatula and Rhizophagus irregularis transcriptomes in AM symbiosis at cellular and spatial resolution. Integrated, spatially registered single-cell maps revealed infected and uninfected plant root cell types. The researchers observed that cortex cells exhibit distinct transcriptome profiles during different stages of colonization by AM fungi. This indicates dynamic interplay between both organisms during establishment of the cellular interface enabling successful symbiosis. This study provides insight into a symbiotic relationship of major agricultural and environmental importance and demonstrates a paradigm combining single-cell and spatial transcriptomics for the analysis of complex organismal interactions.

Benjamin Cole Joint Genome Institute [email protected]  

This study was performed at the Department of Energy’s Joint BioEnergy Institute and Joint Genome Institute and was supported by the DOE Office of Science, Biological and Environmental Research Program. This study was also supported by a Laboratory Directed Research and Development award at Lawrence Berkeley National Laboratory and a DOE Early Career Research Program. Two of the researchers were funded by the Novo Nordisk Foundation.

Publications

Serrano, K., et al. , Spatial co-transcriptomics reveals discrete stages of the arbuscular mycorrhizal symbiosis . Nature Plants 10 , 673–688 (2024). [DOI: 10.1038/s41477-024-01666-3]

Related Links

JGI Press Release: An Inside Look at How Plants and Mycorrhizal Fungi Cooperate

JGI Genome Insider Podcast: Better Crops With a Pointillist Approach to Plant Genomics

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https://www.nist.gov/news-events/news/2024/08/us-ai-safety-institute-signs-agreements-regarding-ai-safety-research

U.S. AI Safety Institute Signs Agreements Regarding AI Safety Research, Testing and Evaluation With Anthropic and OpenAI

These first-of-their-kind agreements between the u.s. government and industry will help advance safe and trustworthy ai innovation for all..

GAITHERSBURG, Md. — Today, the U.S. Artificial Intelligence Safety Institute at the U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) announced agreements that enable formal collaboration on AI safety research, testing and evaluation with both Anthropic and OpenAI.

Each company’s Memorandum of Understanding establishes the framework for the U.S. AI Safety Institute to receive access to major new models from each company prior to and following their public release. The agreements will enable collaborative research on how to evaluate capabilities and safety risks, as well as methods to mitigate those risks. 

“Safety is essential to fueling breakthrough technological innovation. With these agreements in place, we look forward to beginning our technical collaborations with Anthropic and OpenAI to advance the science of AI safety,” said Elizabeth Kelly, director of the U.S. AI Safety Institute. “These agreements are just the start, but they are an important milestone as we work to help responsibly steward the future of AI.”

Additionally, the U.S. AI Safety Institute plans to provide feedback to Anthropic and OpenAI on potential safety improvements to their models, in close collaboration with its partners at the U.K. AI Safety Institute. 

The U.S. AI Safety Institute builds on NIST’s more than 120-year legacy of advancing measurement science, technology, standards and related tools. Evaluations under these agreements will further NIST’s work on AI by facilitating deep collaboration and exploratory research on advanced AI systems across a range of risk areas.

Evaluations conducted pursuant to these agreements will help advance the safe, secure and trustworthy development and use of AI by building on the Biden-Harris administration’s Executive Order on AI and the voluntary commitments made to the administration by leading AI model developers.

About the U.S. AI Safety Institute

The U.S. AI Safety Institute , located within the Department of Commerce at the National Institute of Standards and Technology (NIST), was established following the Biden-Harris administration’s 2023 Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence to advance the science of AI safety and address the risks posed by advanced AI systems. It is tasked with developing the testing, evaluations and guidelines that will help accelerate safe AI innovation here in the United States and around the world. 

• Systematic Review
• Open access
• Published: 30 August 2024

A scoping review of stroke services within the Philippines

• Angela Logan 1 , 2 ,
• Lorraine Faeldon 3 ,
• Bridie Kent 1 , 4 ,
• Aira Ong 1 &
• Jonathan Marsden 1  

BMC Health Services Research volume  24 , Article number:  1006 ( 2024 ) Cite this article

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Stroke is a leading cause of mortality and disability. In higher-income countries, mortality and disability have been reduced with advances in stroke care and early access to rehabilitation services. However, access to such services and the subsequent impact on stroke outcomes in the Philippines, which is a lower- and middle-income countries (LMIC), is unclear. Understanding gaps in service delivery and underpinning research from acute to chronic stages post-stroke will allow future targeting of resources.

This scoping review aimed to map available literature on stroke services in the Philippines, based on Arksey and O’Malley’s five-stage-process.

Summary of review

A targeted strategy was used to search relevant databases (Focused: MEDLINE (ovid), EMBASE (ovid), Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO (ebsco); broad-based: Scopus; review-based: Cochrane Library, International Prospective Register of Systematic Reviews (PROSPERO), JBI (formerly Joanna Briggs Institute) as well as grey literature (Open Grey, Google scholar). The searches were conducted between 12/2022-01/2023 and repeated 12/2023. Literature describing adults with stroke in the Philippines and stroke services that aimed to maximize well-being, participation and function were searched. Studies were selected if they included one or more of: (a) patient numbers and stroke characteristics (b) staff numbers, qualifications and role (c) service resources (e.g., access to a rehabilitation unit) (d) cost of services and methods of payment) (e) content of stroke care (f) duration of stroke care/rehabilitation and interventions undertaken (g) outcome measures used in clinical practice.

A total of 70 papers were included. Articles were assessed, data extracted and classified according to structure, process, or outcome related information. Advances in stroke services, including stroke ready hospitals providing early access to acute care such as thrombectomy and thrombolysis and early referral to rehabilitation coupled with rehabilitation guidelines have been developed. Gaps exist in stroke services structure (e.g., low number of neurologists and neuroimaging, lack of stroke protocols and pathways, inequity of stroke care across urban and rural locations), processes (e.g., delayed arrival to hospital, lack of stroke training among health workers, low awareness of stroke among public and non-stroke care workers, inequitable access to rehabilitation both hospital and community) and outcomes (e.g., low government insurance coverage resulting in high out-of-pocket expenses, limited data on caregiver burden, absence of unified national stroke registry to determine prevalence, incidence and burden of stroke). Potential solutions such as increasing stroke knowledge and awareness, use of mobile stroke units, TeleMedicine, TeleRehab, improving access to rehabilitation, upgrading PhilHealth and a unified national long-term stroke registry representing the real situation across urban and rural were identified.

This scoping review describes the existing evidence-base relating to structure, processes and outcomes of stroke services for adults within the Philippines. Developments in stroke services have been identified however, a wide gap exists between the availability of stroke services and the high burden of stroke in the Philippines. Strategies are critical to address the identified gaps as a precursor to improving stroke outcomes and reducing burden. Potential solutions identified within the review will require healthcare government and policymakers to focus on stroke awareness programs, primary and secondary stroke prevention, establishing and monitoring of stroke protocols and pathways, sustainable national stroke registry, and improve access to and availability of rehabilitation both hospital and community.

What is already known?

Stroke services in the Philippines are inequitable, for example, urban versus rural due to the geography of the Philippines, location of acute stroke ready hospitals and stroke rehabilitation units, limited transport options, and low government healthcare insurance coverage resulting in high out-of-pocket costs for stroke survivors and their families.

What are the new findings?

The Philippines have a higher incidence of stroke in younger adults than other LMICs, which impacts the available workforce and the country’s economy. There is a lack of data on community stroke rehabilitation provision, the content and intensity of stroke rehabilitation being delivered and the role and knowledge/skills of those delivering stroke rehabilitation, unmet needs of stroke survivors and caregiver burden and strain,

What do the new findings imply?

A wide gap exists between the availability of stroke services and the high burden of stroke. The impact of this is unclear due to the lack of a compulsory national stroke registry as well as published data on community or home-based stroke services that are not captured/published.

What does this review offer?

This review provides a broad overview of existing evidence-base of stroke services in the Philippines. It provides a catalyst for a) healthcare government to address stroke inequities and burden; b) development of future evidence-based interventions such as community-based rehabilitation; c) task-shifting e.g., training non-neurologists, barangay workers and caregivers; d) use of digital technologies and innovations e.g., stroke TeleRehab, TeleMedicine, mobile stroke units.

Peer Review reports

Introduction

In the Philippines, stroke is the second leading cause of death, with a prevalence of 0·9% equating to 87,402 deaths per annum [ 1 , 2 ]. Approximately 500,000 Filipinos will be affected by stroke, with an estimated US$350 million to $1·2 billion needed to meet the cost of medical care [ 1 ]. As healthcare is largely private, the cost is borne out-of-pocket by patients and their families. This provides a major obstacle for the lower socio-demographic groups in the country.

Research on implementation of locally and regionally adapted stroke-services and cost-effective secondary prevention programs in the Philippines have been cited as priorities [ 3 , 4 ]. Prior to developing, implementing, and evaluating future context-specific acute stroke management services and community-based models of rehabilitation, it was important to map out the available literature on stroke services and characteristics of stroke in the Philippines.

The scoping review followed a predefined protocol, established methodology [ 5 ] and is reported according to the Preferred Reporting Items for Systematic Review and Meta-Analyses Extension for Scoping Reviews Guidelines (PRISMA-ScR) [ 6 , 7 ]. Healthcare quality will be described according to the following three aspects: structures, processes, and outcomes following the Donabedian model [ 8 , 9 ].The review is based on Arksey and O'Malley’s five stages framework [ 5 ].

Stage 1: The research question:

What stroke services are available for adults within the Philippines? The objective was to systematically scope the literature to describe the availability, structure, processes, and outcome of stroke services for adults within the Philippines.

Stage 2: Identifying relevant studies:

The following databases were searched. Focused: MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO; broad-based: Scopus; review-based: Cochrane Library, Prospero, JBI (formerly Joanna Briggs Institute); Grey literature: Herdin, North Grey, Grey matters, MedRxiv, NIHR health technology assessment, Department of Health Philippines, The Kings Fund, Ethos, Carrot2. Additionally, reference lists of full text included studies were searched.

The targeted search strategy, developed in consultation with an information scientist, was adapted for each database (see supplemental data). Search terms were peer reviewed using the PRESS (Peer Review of Electronic Search Strategies) checklist [ 10 ].

The key search concepts from the Population, Concept and Context (PCC) framework were ≥ 18 years with a stroke living in the Philippines ( population ), stroke services aiming to maximize well-being, participation and function following a stroke ( concept ) and stroke services from acute to chronic including those involving healthcare professionals, non-healthcare related personnel or family or friends ( context ). Search tools such as medical subject headings (MESH) and truncation to narrow or expand searches were used. Single and combined search terms were included (see supplemental data). The search was initially conducted over two weeks in December 2022 and re-run in December 2023.

Studies were selected if they described stroke care in the Philippines in terms of one or more of the following: (a) patient numbers and stroke characteristics (b) staff numbers, qualifications and role (c) service resources (e.g., number of beds/access to a rehabilitation unit, equipment used) (d) cost of services and methods of payment (UHC, Insurance, private) (e) content of stroke care (f) duration of stroke care (hours of personnel contact e.g., Therapy hours per day); interventions undertaken (g) outcome measures used in clinical practice.

Additional criteria:

Context: all environments (home, hospital, outpatients, clinic, academic institute).

Date limits: published between 2002 onwards. This is based on the Philippines Community Rehabilitation Guidelines published in 2009 that would suggest that papers earlier than 2002 may not reflect current practice [ 11 ].

Qualitative and quantitative studies including grey literature.

Language: reported in English or Filipino only.

Publication status: no limit because the level of rigor was not assessed.

Type of study: no limit which included conference abstracts, as the level of rigor was not assessed.

Studies were excluded if they were in non-stroke populations or the full text article could not be obtained. Conference abstracts were excluded if there were insufficient data about methods and results.

Searches of databases were performed by one researcher (JM) and searches of grey literature were performed by one researcher (AO). All retrieved articles were uploaded into Endnote X9 software™, and duplicates identified and removed before transferring them to Rayyan [ 12 ] for screening.

Stage 3: study selection

The title and abstract were selected using eligibility criteria. Two pairs of researchers independently screened abstracts and titles;(Databases: JM and AL and grey literature by AO and LF). Where a discrepancy existed for title and abstract screening, the study was automatically included for full text review and discussed among reviewers.

Two reviewers (JM and AL) undertook full-text screening of the selected studies. Discrepancies were resolved through consensus discussions without the need for a third reviewer. There were no discrepancies that required a third reviewer. Reason for exclusion were documented according to pre-determined eligibility criteria. References of included full text articles were screened by each reviewer independently and identified articles were subjected to the same screening process as per the PRISMA-ScR checklist (Fig.  1 ).

PRISMA-ScR flow diagram

Stage 4: Charting the data

Two reviewers independently extracted the data using a piloted customized and standardized data extraction form including (1) Structure: financial (e.g., costs, insurance, government funding), resources (structure and number of stroke facilities, staff (number, profession/specialism, qualifications etc.), stroke characteristics (2) Process: duration of care, content of stroke care within acute, secondary care, community, outcome measures used; (3) Outcome: survival, function, patient satisfaction, cost (admission and interventions), and (4) year of publication, geographical location (including if Philippines only or multiple international locations) and type of evidence (e.g., policy, review, observational, experimental, clinical guidelines). Critical appraisal of included studies was not undertaken because the purpose of the review was to map available evidence on stroke services available within the Philippines.

Stage 5: Collating, summarising and reporting the results

The search identified 351 records from databases and registers. A total of 70 records are included and reasons for non-inclusion are summarized in Fig.  1 .

Study descriptors

The characteristics of included studies are shown in Supplementary Material Table 1. Of the 70 included studies, 36 were observational with most being based on a retrospective review of case notes ( n  = 31), two were audits, eight were surveys or questionnaires, four were consensus opinion and/or guideline development, three were randomized controlled trial (RCT) or feasibility RCT, 1 was a systematic review, two were policy and guidelines, 11 were narrative reviews or opinion pieces, two were case series or reports and one was an experimental study.

Of the 70 studies, 32 (45.7%) were based in a single tertiary hospital site. There were only three papers based in the community (4.3%). Papers that were opinion pieces or reviews were classified as having a national focus. Of the 22 papers classified as having a national focus, 10 (45.5%) were narrative reviews/ opinion pieces (Table 1 ).

The primary focus of the research studies (excluding the 11 narrative reviews and 2 policy documents) were classified as describing structure ( n  = 8, 14%); process ( n  = 21,36.8%) or outcomes ( n  = 29, 49.2%). The structure of acute care was described in seven studies out of eight studies ( n  = 7/8 87.5%) whilst neurosurgery structures were described in one out of eight studies (12.5%). Acute care processes were described in 11 out of 21 studies ( n  = 11/21 52.3%) whilst rehabilitation processes were described in six out of 21 studies (28.6%), with three out of 21 studies primarily describing outcome measurement (14.3%). The primary focus of the outcomes were stroke characteristics (25 out of 28 papers, 89.2%) in terms of number of stroke (prevalence), mortality or severity of stroke. Measures of stroke quality of life were not reported. Healthcare professional knowledge was described in two studies ( n  = 2/28 7.1%) whilst risk factors for stroke were described in one study ( n  = 1/28, 3.6%). Carer burden was described in one study ( n  = 1/28, 3.6%).

A summary of the findings is presented in Table 2 .

This scoping review describes the available literature on stroke services within the Philippines across the lifespan of an adult (> 18 years) with a stroke. The review has identified gaps in information about structures, processes and outcomes as well as deficits in provision of stroke services and processes as recommended by WHO. These included a low number of specialist clinicians including neurologists, neuro-radiographers and neurosurgeons. The high prevalence of stroke suggests attention and resources need to focus on primary and secondary prevention. Awareness of stroke is low, especially in terms of what a stroke is, the signs/symptoms and how to minimize risk of stroke [ 25 ]. Barriers exist, such as lack of healthcare resources, maldistribution of health facilities, inadequate training on stroke treatment among health care workers, poor stroke awareness, insufficient government support and limited health insurance coverage [ 22 ].

The scoping review also highlighted areas where further work is needed, for example, descriptions and research into the frequency, intensity, and content of rehabilitation services especially in the community setting and the outcome measures used to monitor recovery and impairment. PARM published stroke rehabilitation clinical practice guidelines in 2012, which incorporated an innovative approach to contextualize Western clinical practice guidelines for stroke care to the Philippines [ 42 ]. Unfortunately, availability and equitable access to evidence-based rehabilitation for people with stroke in the Philippines pose significant challenges because of multiple factors impacting the country (e.g., geographical, social, personal, environmental, educational, economic, workforce) [ 25 , 40 , 43 ].

The number of stroke survivors with disability has not been reported previously, thus, the extent and burden of stroke from acute to chronic is unknown. The recent introduction of a national stroke registry across public and private facilities may provide some of this data [ 82 ]. The project started in 2021 and captures data on people hospitalized for transient ischemic attack or stroke in the Philippines. National stroke registries have been identified as a pragmatic solution to reduce the global burden of stroke [ 83 ] through surveillance of incidence, prevalence, and outcomes (e.g., death, disability) of, and quality of care for, stroke, and prevalence of risk factors. For the Philippine government to know the full impact and burden of stroke nationally, identify areas for improvement and make meaningful changes for the benefit of Filipinos, the registry would need to be compulsory for all public and private facilities and include out of hospital data. This will require information technology, trained workforces for data capture, monitoring and sharing, as well as governance and funding [ 83 ].

This scoping review has generated a better understanding of the published evidence focusing on availability of stroke services in the Philippines, as well as the existing gaps through the lens of Donabedian’s Structure , Process and Outcome framework. The findings have helped to inform a wider investigation of current stroke service utilization conducted using survey and interview methods with stroke survivors, carers and key stakeholders in the Philippines, and drive forward local, regional and national policy and service changes.

Conclusions

This scoping review describes the existing evidence-based relating to structure, processes and outcomes of stroke services for adults within the Philippines. The review revealed limited information in certain areas, such as the impact of stroke on functional ability, participation in everyday life, and quality of life; the content and intensity of rehabilitation both in the hospital or community setting; and the outcome measures used to evaluate clinical practice. Developments in stroke services have been identified however, a wide gap exists between the availability of stroke services and the high burden of stroke in the Philippines. Strategies are critical to address the identified gaps as a precursor to improving stroke outcomes and reducing burden. Potential solutions identified within the review will require a comprehensive approach from healthcare policymakers to focus on stroke awareness programs, primary and secondary prevention, establishing and monitoring of stroke protocols and pathways, implementation of a compulsory national stroke registry, use of TeleRehab, TeleMedicine and mobile stroke units and improve access to and availability of both hospital- and community-based stroke rehabilitation. Furthermore, changes in PhilHealth coverage and universal credit to minimize catastrophic out-of-pocket costs.

Limitations

Although a comprehensive search was undertaken, data were taken from a limited number of located published studies on stroke in the Philippines. This, together with data from databases and grey literature, may not reflect the current state of stroke services in the country.

Availability of data and materials

Not applicable.

Data availability

No datasets were generated or analysed during the current study.

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Acknowledgements

We acknowledge the TULAY collaborators: Dr Roy Francis Navea, Dr Myrna Estrada, Dr Elda Grace Anota, Dr Maria Mercedes Barba, Dr June Ann De Vera, Dr Maria Elena Tan, Dr Sarah Buckingham and Professor Fiona Jones. We are grateful to Lance de Jesus and Dr Annah Teves, Research Assistants on the TULAY project, for their contribution to some of the data extraction.

This research was funded by the NIHR Global Health Policy and Systems Research Programme (Award ID: NIHR150244) in association with UK aid from the UK Government to support global health research. The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the UK’s Department of Health and Social Care.

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Logan, A., Faeldon, L., Kent, B. et al. A scoping review of stroke services within the Philippines. BMC Health Serv Res 24 , 1006 (2024). https://doi.org/10.1186/s12913-024-11334-z

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