why is critical thinking important in computer science

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How Computer Engineering Helps You Think Creatively

But in reality, learning the basics of computer science can help you think more critically and with more novel inspiration, ultimately helping you in other areas of your life.

Thinking of a career in computing? Our “Careers in Computing” blog will get you there

Apply Creative Problem Solving to Other Areas

Let’s start by explaining why the creative problem-solving skills you’ll learn in computer science can help you in everyday life:

• Novel solutions and new products. Being familiar with creating and polishing hardware and/or software can help you come up with ingenious solutions for your everyday life. You’re used to thinking about problems as solvable challenges, so you naturally come up with ways to address them. This applies to areas beyond computer science as well; for example, one former computer engineer used his creativity to engineer a pillow that reduces pressure on your face while sleeping .
• Lateral thinking and breaking patterns. Writing code and creating applications from scratch also incentivizes you to think laterally and break the patterns you’d otherwise fall into. Traditional lines of thinking just won’t work for some problems, so you’ll be forced to think in new, creative ways. That allows you to experiment with new approaches and keep trying until you find something that works.
• Seeing problems from other perspectives. As a computer engineer, you’ll be forced to see problems from other perspectives, whether you want to or not. That might mean reviewing code that someone else wrote, getting feedback from a client who has no familiarity with engineering, or imagining how an application might look to a user who’s never seen it before. In any case, you’ll quickly learn how to broaden your perspective, which means you’ll see problems in an entirely new light.

How Computer Engineering Improves Your Abilities

So how exactly does computer engineering improve your creative abilities in this way?

• Generating new ideas. You have to be creative if you’re going to generate new ideas . In some roles, you’ll be responsible for coming up with the ideas yourself—either designing your own apps for circulation, or making direct recommendations to your clients. In other scenarios, you’ll be responsible for coming up with novel ways to include a feature that might otherwise be impossible. In any case, you’ll be forced to come up with ideas constantly, which gets easier the more you practice it.
• Reviewing code. You’ll also be responsible for reviewing code—including code that you wrote and code that other people wrote. Reviewing your own code forces you to see it from an outsider’s perspective, and reviewing the code of others gives you insight into how they think. That diverse experience lends itself to imagining scenarios from different perspectives.
• Fixing bugs. Finding and fixing bugs is an important part of the job, and it’s one of the most creatively enlightening. To resolve the problem, you first have to understand why it’s happening. If you’ve written the code yourself, it’s easy to think the program will run flawlessly, so you’ll have to challenge yourself to start looking for the root cause of the problem. Sometimes, tinkering with the code will only result in more problems, which forces you to go back to the drawing board with a new angle of approach. It’s an ideal problem-solving exercise, and one you’ll have to undergo many times.
• Aesthetics and approachability. Finally, you’ll need to think about the aesthetics and approachability of what you’re creating. Your code might be perfectly polished on the backend, but if users have a hard time understanding the sequence of actions to follow to get a product to do what they want, you may need to rebuild it.

Latest career advice from our Career Round Table: With Demand for Data Scientists at an All-Time High, Top Experts Offer Sound Career Advice

Is Computer Science Worth Learning?

If you’re not already experienced in a field related to computer science, you might feel intimidated at the idea of getting involved in the subject. After all, people spend years, if not decades studying computer science to become professionals.

The good news is, you don’t need decades of experience to see the creative problem-solving benefits of the craft. Learning the basics of a programming language, or even familiarizing yourself with the type of logic necessary to code, can be beneficial to you in your daily life. Take a few hours and flesh out your skills; you’ll be glad you did.

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How critical thinking can help you learn to code

Experienced programmers frequently say that being able to problem-solve effectively is one of the most important skills they use in their work. In programming as in life, problems don’t usually have magical solutions. Solving a coding problem often means looking at the problem from multiple perspectives, breaking it down into its constituent parts, and then considering (and maybe trying) several approaches to addressing it.

In short, being a good problem-solver requires critical thinking .

Today, we’ll discuss what critical thinking is, why it’s important, and how it can make you a better programmer.

We’ll cover :

What is critical thinking?

Why is critical thinking important in programming, how you can start thinking more critically, apply critical thinking today.

Learn to code today. Try one of our courses on programming fundamentals: Learn to Code: Python for Absolute Beginners Learn to Code: C++ for Absolute Beginners Learn to Code: C# for Absolute Beginners Learn to Code: Java for Absolute Beginners Learn to Code: JavaScript for Absolute Beginners Learn to Code: Ruby for Absolute Beginners

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• Streib J (2015) Critical thinking and debugging software Journal of Computing Sciences in Colleges 10.5555/2831373.2831392 31 :1 (110-116) Online publication date: 1-Oct-2015 https://dl.acm.org/doi/10.5555/2831373.2831392
• Myers J (2014) The cheat sheet as pedagogical tool Journal of Computing Sciences in Colleges 10.5555/2667432.2667438 30 :2 (44-51) Online publication date: 1-Dec-2014 https://dl.acm.org/doi/10.5555/2667432.2667438

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Artificial intelligence

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Cognitive robotics

Philosophical/theoretical foundations of artificial intelligence

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• IT technical skills

The growing importance of critical thinking in IT education

This is a guest blog by Dr Arosha K. Bandara, senior lecturer in Computing at The Open University

A criticism often levelled at IT education is that by the time you come to apply the skills, they might be out of date. Why learn technology skills when that technology might not be in use in a couple of years?

IT does change fast, but the fundamentals of how we design and build systems change at a slower pace. As long as we learn about today’s technology in the context of how it relates to the business world and how it is likely to evolve, then we will be in a much better position to respond intelligently to the changing world.

But this is often overlooked by both formal and in-house training programmes, which have favoured skills which address very specific challenges. In order to be adequately prepared to tackle tomorrow’s technology challenges, we need to move from a mindset of knowing how to apply technology to well understood situations, to one of being able to think critically about problems, and identify solutions to unknown as well as familiar technology issues.

Think differently

To prepare IT professionals for the rapidly changing world of technology, we need to instil an approach based on critical thinking. I’ll look at how we might do this, before putting this approach in context.

The organisation you work in is complex. It is shaped by the nature of individual thinking processes as well as existing technology and business pressures. Any changes will have causes and consequences that may have a much wider impact. Solving a problem will change things, which could lead to other problems.

Different people see different priorities. There is sometimes no obvious answer, or many different reasonable answers.  But there are also wrong answers, which can be pursued, sometimes at great cost. These often result from a very narrow focus on the problem out of context.

Interconnections are too often ignored, a single cause may be presumed, or an individual quickly blamed. This is not exclusive to IT, we see this in wider society all the time – it’s easier to blame crime on individual criminals than deal with the many complex societal factors that lead some to criminality. The other mistake is a focus on outcomes – ie how many criminals can we arrest rather than how many crimes can we prevent.

To avoid these mistakes, problems should be approached by thinking about the systems that affect the challenge or opportunity. This is more difficult than isolating and addressing a problem, but ultimately more likely to produce a better solution.

Thinking about systems

As well as looking at how technology works, it is necessary to think about how people will react to it. Is a great new technology too hard to learn? Will tough new security procedures incentivise people to circumvent them? We need to understand the systems in which new technology operates.

Cognitive mapping is a technique for understanding and shaping the mental models your stakeholders use to per­ceive, contextualise, simplify, and make sense of otherwise complex problems. Thinking through these will help ensure new technologies and programmes have the results they are supposed to.

However good your plan is, you won’t foresee everything, so it is also critical to continuously test and review, and feed that learning into your ever evolving plans. Throughout the life cycle of any project, topics such as stakeholders, finance, risk, people, project administration and quality must be constantly reviewed in the context of the project.

The world of the future will require more understanding of flexible management. We will have to place more emphasis on learning as we go and making sure that learning changes our practice and organisations. We need to get used to this.

Critical thinking in context

Two core skills of any modern IT professional are cyber security and software engineering. Both relate to complex real world challenges and can only be dealt with effectively if they think critically.

Firstly, cyber security. Any IT professional needs to fully explore the available security technologies and stay up to date with them. But they also need to think through the risks that may arise in all relevant aspects of an organisation’s operations which may impact security, including human factors, web services and system upgrades.

You also need to be able to plan for when things do go wrong. Again, this needs an understanding of attackers’ motivations and employee weaknesses, as well as of the technologies available to circumvent your defences, and a sense of how these could evolve. It also requires an understanding of the legal frameworks and technologies relevant to digital forensics, which are essential when responding to cyber security incidents. Only then can effective plans be made.

Teaching all this must be put in a real world context. In our own post-graduate courses, most students learn these techniques by crafting a fit-for-purpose Information Security Management System for the organisation where they work.

Secondly, software engineering. Contact between the business and the external world is often mediated by software, and the business has a responsibility to its wider community that may be served, or jeopardised, by this software.

Skilled software engineers can add a lot of value by creating or adapting software, from managing projects and sales, analysing performance and customer data, and automating tasks. All of these exist in a complex real world, where humans react to change in different ways. Any new system must understand how users or customers will respond to it.

The skill is not one of knowing how to do this, it is one of knowing how to model the relationships between the software, the organisation it serves, and its wider environment. This approach must be used in development, roll out, updates and maintenance – it is an evolving process.

Critical thinking doesn’t mean ignoring technology, of course. The process can be evolved further by an understanding of different software engineering tools that can help them simulate, manage and monitor. Using these effectively is part of the skill of good IT planning.

A critical approach allows you to plan effectively

IT is critical to business and will become ever more so. It exists in an increasingly networked and interconnected world, where groups, teams, organisations and even nations will have to be smarter in their ways of working together.

IT professionals therefore need to be able to think in ways that reflect these challenges. IT education at all levels must teach how to take a critical approach which relates technical competencies to complex technological, human and business issues.

Dr Bandara teaches Postgraduate Computing courses at The Open University aimed at helping IT professionals advance by using technology strategically to drive the business forward.

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• Our Mission

Computational Thinking is Critical Thinking—and Belongs in Every Subject

Identifying patterns and groupings is a useful way of thinking not just for computer scientists but for students in all fields.

Computational thinking, a problem-solving process often used by computer scientists, is not that different from critical thinking and can be used in any discipline, writes Stephen Noonoo in “ Computational Thinking Is Critical Thinking. And It Works in Any Subject, ” for EdSurge. 

Elements of computational thinking, like pattern recognition, are easily transferred to unexpected areas of study like social studies or English, says Tom Hammond, a former teacher who is now an education professor at Lehigh University. Hammond says that students like the computational thinking approach because it’s engaging: “Ask yourself, would you rather get to play with a data set or would you rather listen to the teacher tell you about the data set?” 

For example, in history classes students make use of data-rich, often open-source geographic information systems, or GIS, to plot election results from the colonial era to reimagine the way politics unfolded in the 1700s. These kinds of data visualization exercises offer a way for students to actively manipulate real-world information for deeper engagement and understanding.

There are three steps to bring computational thinking into your classroom, regardless of your subject area. First, consider the dataset. Hammond offers an example of incorporating computational thinking into a social studies class: A student is asked to give five state names which Hammond writes on the board. Then a different student lists five more states.

Once all the information is on the table, students execute the second step: identifying patterns. “Typically, this involves shifting to greater levels of abstraction—or conversely, getting more granular,” Noonoo writes. For students looking for commonalities or trends, this kind of critical thinking “cues them into the subtleties.” In the states example, students try to identify why Hammond grouped the states in the way he did. Is it by geography? Is it by what date they became part of the United States? Slowly, students begin to identify patterns—something the brain is already hardwired to do, according to Hammond. 

In the final stage—decomposition—students break down information into digestible parts and then decide “What’s a trend versus what’s an outlier to the trend? Where do things correlate, and where can you find causal inference?” Establish a rule from the data—a process that requires that students make fine distinctions about how complex datasets can be reliably interpreted, Hammond says.

“It definitely took some practice to help them understand the difference between just finding a relationship and then a cause-and-effect relationship,” says Shannon Salter, a social studies teacher in Allentown, Pennsylvania, who collaborates with Hammond. 

An entire curriculum can be dedicated to incorporating computational thinking, but that kind of “major overhaul” isn’t required, Hammond says. “It can be inserted on a lesson-by-lesson basis and only where it makes sense.” 

Computational thinking is not that far afield from critical thinking. The processes mirror each other: “look at the provided information, narrow it down to the most valuable data, find patterns and identify themes,” Noonoo writes. Students become more agile thinkers when they exercise these transferrable skills in subjects not often associated with computer science, like history or literature. 

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Computer Science

What Types of Skills Are Best for a Computer Science Major?

If the idea of writing code and coming up with creative tech solutions appeals to you, then becoming a computer science major might just be for you. What’s the best way to thrive as a computer science major and set yourself up for success? It starts with having the right skill set.

Here are the top five skills the most successful computer science majors possess.

Analytical skills

Being a computer science major involves identifying a problem and coming up with a technological solution to address it. This requires having strong analytical skills that will enable you to understand the issue you’re dealing with and evaluate different solutions in order to find the one that best fits your needs.

Problem-solving skills

One of the other key skills for computer science majors is the ability to solve complex problems in a systematic and logical way. This is because most of the projects you’ll be working on will require you to take a concept and turn it into a reality. In order to do this, you’ll need to be able to think about the best way to execute the project and then outline the steps needed to get it done.

Creativity goes hand in hand with problem solving and it’s one of the other key skills you’ll need as a computer science major. Since coming up with solutions to problems is almost never a straightforward process, out-of-the-box thinking is often required in order to ensure that you’re delivering the most innovative and effective solutions.

Critical-thinking skills

Critical thinking is an important skill to have in any major, but it’s especially important when it comes to computer science. This is because you’re going to be working on a variety of projects and using a variety of methodologies, so knowing which methodologies to use (and when to use them) is an essential part of getting the job done. By thinking critically, you’ll also be able to assess why certain solutions might not work and to save time in coming up with the right approach.

One of the key tenets of programming (at any level) is understanding that you’re most likely going to fail before you succeed. This has nothing to do with your programming abilities and everything to do with the process itself. Programming involves trying out different elements of code until you find the best solution and learning to be resilient, determined and humble in the face of multiple failures is part of the process.

Next, learn more about this college major such as What Is a Computer Science Major and Is It Right for Me?  and get more career tips for internships and entry-level jobs such as Top 10 Things You Should Look For in a Company .

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November 22, 2022 8:00 am

The Four Cs of STEM in Computer Science

Celebrate Computer Science Education Week and the international Hour of Code by exploring the four Cs of STEM. Students can learn about real-world applications of the four Cs in computer science from Chicago to Mars and roll up their sleeves for their own practice with Imagine Robotify, a fun online quiz, or an adventurous robot named Axel.

Digital tools, automation, network security, and AI are shaping our future. Recognizing the increased demand for digital literacy in the workforce, more than  500 CEOs  recently petitioned education leaders to prioritize computer science instruction in K–12 schools. The U.S Department of Education followed that by launching the  YOU Belong in STEM  initiative to enhance science, technology, engineering, and math (STEM) education for all students.

Computer Science Education Week, December 5th–11th, is the perfect time to get involved! A great way for educators at any grade level to explore STEM (which includes computer science!) is to teach its essential skills. Four of the most important abilities in STEM are critical thinking, creativity, collaboration, and communication, also known as  the four Cs . These skills are necessary for 21 st -century college and career readiness, in STEM and beyond:

• Critical thinking  involves analyzing systems, assessing evidence, integrating prior knowledge to make connections to new situations, and the ability to interpret information. 
• Creativity  is necessary to come up with new ideas. The ability to “think outside the box” when challenged, improve ideas, work within constraints, and learn from failure are all components of iterative design, which require creativity!
• Collaboration  means working in groups, sharing responsibility, and making decisions and compromises. 
• Communication  is critical in our global world. It’s the ability to express ideas, understand their meaning, and demonstrate concepts to different audiences.

The four Cs in the real world

Computer Science Education Week presents a great opportunity to learn with your students about how the four Cs are applied in the real world. Here are three examples.

1. Trashbot

Urban Rivers creates solutions to transform urban waterways, including a volunteer-controlled robot called Trashbot that cleans the Chicago River. The creators of Trashbot used critical thinking to recognize the complex system in which Trashbot would operate while also ensuring the safety of wildlife, civilians, and infrastructure.

The team realized the robot would need to be controlled because an automated robot could pose a risk to wildlife habitats. However, financial and personnel constraints made having a manual operator 24/7 impossible.

Urban Rivers tapped into their creativity and learned from previous failures to find a solution: volunteers could control Trashbot throughout the day to clean the river safely. Next, they collaborated with volunteers to make the solution possible, using media communications to teach them how to operate the equipment. Now, Trashbot is run by community volunteers who can clean up the Chicago River regularly.

Watch  this video  to learn more with your students.

2. UTM Project

An unmanned aircraft system (UAS) consists of drones or satellites, and the potential uses are limitless!  NASA’s UAS Traffic Management  (UTM) project aims to find ways for low-altitude drones to operate in large numbers, enabling businesses like  Amazon  to offer drone delivery services. 

The UTM team uses critical thinking skills to identify problems before they arise, such as how extreme weather could affect a drone or what happens if it is lost. The UTM project also researches how future technology would be managed. Drone technology could reduce traffic, fight wildfires, and perform dangerous tasks. 

The project is complex, with many interested partners in corporations and governments. The UTM team knows collaboration and communication are the keys to the project’s success, allowing them to include the needs and challenges of different groups in the research and share that research with the public. 

NASA’s UTM  website  provides up-to-date information and updates about the project. 

3. Mars Rover

The Perseverance Mars Rover  roams the red landscape of Mars with the help of NASA’s scientists. On one mission, the team was challenged to drive Perseverance as far as possible. However, the rover would be self-driving, so the team needed it to drive effectively while avoiding obstacles.

The amount of possible paths to take on Mars is endless, but some paths are better than others. That’s why critical thinking is crucial to the mission: it’s used to assess the situation, make connections, and interpret data. Critical thinking also helps the team learn from previous Mars missions and determine new solutions.

Using creativity, they can overcome obstacles and imagine new ways to program the rover. The team coding Perseverance also understands how to collaborate. By working with teams across NASA and using clear and thorough communication, they can share and interpret data to put the rover on the right path.

Empowering the next generation

The significance of the four Cs of STEM is apparent across these three real-world examples. Critical thinking, creativity, collaboration, and communication are key to any mission. From cleaning up a river to exploring space, computer scientists use the four Cs daily.

What about the future STEM professionals in your classroom? Students can start their own journeys to Mars and practice the four Cs by celebrating Computer Science Education Week and participating in its international Hour of Code.

Hour of Code

Hour of Code is – you guessed it – a one-hour introduction to computer science, using activities to show that anybody can learn the basics. If your school doesn’t already have a coding program, a few fun options to spark engagement and pique students’ interest could include:

• Testing their computer science brain power with  a themed quiz on Kahoot
• Coloring Axel the robot’s many adventures with  downloadable coloring pages
• A special Hour of Code Imagine Robotify project. If you’re using Imagine Robotify, head to the projects tab on your menu to find an Axel drawing project in either Python or Blockly. Students can learn to create programs to draw common shapes on a coordinate plane. 

Whether you celebrate Computer Science Week and Hour of Code with robots and crayons or by exploring essential skills, you’ll create more STEM possibilities for your students’ futures.

• Corpus ID: 17599042

Critical thinking and computer science: implicit and explicit connections

• B. Fagin , J. Harper , +2 authors R. Sward
• Published 1 April 2006
• Computer Science, Education
• Journal of Computing Sciences in Colleges

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18 Citations

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Computational Thinking Is More about Thinking than Computing

• Published: 18 May 2020
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Cite this article

• Yeping Li 1 ,
• Alan H. Schoenfeld 2 ,
• Andrea A. diSessa 2 ,
• Arthur C. Graesser 3 ,
• Lisa C. Benson 4 ,
• Lyn D. English 5 &
• Richard A. Duschl 6  

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Computational thinking is widely recognized as important, not only to those interested in computer science and mathematics but also to every student in the twenty-first century. However, the concept of computational thinking is arguably complex; the term itself can easily lead to direct connection with “computing” or “computer” in a restricted sense. In this editorial, we build on existing research about computational thinking to discuss it as a multi-faceted theoretical nature. We further present computational thinking, as a model of thinking, that is important not only in computer science and mathematics, but also in other disciplines of STEM and integrated STEM education broadly.

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Introduction

In our second joint editorial (Li et al. 2019a ), we focused on design and design thinking in science, technology, engineering and mathematics (STEM) education, and discussed design thinking as an example of models of thinking that are important to each and every student. Contrary to a common perception that design and design thinking belong to certain subjects but not others, we highlighted the need and significance of changing the subject fixation perception to elevate the conception of design thinking as transdisciplinary and not belonging to the field of engineering only. Based on our proposed notion of “everyone designs and can design” (Li et al. 2019a ), we further discussed how existing research supports this notion with evidence of mutual benefits between design and STEM education.

In this editorial we make another extension of our previous discussion about the conception of thinking as plural proposed in our first joint editorial (Li et al. 2019b ), with a focus on computational thinking (CT). Specifically, we take the position of viewing CT, as another example of models of thinking, which is important for every student to develop and apply in the twenty-first century. As there have been quite many studies and discussions about CT over the past decade (e.g., Denning 2009 , 2017 ; diSessa 2018 ; Grover and Pea 2013 ; Wing 2006 , 2014 ), we aim to build on existing research to provide a theoretical account of CT in this editorial and leave the discussion about educational programs and practices to develop students’ CT as the topic for our next editorial.

In the following sections, we start by discussing motivation for conceptualizing CT and then propose a definition of CT that is applicable to STEM education and beyond. To clarify our definition, we further provide an overview of three primary approaches to describing CT in the literature, arguing that this body of literature has conceptualized CT as a stance toward programming competence and skill acquisitions, a cognitive process, and a particular type of literacy. We discuss how our definition connects with each of these three approaches. We conclude by describing how CT is distinct from other models of thinking like design thinking. We also highlight the implications of this definition for STEM education and future CT research.

Motivation for Conceptualizing CT Applicable to STEM Education and beyond

Wing’s succinct article ( 2006 ) about CT has raised significant interest in professional and education communities (e.g., CSTA & ISTE 2011 ; Grover and Pea 2013 ). Wing argued that CT “represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use” (Wing 2006 , p. 33). This proposition reflects a rapidly growing interest in knowing, learning, and using computation in a broad array of professional activities in diverse fields such as physics, biology, and finance. Indeed, a recent report Charting a Course for Success: America’s Strategy for STEM Education, released by the White House (December 2018), highlights that building computational literacy is one of the four pathways to succeed in STEM education, with one of three objectives under this pathway being “make computational thinking an integral element of all education” (Committee on STEM Education 2018 , p. 23).

While the importance of CT has been commonly recognized, the meaning of the concept is contested. For example, Wing came to the concept from deeply inside the culture and technicalities of professional computer science. Someone outside that community might be prone to narrowly construe the idea of CT to direct connections with “number computation” or “computer.” The following are example interpretations.

Viewing CT as Related to Computation Skill Development in School Mathematics

Computation is a familiar idea to most, especially to parents and students in elementary school. Students are required to learn to compute with numbers (e.g., CCSSI 2010 ; NRC 2002 ). Such skill is commonly acknowledged as important not only in people’s daily life, but also in preparation for, and in the conduct of, many professions, including science, engineering, insurance, and finance - wherever numbers are relevant. Computation is typically taken to be a basic skill, and parents and the public would be upset if children don’t gain such basic skills through school education (e.g., Kakaes 2012 ; Kline 1973 ).

Computation was loosely connected to thinking until mathematics educators started to emphasize the importance of students making sense of what they do when they engage in computation (e.g., Brownell 1945 ; Li and Schoenfeld 2019 ). For example, students might simply memorize the subtraction algorithm and know how to compute, say, 45–21, as “subtracting a small digit from a larger digit,” getting the correct answer, 24. But, without the needed understanding of place value and base-10 number composition and decomposition, then, a student might well carry out the computation 41–25 but get the same answer of 24. Here, we highlight the words of “making sense” and “understanding,” as they require thinking beyond rote computation. Helping students to develop such deeper understanding has long been advocated and emphasized (e.g., CCSSI 2010 ; NCTM 1989 ), and also practiced in school mathematics such as the use of “number talks” (e.g., Parrish 2011 ).

Thus, in combining “computation” and “thinking” in this restricted sense, CT won’t be strange to mathematicians, mathematics educators, and teachers at all. CT would be then emphasizing the importance of thinking and understanding in and for doing computation. The notion of CT might well be readily accepted for its importance to every student in learning mathematics. And yet, mathematics educators already have other terms that convey similar meaning, such as “number sense” (e.g., Sowder 1992 ) and “symbol sense” (Arcavi 1994 ). But, then, why should this new term have any particular importance beyond other, older ones? Why should the importance of CT be advocated by computer scientists as important to everyone, when computation in mathematics is commonly taken as a basic skill? Footnote 1

Viewing CT as Specifically for Computer Scientists or Merely Learning how to Use a Computer

Widespread association with computers or programming can easily lead people to perceive CT as specifically for computer science professionals. It would therefore be difficult for many to understand why CT is important to everyone. Certainly programming—at least in the way it is perceived from the work of professional programmers—is considered difficult and esoteric. Developing software for a computer’s internal operations would then be important to professionals in computer science, but out of reach to many others. In the same way, abstraction and modeling with the use of CT in many professional fields beyond computer science would be seen as unimportant and of marginal concern for most people. For more details, see the discussion of “vocationalism” in the CT movement in diSessa ( 2018 ).

In terms of making the concept of CT more accessible and relevant to those who are outside of computer science, it should also be noted that CT is not simply about learning how to use computers or software (i.e., “computer literacy”). By analogy, just learning to drive a car does not mean that one develops “mechanical thinking.”

A Proposed Definition of CT

An adequate understanding of the notion of CT is clearly needed if CT is to be seen as important to everyone and worthy of being taught and learned in widespread educational contexts. Wing ( 2006 ) asserted that CT “involves solving problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science.” (p. 33). The description provides a broad scope for CT’s relevance. Wing ( 2006 ) further highlighted its importance with different manifestations of CT and its uses in many other fields, such as statistics, biology, physics, and economics.

At the same time, what makes CT special in Wing’s description is the implication of “… drawing on the concepts fundamental to computer science.” Wing ( 2008 ) further specified two essences of CT: abstraction and automation. The specifications strengthened the linkages of CT with core and general competences involved in computing and computer science.

Emphasizing “computing” or “programming” in CT, we then can conclude that CT has not been highlighted in traditional school education, as course requirements in computer science or programming are minimal or completely lacking. Wing ( 2006 ) should be credited with a notion of CT that is future-oriented and important to everyone. Through highlighting direct associations between CT and “concepts fundamental to computer science,” Wing contributed substantially to the on-going movement of computer science education for all in the United States (e.g., PITAC, 2005 ; White House 2017 ).

However, challenges remain for many teachers and education researchers who struggle to understand the meaning of CT, its assessment, and usefulness for everyone (Denning 2017 ). The accessibility and usefulness of the notion might well be undermined for many by the expectation of training in computer science as a pre-condition. In fact, though, computer science itself is no longer viewed as the study of phenomena surrounding computers, but, instead, it is the study of computational information processing, both natural and artificial (Denning 2005 , 2007 ). At the same time, human thinking can also be characterized as specific models of information processing when performing various tasks (e.g., Anderson et al. 2004 ; Simon 1979 ). The connections between computing and human thinking in information processing suggest the possibility of taking the notion of CT to a more generalizable level.

Specifically, we want to view CT as a model of thinking that is more about thinking than computing. As computing is the study of natural and artificial information processing (Denning 2007 ), CT is about searching for ways of processing information that are always incrementally improvable in their efficiency, correctness, and elegance. The entailed improvement can call for the use of various strategies (including abstraction and modeling), practice, skill acquisition and improvement. Here, information can take different formats, at different levels of abstraction, and thus appears as various representations that can be customized and used in different disciplines for problem solving, modeling, and system building. Just as everyone designs and can design, we believe that everyone processes information, and helping them to do that well is our job as teachers.

Although programming and coding can be part of CT, CT should not be restricted in computer science but is prevalent in diverse professional fields and in daily-life events. For example, computational modeling has been used to summarize and analyze data (as code in CT) in different ways to help predict on-going trends in the coronavirus crisis, in multiple countries. A vignette of such an analysis by Andrea diSessa is included as supplementary material (see Computational Literacy in the Time of COVID-19). The lack of accurate data or CT would prevent people from effectively monitoring and managing the crisis development to save lives. Without specific attention to the improvement of information processing efficiency and elegance, we may lose opportunities to nurture students’ CT and develop skills that prepare them to grapple with global crises. It is imperative that school curricula and instruction integrate CT in students’ subject content learning, not just in computer science and mathematics but also in other STEM disciplines and beyond.

To further clarify our position, we take a brief review of different approaches in describing CT and discuss how our perspective is associated with these approaches.

Approaches to CT in the Literature

In the following sub-sections, we examine three different approaches that have had tremendous influence on the development of CT in research and educational practice.

Discipline-Based Approaches

The discipline-based approaches in describing CT have a long history associated with the development of computer science and computation itself in general. Denning ( 2017 ) indicated that George Pólya’s work on mathematical problem solving (e.g., Pólya 1945 ) that provided general heuristics for solving a wide range of problems, as discussed in our first joint editorial (Li et al. 2019b ), can be viewed as a precursor to CT. diSessa ( 2018 ) also identified many similarities between Pólya’s work and Wing’s writings about CT (Wing 2006 , 2014 ). Although computation was in existence long before the creation of computers, the development of computation has experienced tremendous changes over the years associated with the invention and use of computers. Denning ( 2007 ) summarized the revolution in three main stages: (1) computation as a tool for performing simple and well-structured tasks, such as solving equations and running simulations, together with the creation and use of the first electronic digital computers in the 1940s; (2) computation used not only as a tool but also a method for discovering new knowledge beginning in the 1980s; and (3) computation and information processing found in the deep structures of many different fields beginning in the 2000s, such as biology, physics, and business management. Abstraction and modeling are essential to computation and computing as they develop and use in many different fields.

Related to the development of computation, computational science, and computer science, the notion of CT has also evolved from “algorithmic thinking” in the 1950s and 1960s (a mental orientation toward looking for algorithms that can help convert some input to an output in problem solving), a way of doing science that develops and uses computational models (associated with the development of “computational science”, distinct from computer science, beginning in the 1980s), and as one of several key practices for every computer scientist whereas computation itself as existing in nature is viewed as more fundamental than CT (Denning 2009 ).

The discipline-based approaches in describing CT as discussed above suggest that CT can be characterized as a way of thinking and doing —a method— or as a key practice, which needs to be developed through programming practices. What is consistent among discipline-based approaches is the emphasis on one’s capability of designing a correct solution with efficiency and elegance, in computational steps, that might reply on years’ experiences and programming capability. As a computer scientist well known for his work on programming language and algorithms, Aho ( 2011 ) indicated that “Mathematical abstractions called models of computation are at the heart of computation and computational thinking. Computation is a process that is defined in terms of an underlying model of computation and computational thinking is the thought processes involved in formulating problems so their solutions can be represented as computational steps and algorithms.” (p. 7) Aho’s characterization of CT is consistent with what Wing ( 2008 , 2014 ) emphasized as a key of CT: abstraction.

The historical development of the notions of computation and CT led Denning ( 2017 ) to argue that CT, as proposed by Wing ( 2006 ), represents a new version that is not the same as the traditional version developed through the history. The basic difference is that the traditional CT would be developed through programming practices in the profession, and the new version of CT would rely on concept learning to produce programming ability. Thus, the usefulness of the new CT to everybody is unclear and remains to be empirically studied (Denning 2017 ).

At the same time, the historic development of computation and CT also suggest that CT should not be taken simply as equivalent to computer science. The notion of CT has been used so widely in many different fields including mathematics and science both in the past and present. The position we propose to view CT is consistent with discipline-based approaches, in the sense that we emphasize the need and importance of performance improvement in efficiency, correctness, and elegance. In the computing field, performance can then be manifested as formulating and solving problems as computational steps and algorithms, and improvement can be made through developing and testing different computational steps and algorithms.

Psychology-Based Approaches

Although some scholars also characterized CT as a thought process in discipline-based approaches albeit from a computing perspective (e.g., Aho 2011 ), the emphasis placed on thinking rather than computing represents a shift of focus in the conception.

The study of thinking has had its own long history, as we discussed in our first joint editorial (Li et al. 2019b ), which has evolved from philosophical discussion to psychological studies in and across disciplinary domains.

One particular approach that revolutionized the study of problem solving in the 1950s and 1960s was to conceptualize information processing in the human mind and use the computer to simulate human problem solving performance (e.g., Newell and Simon 1972 ). The approach was powerful as it built empirically from psychological studies about various components of human cognition and then tested them through software development and simulations. Examples include the Elementary Perceiver and Memorizer (EPAM, Feigenbaum and Simon 1984 ), and adaptive control of thought-rational (ACT-R, Anderson et al. 2004 ; Anderson and Lebiere 1998 ). At the same time, the approach was restricted in the sense that it did not really conceptualize CT at all, but used computation as a tool to help with research about human cognition. As discussed in the previous editorial (Li et al. 2019b ), Simon expanded the information processing model of “problem solving man” from Human Problem Solving (Newell and Simon 1972 ) to the notion of “thinking man” in the book Models of Thought (Simon 1979 ). Simon used “thinking man” as a prototype to conceptualize human thinking as information processing in and through various component elements that can and should be merged into a coherent whole (Simon 1979 ).

At that time, there was very little emphasis on the idea that information processes and computation actually exist in nature. His book The Sciences of the Artificial (Simon 1969 ) contributed to building a foundation for the development of artificial intelligence, Footnote 2 including models of how the mind works. Now we can learn also from biology research; information processes and computation exist in nature as information encoding and generation in and through DNA, with its distinct computational methods (see Denning 2007 ). Thus, it is better to surpass Simon’s notion of conceptualizing human thinking as information processes and computation. What makes CT, as proposed in our position, distinct from general human thinking then resides in the dedication to performance improvement in efficiency, correctness, and elegance, as discussed above.

Education-Oriented Approaches

Many scholars have discussed the ambiguity associated with CT and tried to clarify its meaning (e.g., diSessa 2018 ; Grover and Pea 2013 ; Hu 2011 ). For example, Hu ( 2011 ) reviewed and discussed many different perceptions that people held about CT, including CT as related to the tension between empirical and theoretical investigations; as an ability to see, comprehend and devise systems and processes; as an aid to do mathematics computationally; or as a set of problem-solving skills and techniques for software engineers in programming. Taking it positively, people view CT as relevant to many different professional activities, especially in different fields of STEM. At the same time, these diverse perceptions suggest the importance of clarifying the meaning of CT as is appropriate and needed for education.

There are three main approaches in describing CT that aim to facilitate educational practice.

One approach in education is to follow a description developed from discipline-based approaches as discussed above. For example, Grover and Pea ( 2013 ) reviewed relevant development in K-12 education associated with CT, from procedural thinking development through LOGO programming in the 1980s (Papert 1980 ) to recent movement of several professional societies and organizations aimed to develop students’ CT such as, the Association for Computing Machinery (ACM), Computer Science Teachers Association (CSTA), and Google. Instead of discussing possible clarifications that may be needed, Grover and Pea focused on how others might have interpreted Wing’s description of CT. The review provided a nice summary of on-going efforts from professional organizations and studies that aim to develop CT through programming and computer science in K-12 education. Grover and Pea also highlighted and discussed that tremendous efforts are needed in developing programs and research further in a broad range of topic areas including curriculum, instruction, assessment, and teacher education.

Another approach is to propose and discuss possible expansion of CT beyond computer science. For example, a recent report Charting a Course for Success: America’s Strategy for STEM Education, released by the White House in December 2018, included CT, digital literacy, and computational literacy when laying out the vision for the United States to success in STEM education (Committee on STEM Education 2018 ). With the increasing use and importance of digital devices and the internet, the committee envisioned the importance of “digital literacy” as a basic level of understanding and “computational literacy” as a higher level of skill for all students to benefit from what technology development can bring for tomorrow’s job opportunities. Building computational literacy was taken as one of the four pathways to success in STEM education, with “make computational thinking an integral element of all education” listed as one of three objectives under this pathway. Although possible relationships among computational literacy, CT, and digital literacy were not explained in the report, computational literacy was seemingly taken as having a broader scope than CT. The meaning of CT was explained first in the report with the definition from Wing ( 2014 ), and then expanded as including some broadly valuable thinking skills beyond computer science: evaluating information, breaking down a problem, and developing a solution through the use of data and logic. In fact, this expanded description shares many similarities with George Pólya’s work on problem solving. With this expansion, the report further indicated the importance of developing students’ CT as an integral part of all education with or without the use of a computer.

There is one other approach that aims to highlight the importance of computation for students’ learning beyond programming. diSessa ( 2000 ) advocated the notion of computational literacy before Wing’s promotion of computational thinking, and also took a principled approach in emphasizing both “cognitive” and “social” aspects rather just focusing on programming and the computer environment.

Different from the popular use of literacy that many may perceive as “a casual acquaintance with …,” diSessa ( 2018 ) defined literacy as a massive intellectual accomplishment of a culture together with a grand “re-mediation,” shifting and expanding the fundamental forms of representation in society to include computation as universally known and used. Similar to the way algebra and calculus transformed the study of physics from a philosophical inquiry to a rigorous, precise empirical pursuit (diSessa 2000 ), computation not only supports many different fields (not just computer science) but can also change the very intellectual landscape of fields in what they do and how they develop. diSessa ( 2018 ) thus viewed computational literacy as important to every student, but not in the same way as Wing ( 2006 ). In his view, computation is not the special province of computer scientists, and everyone does not need to think like a computer scientist. Instead, computation is a fundamental resource for all of society, and it will develop earmarks that distinguish it in the way it is useful in each discipline and also in the larger, public society.

What diSessa ( 2000 , 2018 ) advocated as computational literacy for everyone shares much with our position about CT in terms of the universal importance of computation and the emphasis on cognition. Footnote 3 At the same time, they differ not only in their approaches to formulating definitions for these two connected and complementary concepts, but in the patterns of appropriation of CT or computational literacy in the broader society. As such these different-but-related concepts also suggest different strategies for anyone anxious to get the most from computation in education and in the intellectual performance of society broadly. Footnote 4

Differentiating CT from Other Models of Thinking

At the beginning, we indicated that we take the position of viewing CT, as another example of models of thinking, as being important for every student to develop and have in the twenty-first century. After discussing what we mean by CT, we need to explain further how CT may differ from other models of thinking. So far, we only discussed design thinking as another model of thinking in our second joint editorial (Li et al. 2019a ). Thus, we would like to share some of our thinking behind identifying and defining specific models of thinking.

There are several principles that have guided our thinking: trans-disciplinary, purpose, and function. Taking CT as an example, if perceiving what makes CT special is the indication of “… by drawing on the concepts fundamental to computer science” (Wing 2006 ), people can wonder whether CT is pertinent only to computer science professionals or whether replacing the phrase of “computer science” with “physics”, “life science”, or “earth science”, we can have “physical thinking”, “life (science) thinking”, or “earth (science) thinking” when solving problems. If CT is important to everyone, should physical thinking, life (science) thinking, and earth (science) thinking be all important to everyone especially when we all live and stay on this planet? The discipline-based thinking can be important but often carry limitations. Thus, CT, as a model of thinking in STEM education and beyond, needs to be conceptualized as truly trans-disciplinary and important to everyone.

Across different models of thinking in our perspective (see Li et al. 2019b ), their differentiations can be made in terms of the purpose and function. For example, while design thinking focuses on designing and making things like everyone does and not just in engineering design, CT focuses on the performance improvement in efficiency and elegance. At the same time, these models of thinking can and should work together in various problem solving activities either individually or collaboratively in groups. Different forms of representations and abstractions can also be taken and used in different fields of study when these models of thinking may function for specific aspects of cognition in activities.

It becomes clear and important to us, in school education, to take an alternate perspective on CT and not restrict it to an association with programming or computer science professionals. While the practice of, and capability for, programming are certainly important for developing CT for computer science professionals, it is more important to realize that computation is an integral part of many other fields beyond computer science. The notion of CT should not be restricted definitively to computer science or programming, thus avoiding a subject fixation about CT. CT needs to be re-conceptualized, as we did in this editorial, to ensure it is relevant, important, and accessible to everyone. The development of CT can then be truly integrated into all education for everyone to succeed in STEM education (Committee on STEM Education 2018 ).

It is also important to point out that the reconceptualization of CT, as a model of thinking, makes its integration in all education a possibility. Great challenges remain to develop educational programs and practices to make the integration happen and to conduct research for further scholarship development (e.g. Honey et al. 2014 ). There is a rapidly growing number of programs and studies that focused on how CT can be developed through programming and computer science in K-12 education (e.g., Barth-Cohen et al. 2018 ; Bienkowski et al. 2015 ; Grover and Pea 2013 ), in and through STEM education with mutual benefits for students’ subject content learning (e.g., Dauer et al. 2019 ; Sengupta et al. 2013 ; Yadav et al. 2018 ). In our next editorial, we will further discuss educational programs and studies to develop students’ CT, conceptualized in different approaches. At the same time, we would like to take this opportunity to let everyone know that this journal encourages submission of related research on CT, its development in and through STEM education, through different theoretical lens and/or with the use of different research methodologies. It is a frontier topic in STEM education that calls for the development of new and robust scholarship (Li 2018 ).

While numerical computation may be a basic skill, it is not necessarily mechanical and routine, as it is often perceived. For example, Dowker’s ( 1992 ) work on estimation showed that mathematicians are flexible – they don’t follow algorithms and may not use the same techniques when estimating the same quantities at different times. But they always have a good sense of how solid the estimates are.

With a focus on problem solving, George Pólya was well recognized in the field of artificial intelligence (AI) for his work in heuristic but AI had not made good use of Pólya’s work. Newell ( 1981 ) examined and discussed possible reasons.

The vignette in the supplement provided by Andrea diSessa can serve as a good prompt for thinking about computational literacy and its relation with CT.

For example, CT in our definition emphasizes thinking, per se. Computational literacy also emphasizes developing computational environments that are widespread, very easy to learn, and which have affordances for many, many uses, not just for discipline-specific ones.

I use the Boxer programming environment. We designed Boxer precisely to be a medium supporting computational literacy See diSessa (2000).

They wrote video games. You can imagine how complex that might be, with multiple levels, scoring, a lot of narrative, different internal subgames, etc. Some of this is reported in diSessa (2000).

Down the road, I expect to look for another inflection point, where the number of cases ceases increasing.

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Acknowledgments

We would like to thank Christian Dieter Schunn, Eric B. Snow, and Pratim Sengupta for their valuable feedback on an earlier version of this editorial.

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Computational Literacy in the Time of COVID-19

Andrea A. diSessa

Graduate School of Education

University of California at Berkeley

Introduction: My Life as a Computationally Literate Person

I am among the privileged few for whom exercising computational literacy is an everyday affair. For example, I keep all my financial records in a self-constructed database, and I do financial planning with tools I’ve developed for myself. One of the advantages is that I get exactly the information I want, in the visible form I want, and I understand the details of how the tools work—for example, what assumptions they make, which is seldom or never true with on-line “calculators” such as those that estimate your income tax or plot a graph of future savings for retirement. I rarely use algebra to solve everyday mathematical problems because it’s so much easier just to write a program. I prefer to write a program to compute, say, compound interest than to use a formula because (1) it’s much faster than looking up or re-deriving the formula, (2) I can decide whether I want just a single result, a chart of gain over time, or a graph, and (3) I don’t need to make any simplifying assumptions, such as a constant rate of return. To exemplify the last, in planning financially for our sons’ college I wrote a little program that included both of our sons’ expected tuition and board (and relevant dates), our estimated savings rate, raises in my wife’s and my salaries, and also expected large purchases, such as a new car.

Professionally, I keep and analyze video data with my own tools. I outline papers in the same environment in which I program because that system has an excellent hierarchical organization facility (see images later), which is well-suited for good planning and editing, organized in multiple levels. I keep notes at meetings in the same way, since it produces a much better organized summary than linear text. And so on.

Some of this may sound sophisticated, but I am not a programmer. And many of these things are trivial, given a little knowledge of programming and a good environment in which to work. Footnote 5 In one of our classroom experiments, sixth grade students wrote programs that were far larger and more complex than what I normally make and use. Footnote 6

But I’m sure my life is not like yours. What follows might be more vivid in your own experience.

A Vignette: Tracking COVID Infections

Here is an exercise that I did for myself, just out of curiosity. Well, curiosity and perhaps some fear of what COVID-19 meant for us and our communities. I wanted to track some critical inflection points on the progression of the pandemic. In particular, I wanted to track whether and when social distancing had any noticeable effect. Technically, I wanted to see if and when there might be a deviation from the ordinary, purely exponential increase one gets from a situation where each infected person infects a fixed number of other people. With social distancing, that number should decrease. Footnote 7

It took me maybe 20 minutes to assemble what I needed, including finding an old graphing utility I had laying around, and also writing some new but simple utility functions. I keep mentioning speed because: (1) People who don’t program don’t know how easily such things can be done. (2) I would not do these things with programming if I knew a faster way to do them. I have no ideological commitment to programming just because it can be done. I do it if and when it’s the fastest, easiest way I know to solve the problems I have.

I’ll cut to the chase, and then backfill details. My very first graph, aimed to compare infection rates in California, compared to the US as a whole, appears below. The graph starts on March 18—two days after social distancing was instituted—and continues until March 29 of 2020.

This is a plot of log values of the data, since exponentials (which is the form of unfettered, constant infection rate growth) then appear as straight lines. The key lesson here is that, at the beginning of this time period, the slope of CA infections is significantly less than the US as a whole. That’s what I expected to see. Selfishly, it’s what I hoped for. To avoid confusion, note that I scaled the CA data so that it precisely matched the US at the beginning, just so that I could easily compare slope, there. (Rescaling and then applying the log function just provides a constant vertical shift; log ay = log a + log y.)

But there are interesting complications. While the blue (CA) graph is fairly straight, with the possible exception of a small downturn in the final two days, a colleague pointed out that it is a little jagged. It turns out that the jagginess is too much to be random error (1 / root N). But, a day later I read in the paper that California had been having trouble collecting data. Apparently, some counties were not reporting, or not reporting in a form that could be imported into the state’s data bases. That fact may resolve the puzzle of jagginess. But, it’s also true that the graph is as good as the data. I used: https://ncov2019.live. Finally, I could not get to the site at exactly the same time of day each day, and the data was continuously updating.

Another observation is the arching curve in the US data. I still don’t know why that is so. But, then, that was not an interesting point for me.

You can probably see that toward later times, the two graphs appear to be more parallel, signaling a similar infection rate. In order to make this clearer, I just re-scaled the CA data so that it matched the US data later in the graph.

In this form, it is clear that for a while the US and CA had the same slope (infection rate). But now, although both CA and US appear to have tilted slightly lower (smaller infection rates) in just the last couple of days, it appears that CA is beginning to show a lower, better rate. This is what I was hoping to see, even if I expected more than this little change. On the other hand, a change in infection rate should show up after about two weeks, so we are just edging into that regime. Yesterday, the day after I noticed the slight downturn in infection rates, I saw an article in the San Francisco Chronicle , entitled “Coronavirus slowing in Bay Area? Experts track data to see whether shelter in place is working.” The article said:

By day’s end Monday [tomorrow], most of the Bay Area will have been holed up in their homes for two weeks — long enough, experts say, to see whether the unprecedented efforts to keep people apart are beginning to halt, or at least slow down, the coronavirus.

Yes, but you don’t have to be an expert, if you’re computationally literate! And I am learning so much more about COVID-19 and its tracking by doing it myself. Furthermore, I could not find any online tools to do what I wanted, much less the particular graphs I wanted. I could not even find any historical data listing, so that I have had to enter each day’s data by hand and keep my own historical dataset. These failures of the on-line world to give me what I wanted are cultural failures of our society with respect to supporting widespread computational literacy. Very few expect the public, now, to have any use for bare data, nor certainly the capability to do their own analysis of it.

What might my vignette have to do with education, other than suggesting that we should work to develop a more computationally literate public? I told someone that I could easily imagine working with a group of high school students developing hypotheses, tools, and analytical techniques like this—and in real time as the pandemic develops. I’m missing a wonderful opportunity (for not having a high school class to work with, just now). I said I was sure high schoolers could develop original hypotheses and appropriate analytical methods.

But, then, it occurred to me that we had already done something very like this, in a more difficult (if less compelling) case! We asked students to take data on the heating/cooling of two objects, at different temperatures, in thermal contact. We looked at the graphs, thought about how and why that happened (it’s exponential decay; instead of change being proportional to amount (infections), change in temperature is proportional to the difference of temperatures). We then collaboratively developed a program embodying their model. In diSessa (2017) you can read about how one group of high school students developed, on their own and with no instruction, a normative model of temperature equilibration. In diSessa (2008) you can read several cases of students building conceptual and computational models of fundamental scientific principles, including early versions of our temperature equilibration curriculum unit. Indeed, in a later edition of the same project, we did teach eight grade students (from a marginalized, immigrant population) how to think about exponential growth (in the form of spreading rumors; “each one tells two”).

The Nitty Gritty of Programming

Finally, I want to further demystify the work I did building my little COVID exploration microworld. Just below is the database for California, as it exists today. The columns are, in the sequence specified by the Key : date, cases of infection, deaths, and the number of people who recovered. The “database” is just text typed or pasted into a “box.” “X” represents missing data, all in the category of recovered cases, which I found for the US but never managed to find for CA.

Next, I’ll show the complete code for drawing one graph, revealed in stages. The first panel, below, shows the top level. Just plot a certain set of data points, which appears here as a black box.

The next panel shows the black box opened (just click on it) to reveal that what’s plotted are the log values of each element of another black box of data.

The third panel shows that black box opened up, revealing a data set consisting of yet another (black box) dataset, but scaled by a factor of 11.5. That happens to be exactly the factor that I needed to scale CA data in order to match with US data right at the beginning of my graphs.

Finally, with everything revealed, you can see that the input to the whole process is the second column of the CA COVID database, which is the number of reported infections.

That’s the whole thing. The program to draw my COVID graphs is four commands in a nested sequence. Plot-data is a command the graphing utility understands. Log-all and scale-all are tiny programs I wrote to apply the named function to all the elements of a list of numbers. Column is an in-built primitive function of the system.

So, what’s the world like when every citizen can program to the (very modest) level involved in this example? How will citizens then relate to the data-filled world in which they find themselves? What will schools be like? How will mathematics and science be taught differently? What different topics will be covered, how will basic conceptions of math and science change, and what different kinds of activities will students be engaged in—such as real-world data inquiries and modeling important scientific phenomena? That’s computational literacy. You can read some of my own expectations and hopes in diSessa (2000) and diSessa (2018).

I thank Yeping Li, Geoff Saxe, and Melinda diSessa for helpful comments on earlier drafts.

diSessa, A. A. (2000). Changing Minds: Computers, Learning, and Literacy . Cambridge, MA: MIT Press.

diSessa, A. A. (2008). Can students re-invent fundamental scientific principles?: Evaluating the promise of new-media literacies. In T. Willoughby, & E. Wood (Eds.), Children’s learning in a digital world (pp. 218-248). Oxford, UK: Blackwell Publishing.

diSessa, A. A. (2017). Conceptual change in a microcosm: Comparative analysis of a learning event. Human Development , 60 (1), 1-37. doi: 10.1159/000469693

diSessa, A. A. (2018). Computational literacy and “The Big Picture” concerning computers in mathematics education. Mathematical Thinking and Learning , 20 (1), 3-31. (Special issue on “Computational Thinking and Mathematics Learning.”) doi: 10.1080/10986065.2018.1403544

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Li, Y., Schoenfeld, A.H., diSessa, A.A. et al. Computational Thinking Is More about Thinking than Computing. Journal for STEM Educ Res 3 , 1–18 (2020). https://doi.org/10.1007/s41979-020-00030-2

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The task-based approach to teaching critical thinking for computer science students.

1. Introduction

• “critical thinking” + teaching + “computer science”,
• “critical thinking” + teaching + “business informatics”, and
• “critical thinking” + teaching + “information systems management”

Research Question

• The proposed approach has a positive impact on the development of students’ perceived CT cognitive skills and on their ability to transfer these skills to other tasks and domains.
• The proposed approach has a positive impact on the development of students’ perceived CT dispositions.

2. Theoretical Background

2.1. definition of critical thinking, 2.2. challenges of teaching critical thinking.

• planning, e.g., “the selection of appropriate strategies, allocation of available resources”;
• monitoring, e.g., “checking task information to validate comprehension, allocating attention to important ideas, and pointing out informational ambiguities”;
• evaluating, e.g., “evaluating one’s reasoning, goals and conclusions as well as making revisions when necessary”.

2.3. Pedagogical Approaches in HE and the Promotion of CT

• Learning general principles and concepts facilitates their transfer to dissimilar problems, as it creates more flexible mental representations;
• Abstract generalized principles and the rules of CT need to be linked to varied examples and potential applications in different contexts;
• Practices of metacognitive strategies such as self-monitoring, self-awareness, and self-explanations best stimulate learners and promote the transferability of CT skills.

2.4. The Proposed Educational Approach

• Introduction of subject-specific concepts using the perceptional approach;
• Processing of a task/problem by students (individually or in group);
• Discussion of the problem-solving and thinking process and results using Socratic questioning and dialogue;
• Introduction of general CT principles and aspects or reminder of them if they have already been introduced.

3. Methodology

3.1. research design, 3.2. educational experiment.

• The master’s degrees of these modules are consecutive degrees to the bachelor’s degree in CS at the University of Applied Sciences Emden/Leer (Germany);
• The intended learning outcomes and topics of these modules offered an opportunity to promote CT in addition to teaching subject-specific skills;
• The modules included parts with identical intended learning outcomes and topics and were taught using the same teaching materials. Consequently, the collected data were categorized and analyzed together in order to measure the impact of the proposed approach.

3.2.1. Teaching in the Experiment

• Analyze the structure and quality of scientific publications based on the given acceptance criteria for scientific conferences and journals. Apply the quality criteria of conferences and scientific journals to evaluate them. (Students were presented with both published articles and those manuscripts that were submitted but unaccepted in order to demonstrate the difference between high-quality and low-quality texts.)
• Critically examine your work on the bachelor’s thesis and its results. Answer the following questions: “How did you organize your writing process?” “What would you do differently today and why?” “What have you done well and would not change?” “What would I advise myself to do better?” (The focus of this task was on the CT skill ‘self-regulation’ and the CT dispositions ‘self-confidence’ and ‘cognitive maturity’).
• Describe the CT aspects that you used in your bachelor’s thesis and the aspects you would use in your bachelor’s thesis if you had to do it again. What would you have done differently when working on your bachelor’s thesis if you had known the CT principles learned in this module?
• Use creative thinking methods in groups to generate innovative ideas in the field of cyber–physical systems (only the ‘Innovation Management’ module).
• Analyze household electricity consumption, investigate how and where energy recovery can be used, identify challenges and describe how to address them. Describe your solution and your personal point of view on the topic, both in writing and orally (both modules).
• Analyze benefits and drawbacks of new technologies, e.g., mobile technology, Internet of things technology.

3.3. Instruments

• ‘Never’ = 1; ‘Rarely’ = 2; ‘Occasionally’ = 3; ‘Usually’ = 4; ‘Often’ = 5; ‘Frequently’ = 6; ‘Always’ = 7;
• ‘Strongly Disagree’ = 1; ‘Disagree’ = 2; ‘Slightly Disagree’ = 3; ‘Neither Agree nor Disagree’ = 4; ‘Slightly Agree’ = 5; ‘Agree’ = 6; ‘Strongly Agree’ = 7

3.4. Data Collection and Analysis

4.1. students’ reflections on the development of skills, 4.1.1. c1: what is ct for me, 4.1.2. c2: what do i do to solve a problem, 4.1.3. c3: what did i learn in the module.

• Subject-specific skills (73%);
• Transferable skills (64%);
• Problem-solving skills (55%);
• Thinking skills (46%);
• Metacognitive skills (28%).

4.1.4. C4: How Did My Understanding and Skills Change?

4.2. students’ self-assessment of critical thinking skills and dispositions, 5. discussion, 5.1. students’ understanding of ct and the problem-solving process, 5.2. what students learned, 5.3. change in students’ understanding and skills, 5.4. study limitations, 5.5. future works, 6. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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• Nosich, G.M. Learning to Think Things through: A Guide to Critical Thinking across the Curriculum ; Pearson: Upper Saddle River, NJ, USA, 2009. [ Google Scholar ]
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Mäkiö, E.; Mäkiö, J. The Task-Based Approach to Teaching Critical Thinking for Computer Science Students. Educ. Sci. 2023 , 13 , 742. https://doi.org/10.3390/educsci13070742

Mäkiö E, Mäkiö J. The Task-Based Approach to Teaching Critical Thinking for Computer Science Students. Education Sciences . 2023; 13(7):742. https://doi.org/10.3390/educsci13070742

Mäkiö, Elena, and Juho Mäkiö. 2023. "The Task-Based Approach to Teaching Critical Thinking for Computer Science Students" Education Sciences 13, no. 7: 742. https://doi.org/10.3390/educsci13070742

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• Published Mar 1, 2023

Why students need Computer Science to succeed

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As technology continues to evolve at an accelerated pace, transforming the way we live and work in the process, we find ourselves navigating the challenges of an always-changing digital landscape. Understanding the principles of computing is quickly becoming an essential skill. It provides people with a keen understanding of how technology impacts their lives, empowers them to become full participants in society, and unlocks a wide range of career opportunities. This is especially true for today’s students, who will rely on computing skills throughout their lives, making it necessary for them to have opportunities to learn Computer Science (CS).

A report by LinkedIn and Microsoft revealed that 149 million new digital jobs will be created by 2025 in fields such as software development, data analysis, cybersecurity, and AI. However, education cannot currently meet the growing demand for people with CS skills. As of October 2022, only 33% of technology jobs worldwide were filled by the adequately skilled. And by 2030, the global shortage of tech workers will represent an $8.5 trillion loss in annual revenue, according to research cited by the International Monetary Fund i .

Around the world, technology is opening up opportunities for new ways to solve the challenges and needs of businesses and organizations, everything from technology-focused [industries] to agriculture, healthcare, financial services, transportation and so many more. They’re all struggling to find the talent they need to fill many of the jobs.” Christina Thoresen, Director of Worldwide Education Industry Sales Strategy at Microsoft

A growing interest in CS curricula

Learning coding and software development, two key parts of CS, has been shown to improve students’ creativity, critical thinking, math, and reasoning skills ii . CS skills like problem-solving iii and planning iv are transferable and can be applied across other subjects. A 2020 study examining the effects of CS courses on students’ academic careers in the United States showed that they have a significant impact on the likelihood of enrolling in college v . Moreover, CS can be useful for many courses and degrees including biology, chemistry, economics, engineering, geology, mathematics, materials science, medicine, physics, psychology, and sociology vi . 

CS curricula that are relevant and engaging provide an additional benefit in that they attract traditionally marginalized groups and girls and empower those with lower access to technological resources to develop high value skills, and unlock new and exciting career opportunities. It is also worth noting that due to enduring talent shortages, CS-related fields consistently offer above-average pay and have the fastest-growing wages vii .

How Microsoft supports CS implementation

 Microsoft has been helping educational institutions around the world develop rich CS curricula that empower all students with the skills they need to confidently transition from classroom to career. By creating content that is meaningful and engaging for all students, as well as helping promote equal access to CS in school, Microsoft is fulfilling its commitment to making learning more inclusive and equitable. One of the principal resources for this is Microsoft’s Computer Science Guide (MCSG) , a comprehensive CS framework that includes:

• An implementation plan
• Training for educators
• Lesson and project suggestions
• Practical guidance for coding activities
• Certification

An important part of building up students’ CS capabilities is to engage learners as early as possible, which encourages and supports creative expression and the development of computational thinking skills. However, CS curriculums at the national level often focus on ICT or simple coding exercises and offer little in terms of immersive, hands-on experiences that feel relevant, authentic, and inclusive. The MCSG was made to engage students of all ages through a learner-centric curriculum using constructivism, hands-on activities, problem-solving, and inquiry-based approaches that are often linked to real-world challenges viii .

CS curriculum design can also help address a well-documented gender divide ix by engaging all students as early as primary school using relevant and meaningful content. It can ensure that all students have access to CS courses based on their needs and abilities, regardless of socio-economic status, race, ethnicity, or special learning needs. Additionally, as students are likely to encounter changes in technology that are difficult to imagine over the course of their education, another key goal of the MCSG is to be future-proof by incorporating subjects that are likely to be highly relevant well into the future.

Computer science skills are critical to succeed in today’s economy, but too many students – especially those from diverse backgrounds and experiences – are excluded from computer science. That’s why we’ve created a new resource guide which we hope will help teachers build inclusive computer science education programs.” Naria Santa Lucia, General Manager of Digital Inclusion and Community Engagement for Microsoft Philanthropies

Georgia Ministry of Education develops national CS program

In 2022, the Ministry of Education and Science of Georgia launched a pilot program to test how the Microsoft CS Curriculum could be integrated into primary classes as part of a national campaign to introduce broader CS concepts and computational thinking to K-12 learning. The pilot project focused on two ICT teachers and was reviewed by volunteer educators from other cities. An advisory board was formed consisting of experts from the National Curriculum Department.

The process involved translating the Foundation Phase of the Microsoft CS Curriculum Toolkit into Georgian, as well as weekly meetings to discuss progress. In the end, the teachers designed two curriculums for the 2nd and 3rd grades, and the project team made a recommendation for a completely new framework concept that considered the existing National Curriculum context, the integration of the Microsoft CS Curriculum Framework, as well as additional concepts from the Computer Science Teachers Association.

Learn more about computer science with Microsoft

It is no longer possible to ignore the critical importance of CS skills to students whose lives are going to revolve around their ability to understand and engage with technology, both at work and in their day-to-day. At Microsoft Education, our goal is to empower every learner on the planet to achieve more. That is why we are working together with governments and education leaders around the world to implement CS in schools and ensure that students feel included, supported, and empowered to confidently follow their passions and achieve great success both in their careers and in life.

• Start building a CS curriculum using the Microsoft Computer Science Curriculum Toolkit .
• To inspire a STEM passion in K-12 learners and teach them how to code with purpose, use Minecraft’s Computer Science Progression .
• Find out how the Microsoft TEALS Program can help you create access to equitable, inclusive CS education and learn more about building inclusive economic growth .
• Enlist one of Microsoft’s Global Training Partners to support your educators to incorporate CS into their curriculum and teaching practices.

i https://www.imf.org/en/Publications/fandd/issues/2019/03/global-competition-for-technology-workers-costa   

ii https://codeorg.medium.com/cs-helps-students-outperform-in-school-college-and-workplace-66dd64a69536   

iii Can Majoring in CS Improve General Problem-solving Skills?, ACM, Salehi et al., 2020   

iv The effects of coding on children’s planning and inhibition skills, Computers & Education, Arfé et al., 2020   

v http://www.westcoastanalytics.com/uploads/6/9/6/7/69675515/longitudinal_study_-_combined_report_final_3_10_20__jgq_.pdf   

vi https://www.hereford.ac.uk/explore-courses/courses/computer-science/   

vii https://www.thebalancemoney.com/average-salary-information-for-us-workers-2060808   

viii Kotsopoulos, D., Floyd, L., Khan, S., Namukasa, I.K., Somanath, S., Weber, J. & Yiu, C. (2017) A Pedagogical Framework for Computational Thinking. Digital Experiences in Mathematics Education vol. 3, pages 154–171(2017)     

ix https://www.theguardian.com/careers/2021/jun/28/why-arent-more-girls-in-the-uk-choosing-to-study-computing-and-technology  

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Why You Should Integrate Computational Thinking Into Your Curriculum

• Computer Science & Computational Thinking

Computational thinking is the problem-solving skill of the digital world. It’s powerful when integrated into the curriculum because students engage in experiential learning of content-related problems, such as how to identify the tone of a story or how to best address pollution in their local area.

Students sharpen their critical thinking skills by working through all the considerations that a problem presents. They practice inquiry-based thinking by imagining and molding problems to be solved. They sharpen their logical thinking by outlining specific rules to be followed to solve their problem. Practicing and combining these three types of thinking to solve problems is what students have to gain. Thinking first, computing second.

I find the most compelling reason for CT integration isn’t preparing students for the jobs of tomorrow, or even the emphasis on the computation , but rather the thinking . CT is not the future of education,  it’s the now !

Despite the importance of CT in K-12, it can be intimidating for educators to implement. It certainly was for me. Initially, I thought, “Why would my students need to learn about computing in Spanish class?” I didn’t see its relevance to the content.

I decided that I wanted to try to create a Spanish lesson integrating CT to get a better understanding of what teachers face when first learning CT. This article attempts to answer all the questions I initially had in plain terms. 

What even is CT?

While there are many different definitions, they all center on the following core idea:  Individuals and organizations use massive amounts of data to make decisions at every turn in life. That data can be internet searches, purchase histories, trip destinations — absolutely anything. To make sense of that data, they create algorithms, which are rules a computer (or a human) follows. This is powerful stuff .

As society plunges further into the Information Age, we use computing to solve our problems. This helps us understand how to best use computing to better solve problems as they arise. Computers need instructions, and this is where CT comes into play.

In other words, people create rules, based on data, which we give to a computer (or human) so that it can solve problems or reach decisions for us.

It’s problem solving and communication. These are skills students of all ages in all subjects need, from kinders deciding where to best put a school garden to high schoolers creating chatbots that answer questions about Macbeth.

[ Click on the image below to open the computational thinking infographic. ]

Why invest effort in CT?

Asking questions to logically organize and analyze data, creating detailed rules for others to follow, and engaging in trial and error deepens content learning. These skills teach tenacity, tolerance for ambiguity and complexity, and teamwork. If this sounds familiar, chances are you’re already promoting these in your classroom!

The “thinking” in CT is worth the investment of time and energy because thinking is a skill applicable to all subjects, which is why integrating CT into content across grade levels is vital.

According to Code.org’s 2021 report,  State of Computer Science Education , just 51% of high schools offered computer science, up from 35% in 2018. It also states that 31 states had adopted 50 computer science education policies in the prior year. While that’s a start, it’s nowhere near enough.

The fact is, all students need an education that will prepare them for the world they’re walking into. Not only for the sake of jobs or furthering economic development, but also so they will know how to be good digital citizens, recognize misinformation, and create better lives for themselves and those around them.  

Computational thinking is a literacy that is desperately needed in K-12 education.

Why should I integrate CT into my class?

It’s important on a societal scale, but also in your classroom with your students.

There’s the old saying that you don’t really understand something until you can teach it. That’s CT. I’ve always assumed it meant teaching people, but now I know it includes computers. Teaching computers what exactly? How to solve problems!

In fourth grade math, your students could think about how to move a robot car successfully along a path . In eighth grade science, they might be finding the best home for oyster castles in the local watershed. In high school biology, they might be collecting, logging, and comparing DNA sequences generated from algorithms .  

The connection between these various activities is that they all involve problem-solving and computing. Designing and implementing a plan to reduce food waste in your immediate environment is leagues more memorable than learning the theory of it. Experience is the best teacher.

Like with language, the earlier students learn a skill, the more proficient they’ll become. As students grow more comfortable with the skills and language of CT, they’ll be able to solve problems at larger scales. Today it might be how to reduce food waste in school; tomorrow it could be finding solutions to global food security issues.

Your students’ learning is deepened and made more memorable when integrating CT into your class.  

How do I integrate CT into my class?

If you’re a teacher, your students already learn CT skills, just not packaged as the CT process. For example, middle school algebra students learn to move from solving specific math problems to deriving general formulas and equations. This is called abstraction and is a core element of CT.

Another example is students discussing Macbeth. They have to read, understand and analyze Macbeth. This is decomposition and pattern recognition, which are other core elements of CT. 

Why not take it a step further? Students could create a chatbot to quiz their classmates by creating questions, crafting answers, and designing rules for the chatbot to follow. You need a deep understanding of Macbeth to do all of that!

I often found myself asking, if it’s called CT, won’t students need computers? The answer is not necessarily! There are plenty of unplugged CT activities where students can create algorithms. Another strength of CT is that it can be integrated into any subject area — plugged or unplugged! 

Where do I start?

Here are three good resources for you:

• ISTE Compuational Thinking Competencies
• ISTE computational thinking infographic
• ISTE computational thinking blog posts

Learning to think computationally is the start of a journey of seeing society’s relationship with technology more clearly, and it’s a skill that will help students change society for the better.

Nick Pinder is a project manager of computational thinking and higher education projects at ISTE. Nick is interested in the promotion of computational thinking and its intersection with language instruction specifically and the humanities in general.

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CS for CA News & Updates

Computer science skills: computational thinking explained.

It’s a common misconception that computer science (CS) is only applicable to people working in a technology or STEM careers. However, skills learnt through CS are used in our everyday lives, and in a variety of subjects.

One of these skills is known as computational thinking (CT). 

What is computational thinking?

There are many problem-solving skills involved in computer science, including those needed to design, develop, and debug software. Computational thinking is a way of describing these skills.

Computational thinking refers to the thought processes involved in defining a problem and its solution so that the solution can be expertly carried out by a computer. We don't need computers to engage in computational thinking, but CT can leverage the power of computers to solve a problem.

Computational thinking helps build these skills:

• Decomposition – the process of breaking down a complex problem into smaller parts that are more manageable, and helps us see problems as less overwhelming.
• Abstraction – identifying common features, recognizing patterns, and filtering out what we don’t need. 
• Algorithmic Thinking – designing a set of steps to accomplish a specific task. 
• Debugging and Evaluation – testing and refining a potential solution, and ensuring it’s the best fit for the problem.

These skills relate to critical thinking and problem solving skills across different subject matter, highlighting how concepts of computing can be combined with other fields of study to assist in problem-solving.

Computational thinking is a way of describing the many problem solving skills involved in computer science, including those needed to design, develop, and debug software. However, computer science is more than just skills, it also includes concepts about the Internet, networking, data, cybersecurity, artificial intelligence, and interfaces. Computational thinking can be relevant beyond computer science, overlapping with skills also used in other STEM subjects, as well as the arts, social sciences, and humanities.

Why is computational thinking important? 

Computational thinking can apply these problem-solving techniques to a variety of subjects. For example, CT is established as one of the Science and Engineering Practices in the Next Generation Science Standards , and can also be found in several math state standards . Computational thinking also overlaps with skills used in other STEM subjects, as well as the arts, social sciences, and humanities. Computational thinking encourages us to use the power of computing beyond the screen and keyboard. 

It can also allow us to advance equity in computer science education...

By centering the problem-solving skills that are at the heart of computer science, we can promote its integration with other subject areas, and expose more students to the possibilities of computer science. 

Not only that, but computational thinking also opens the door for us to examine the limitations and opportunities of technology as it’s being developed. We’re able to analyze who is creating technology and why, as well as think critically about the ways in which it can impact society. 

Want to learn more about computational thinking?

To learn more about computational thinking, check out the resources:

• This framework for CS for K-12 places CT at the core of its practices and is what the California standards are based on. 
• Part of the British Computing Society, Computing at School put forth resources to assist teachers in the UK in embedding  CT in their classrooms. 
• This is one of the earliest definitions of CT for educators, and noteworthy for its inclusion of certain dispositions as being essential for effective CT.  
• The developers of Scratch divide CT into concepts, practices, and perspectives, and focus on the expressive and creative nature of computing. 
• Instead of focusing solely on standards for students, ISTE  compiled a set of knowledge, skills, and mindsets needed for educators to be successful in integrating  CT across the K-12 content areas and grade bands.  
• Bebras began as an international competition to promote CT for students, regardless of programming experience. It is now increasingly being used as a form of CT assessment. 

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• What Is Critical Thinking? | Definition & Examples

What Is Critical Thinking? | Definition & Examples

Published on May 30, 2022 by Eoghan Ryan . Revised on May 31, 2023.

Critical thinking is the ability to effectively analyze information and form a judgment .

To think critically, you must be aware of your own biases and assumptions when encountering information, and apply consistent standards when evaluating sources .

Critical thinking skills help you to:

• Identify credible sources
• Evaluate and respond to arguments
• Assess alternative viewpoints
• Test hypotheses against relevant criteria

Table of contents

Why is critical thinking important, critical thinking examples, how to think critically, other interesting articles, frequently asked questions about critical thinking.

Critical thinking is important for making judgments about sources of information and forming your own arguments. It emphasizes a rational, objective, and self-aware approach that can help you to identify credible sources and strengthen your conclusions.

Critical thinking is important in all disciplines and throughout all stages of the research process . The types of evidence used in the sciences and in the humanities may differ, but critical thinking skills are relevant to both.

In academic writing , critical thinking can help you to determine whether a source:

• Is free from research bias
• Provides evidence to support its research findings
• Considers alternative viewpoints

Outside of academia, critical thinking goes hand in hand with information literacy to help you form opinions rationally and engage independently and critically with popular media.

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Critical thinking can help you to identify reliable sources of information that you can cite in your research paper . It can also guide your own research methods and inform your own arguments.

Outside of academia, critical thinking can help you to be aware of both your own and others’ biases and assumptions.

Academic examples

However, when you compare the findings of the study with other current research, you determine that the results seem improbable. You analyze the paper again, consulting the sources it cites.

You notice that the research was funded by the pharmaceutical company that created the treatment. Because of this, you view its results skeptically and determine that more independent research is necessary to confirm or refute them. Example: Poor critical thinking in an academic context You’re researching a paper on the impact wireless technology has had on developing countries that previously did not have large-scale communications infrastructure. You read an article that seems to confirm your hypothesis: the impact is mainly positive. Rather than evaluating the research methodology, you accept the findings uncritically.

Nonacademic examples

However, you decide to compare this review article with consumer reviews on a different site. You find that these reviews are not as positive. Some customers have had problems installing the alarm, and some have noted that it activates for no apparent reason.

You revisit the original review article. You notice that the words “sponsored content” appear in small print under the article title. Based on this, you conclude that the review is advertising and is therefore not an unbiased source. Example: Poor critical thinking in a nonacademic context You support a candidate in an upcoming election. You visit an online news site affiliated with their political party and read an article that criticizes their opponent. The article claims that the opponent is inexperienced in politics. You accept this without evidence, because it fits your preconceptions about the opponent.

There is no single way to think critically. How you engage with information will depend on the type of source you’re using and the information you need.

However, you can engage with sources in a systematic and critical way by asking certain questions when you encounter information. Like the CRAAP test , these questions focus on the currency , relevance , authority , accuracy , and purpose of a source of information.

When encountering information, ask:

• Who is the author? Are they an expert in their field?
• What do they say? Is their argument clear? Can you summarize it?
• When did they say this? Is the source current?
• Where is the information published? Is it an academic article? Is it peer-reviewed ?
• Why did the author publish it? What is their motivation?
• How do they make their argument? Is it backed up by evidence? Does it rely on opinion, speculation, or appeals to emotion ? Do they address alternative arguments?

Critical thinking also involves being aware of your own biases, not only those of others. When you make an argument or draw your own conclusions, you can ask similar questions about your own writing:

• Am I only considering evidence that supports my preconceptions?
• Is my argument expressed clearly and backed up with credible sources?
• Would I be convinced by this argument coming from someone else?

If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.

• ChatGPT vs human editor
• ChatGPT citations
• Is ChatGPT trustworthy?
• Using ChatGPT for your studies
• What is ChatGPT?
• Chicago style
• Paraphrasing

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• Self-plagiarism
• Avoiding plagiarism
• Academic integrity
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• Common knowledge

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

Critical thinking skills include the ability to:

You can assess information and arguments critically by asking certain questions about the source. You can use the CRAAP test , focusing on the currency , relevance , authority , accuracy , and purpose of a source of information.

Ask questions such as:

• Who is the author? Are they an expert?
• How do they make their argument? Is it backed up by evidence?

A credible source should pass the CRAAP test  and follow these guidelines:

• The information should be up to date and current.
• The author and publication should be a trusted authority on the subject you are researching.
• The sources the author cited should be easy to find, clear, and unbiased.
• For a web source, the URL and layout should signify that it is trustworthy.

Information literacy refers to a broad range of skills, including the ability to find, evaluate, and use sources of information effectively.

Being information literate means that you:

• Know how to find credible sources
• Use relevant sources to inform your research
• Understand what constitutes plagiarism
• Know how to cite your sources correctly

Confirmation bias is the tendency to search, interpret, and recall information in a way that aligns with our pre-existing values, opinions, or beliefs. It refers to the ability to recollect information best when it amplifies what we already believe. Relatedly, we tend to forget information that contradicts our opinions.

Although selective recall is a component of confirmation bias, it should not be confused with recall bias.

On the other hand, recall bias refers to the differences in the ability between study participants to recall past events when self-reporting is used. This difference in accuracy or completeness of recollection is not related to beliefs or opinions. Rather, recall bias relates to other factors, such as the length of the recall period, age, and the characteristics of the disease under investigation.

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Ryan, E. (2023, May 31). What Is Critical Thinking? | Definition & Examples. Scribbr. Retrieved September 10, 2024, from https://www.scribbr.com/working-with-sources/critical-thinking/

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Thinking critically on critical thinking: why scientists’ skills need to spread

Lecturer in Psychology, University of Tasmania

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Rachel Grieve does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Tasmania provides funding as a member of The Conversation AU.

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MATHS AND SCIENCE EDUCATION: We’ve asked our authors about the state of maths and science education in Australia and its future direction. Today, Rachel Grieve discusses why we need to spread science-specific skills into the wider curriculum.

When we think of science and maths, stereotypical visions of lab coats, test-tubes, and formulae often spring to mind.

But more important than these stereotypes are the methods that underpin the work scientists do – namely generating and systematically testing hypotheses. A key part of this is critical thinking.

It’s a skill that often feels in short supply these days, but you don’t necessarily need to study science or maths in order gain it. It’s time to take critical thinking out of the realm of maths and science and broaden it into students’ general education.

What is critical thinking?

Critical thinking is a reflective and analytical style of thinking, with its basis in logic, rationality, and synthesis. It means delving deeper and asking questions like: why is that so? Where is the evidence? How good is that evidence? Is this a good argument? Is it biased? Is it verifiable? What are the alternative explanations?

Critical thinking moves us beyond mere description and into the realms of scientific inference and reasoning. This is what enables discoveries to be made and innovations to be fostered.

For many scientists, critical thinking becomes (seemingly) intuitive, but like any skill set, critical thinking needs to be taught and cultivated. Unfortunately, educators are unable to deposit this information directly into their students’ heads. While the theory of critical thinking can be taught, critical thinking itself needs to be experienced first-hand.

So what does this mean for educators trying to incorporate critical thinking within their curricula? We can teach students the theoretical elements of critical thinking. Take for example working through [statistical problems](http://wdeneys.org/data/COGNIT_1695.pdf](http://wdeneys.org/data/COGNIT_1695.pdf) like this one:

In a 1,000-person study, four people said their favourite series was Star Trek and 996 said Days of Our Lives. Jeremy is a randomly chosen participant in this study, is 26, and is doing graduate studies in physics. He stays at home most of the time and likes to play videogames. What is most likely? a. Jeremy’s favourite series is Star Trek b. Jeremy’s favourite series is Days of Our Lives

Some critical thought applied to this problem allows us to know that Jeremy is most likely to prefer Days of Our Lives.

Can you teach it?

It’s well established that statistical training is associated with improved decision-making. But the idea of “teaching” critical thinking is itself an oxymoron: critical thinking can really only be learned through practice. Thus, it is not surprising that student engagement with the critical thinking process itself is what pays the dividends for students.

As such, educators try to connect students with the subject matter outside the lecture theatre or classroom. For example, problem based learning is now widely used in the health sciences, whereby students must figure out the key issues related to a case and direct their own learning to solve that problem. Problem based learning has clear parallels with real life practice for health professionals.

Critical thinking goes beyond what might be on the final exam and life-long learning becomes the key. This is a good thing, as practice helps to improve our ability to think critically over time .

Just for scientists?

For those engaging with science, learning the skills needed to be a critical consumer of information is invaluable. But should these skills remain in the domain of scientists? Clearly not: for those engaging with life, being a critical consumer of information is also invaluable, allowing informed judgement.

Being able to actively consider and evaluate information, identify biases, examine the logic of arguments, and tolerate ambiguity until the evidence is in would allow many people from all backgrounds to make better decisions. While these decisions can be trivial (does that miracle anti-wrinkle cream really do what it claims?), in many cases, reasoning and decision-making can have a substantial impact, with some decisions have life-altering effects. A timely case-in-point is immunisation.

Pushing critical thinking from the realms of science and maths into the broader curriculum may lead to far-reaching outcomes. With increasing access to information on the internet, giving individuals the skills to critically think about that information may have widespread benefit, both personally and socially.

The value of science education might not always be in the facts, but in the thinking.

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The Critical Computer Science Principles Every Strategic Leader Needs to Know

In an AI-world, leaders who speak technology’s language gain an edge. But that doesn’t mean every manager needs a computer science degree.

A handle on a handful of basics goes a long way toward preparing strategic leaders for today’s reality: Almost all businesses now touch technology—some more so than others.

“Every company today needs to think of themselves as a tech company,” says Andy Wu, the Arjun and Minoo Melwani Family Associate Professor of Business Administration at Harvard Business School. “Whether you’re in retailing or you’re a law firm or a real estate company, technology is an important part of how businesses operate, and that can only increase going forward.”

“Increasingly, the tech architectures inside firms are a source of competitive advantage.”

In a new industry and background note written with HBS research associate Matt Higgins, the authors distill the fundamentals of digital technology that can help leaders achieve their strategic priorities.

It’s vital for managers to engage with some of the basics of computer science because “they give people a framework to think about the direction that technology will evolve and the opportunities for value creation,” Wu says. Not only that, but “increasingly, the tech architectures inside firms are a source of competitive advantage.”

Wu suggests executives study up on these five computer science principles—and leave the rest to their tech teams.

1. Think in the abstract

One of the ways managers can avoid getting caught up in bits and bytes and microprocessor architectures is to embrace the concept of abstraction.

Abstraction means substituting a simplified model for the full and technically complex reality. It acts as a filter, enabling “MBAs interested in technology to skip the circuit-design courses,” Wu says.

“Generative AI chatbots like ChatGPT and the motion gestures control in the Apple Vision Pro continue to expand who can use a computer and what you can use it for.”

Wu shares how his father, who studied computer science in college several decades ago, used punch cards to instruct the computer—an early method that today’s engineers can understand thinking abstractly. The computer would convert the punch cards into a series of zeros and ones that it could understand. Over time, punch cards gave way to the command line, allowing users to give instructions in plain language—but the underlying mechanism was the same. After the command line came MS-DOS, then Windows 3.0, and so on.

“So, essentially, we added a layer of abstraction onto the punch card. Just adding these layers of abstractions completely changed who could use a computer and what you could use it for, even though the computer is intrinsically the same thing,” says Wu. “Generative AI chatbots like ChatGPT and the motion gestures control in the Apple Vision Pro continue to expand who can use a computer and what you can use it for.”

2. Platforms are power

In the beginning, Jeff Bezos built a website that sold books from its own inventory. Today, Amazon is a classic example of “platformization”: The company grew from an online bookstore into a vast technological hub that provides logistics and advertising to third-party retailers and public cloud services underlying much of the internet today. Platforms attract developers and other third parties, which in turn broaden their reach and influence.

Wu points to the Apple iPhone as another example of this phenomenon. While Steve Jobs originally intended to limit the iPhone to just Apple’s own applications, the iPhone evolved into a platform with the introduction of the App Store and its ecosystem of services. Eight of the 10 most valuable companies in the world are currently pursuing platform strategies, Wu says.

Ultimately, platform strategies lead to the greatest outcome in business, “which is what we call a winner-take-all outcome,” Wu adds. This is because network effects allow platforms to grow exponentially, attracting ever more users and partners and eventually crowding out competitors.

3. Think like a sandwich

From the computer keyboard and user interface to the smallest circuit, computer systems consist of layers. Each layer has a specific job to do in recognizing and then communicating the user’s commands. Understanding the various levels can help managers focus on the big concepts without getting mired in minutiae.

Technology systems consist of five key layers: assembly language/machine code, instruction set, operating system, middleware, and application. Each layer presents distinct business opportunities for establishing strategic differentiation.

Companies can leverage their position within layers to grow larger by pursuing strategies for integration (expanding into other areas) or foreclosure (blocking competitors from using the platform). Over time, Microsoft has pursued both integration and foreclosure strategies with its Microsoft Windows operating system, Wu says.

Companies that are new to a market don’t initially have the same market power to integrate or foreclose, so they are left with structuring opportunities around an “insert and mediate” strategy. Typically, Wu writes, insert and mediate works best when the new entrant “can offer something to both sides”—an example being Sun Microsystems’ development of Java.

4. The two layers that run the show

As in society, technology systems depend on a set of clearly defined rules to operate quickly and effectively. Two layers—the instruction set architecture and the operating system—shoulder much of the responsibility for determining both what a platform can do and how it should do it.

Most people typically relate to operating systems as a gateway that distinguishes one computer from another. In reality, the operating system is more like a chief executive in that it allocates resources and establishes and controls workflow. In the simplest sense, it tells the computer how to get the work done.

Instruction set architectures, on the other hand, are the authoritative source for what functions a computer can handle and what services it can offer to users.

The operating system and instruction set architecture are critical for leaders to know because they help determine the shape of an organization’s technology strategy, including the nature of vendor relationships and other variables.

5. Applications: Abstraction’s highest level

For end users, the application layer opens up worlds of possibilities. Applications represent the ultimate abstraction—they allow users to perform specific tasks without ever contemplating the complex interactions taking place in the actions underneath.

“Today, it is fair to say that Chrome is both: an application capable of running on most operating systems, and an operating system that runs the Chrome suite of software and extensions when it is configured with ChromeOS as the user-facing operating system.”

The concept of an application has changed dramatically over time. Initially, applications performed single tasks (such as spreadsheets) and only worked on specific machines (such as the Apple II). Today, applications are multifunctional and complex, often blurring the lines between various layers.

One example is Google Chrome. Initially considered a tool for browsing the web, Wu writes, “Today, it is fair to say that Chrome is both: an application capable of running on most operating systems, and an operating system that runs the Chrome suite of software and extensions when it is configured with ChromeOS as the user-facing operating system.”

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• How Humans Outshine AI in Adapting to Change

Feedback or ideas to share? Email the Working Knowledge team at [email protected] .

Image: Image created by HBSWK using asset from AdobeStock/beast01

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Home > Blog > Tips for Online Students > Why Is Critical Thinking Important and How to Improve It

Tips for Online Students , Tips for Students

Why Is Critical Thinking Important and How to Improve It

Updated: July 8, 2024

Published: April 2, 2020

Why is critical thinking important? The decisions that you make affect your quality of life. And if you want to ensure that you live your best, most successful and happy life, you’re going to want to make conscious choices. That can be done with a simple thing known as critical thinking. Here’s how to improve your critical thinking skills and make decisions that you won’t regret.

What Is Critical Thinking?

Critical thinking is the process of analyzing facts to form a judgment. Essentially, it involves thinking about thinking. Historically, it dates back to the teachings of Socrates , as documented by Plato.

Today, it is seen as a complex concept understood best by philosophers and psychologists. Modern definitions include “reasonable, reflective thinking focused on deciding what to believe or do” and “deciding what’s true and what you should do.”

The Importance Of Critical Thinking

Why is critical thinking important? Good question! Here are a few undeniable reasons why it’s crucial to have these skills.

1. Critical Thinking Is Universal

Critical thinking is a domain-general thinking skill. What does this mean? It means that no matter what path or profession you pursue, these skills will always be relevant and will always be beneficial to your success. They are not specific to any field.

2. Crucial For The Economy

Our future depends on technology, information, and innovation. Critical thinking is needed for our fast-growing economies, to solve problems as quickly and as effectively as possible.

3. Improves Language & Presentation Skills

In order to best express ourselves, we need to know how to think clearly and systematically — meaning practice critical thinking! Critical thinking also means knowing how to break down texts, and in turn, improve our ability to comprehend.

4. Promotes Creativity

By practicing critical thinking, we are allowing ourselves not only to solve problems but also to come up with new and creative ideas to do so. Critical thinking allows us to analyze these ideas and adjust them accordingly.

5. Important For Self-Reflection

Without critical thinking, how can we really live a meaningful life? We need this skill to self-reflect and justify our ways of life and opinions. Critical thinking provides us with the tools to evaluate ourselves in the way that we need to.

Photo by Marcelo Chagas from Pexels

6. the basis of science & democracy.

In order to have a democracy and to prove scientific facts, we need critical thinking in the world. Theories must be backed up with knowledge. In order for a society to effectively function, its citizens need to establish opinions about what’s right and wrong (by using critical thinking!).

Benefits Of Critical Thinking

We know that critical thinking is good for society as a whole, but what are some benefits of critical thinking on an individual level? Why is critical thinking important for us?

1. Key For Career Success

Critical thinking is crucial for many career paths. Not just for scientists, but lawyers , doctors, reporters, engineers , accountants, and analysts (among many others) all have to use critical thinking in their positions. In fact, according to the World Economic Forum, critical thinking is one of the most desirable skills to have in the workforce, as it helps analyze information, think outside the box, solve problems with innovative solutions, and plan systematically.

2. Better Decision Making

There’s no doubt about it — critical thinkers make the best choices. Critical thinking helps us deal with everyday problems as they come our way, and very often this thought process is even done subconsciously. It helps us think independently and trust our gut feeling.

3. Can Make You Happier!

While this often goes unnoticed, being in touch with yourself and having a deep understanding of why you think the way you think can really make you happier. Critical thinking can help you better understand yourself, and in turn, help you avoid any kind of negative or limiting beliefs, and focus more on your strengths. Being able to share your thoughts can increase your quality of life.

4. Form Well-Informed Opinions

There is no shortage of information coming at us from all angles. And that’s exactly why we need to use our critical thinking skills and decide for ourselves what to believe. Critical thinking allows us to ensure that our opinions are based on the facts, and help us sort through all that extra noise.

5. Better Citizens

One of the most inspiring critical thinking quotes is by former US president Thomas Jefferson: “An educated citizenry is a vital requisite for our survival as a free people.” What Jefferson is stressing to us here is that critical thinkers make better citizens, as they are able to see the entire picture without getting sucked into biases and propaganda.

6. Improves Relationships

While you may be convinced that being a critical thinker is bound to cause you problems in relationships, this really couldn’t be less true! Being a critical thinker can allow you to better understand the perspective of others, and can help you become more open-minded towards different views.

7. Promotes Curiosity

Critical thinkers are constantly curious about all kinds of things in life, and tend to have a wide range of interests. Critical thinking means constantly asking questions and wanting to know more, about why, what, who, where, when, and everything else that can help them make sense of a situation or concept, never taking anything at face value.

8. Allows For Creativity

Critical thinkers are also highly creative thinkers, and see themselves as limitless when it comes to possibilities. They are constantly looking to take things further, which is crucial in the workforce.

9. Enhances Problem Solving Skills

Those with critical thinking skills tend to solve problems as part of their natural instinct. Critical thinkers are patient and committed to solving the problem, similar to Albert Einstein, one of the best critical thinking examples, who said “It’s not that I’m so smart; it’s just that I stay with problems longer.” Critical thinkers’ enhanced problem-solving skills makes them better at their jobs and better at solving the world’s biggest problems. Like Einstein, they have the potential to literally change the world.

10. An Activity For The Mind

Just like our muscles, in order for them to be strong, our mind also needs to be exercised and challenged. It’s safe to say that critical thinking is almost like an activity for the mind — and it needs to be practiced. Critical thinking encourages the development of many crucial skills such as logical thinking, decision making, and open-mindness.

11. Creates Independence

When we think critically, we think on our own as we trust ourselves more. Critical thinking is key to creating independence, and encouraging students to make their own decisions and form their own opinions.

12. Crucial Life Skill

Critical thinking is crucial not just for learning, but for life overall! Education isn’t just a way to prepare ourselves for life, but it’s pretty much life itself. Learning is a lifelong process that we go through each and every day.

How To Improve Your Critical Thinking

Now that you know the benefits of thinking critically, how do you actually do it?

• Define Your Question: When it comes to critical thinking, it’s important to always keep your goal in mind. Know what you’re trying to achieve, and then figure out how to best get there.
• Gather Reliable Information: Make sure that you’re using sources you can trust — biases aside. That’s how a real critical thinker operates!
• Ask The Right Questions: We all know the importance of questions, but be sure that you’re asking the right questions that are going to get you to your answer.
• Look Short & Long Term: When coming up with solutions, think about both the short- and long-term consequences. Both of them are significant in the equation.
• Explore All Sides: There is never just one simple answer, and nothing is black or white. Explore all options and think outside of the box before you come to any conclusions.

How Is Critical Thinking Developed At School?

Critical thinking is developed in nearly everything we do, but much of this essential skill is encouraged and practiced in school. Fostering a culture of inquiry is crucial, encouraging students to ask questions, analyze information, and evaluate evidence.

Teaching strategies like Socratic questioning, problem-based learning, and collaborative discussions help students think for themselves. When teachers ask questions, students can respond critically and reflect on their learning. Group discussions also expand their thinking, making them independent thinkers and effective problem solvers.

How Does Critical Thinking Apply To Your Career?

Critical thinking is a valuable asset in any career. Employers value employees who can think critically, ask insightful questions, and offer creative solutions. Demonstrating critical thinking skills can set you apart in the workplace, showing your ability to tackle complex problems and make informed decisions.

In many careers, from law and medicine to business and engineering, critical thinking is essential. Lawyers analyze cases, doctors diagnose patients, business analysts evaluate market trends, and engineers solve technical issues—all requiring strong critical thinking skills.

Critical thinking also enhances your ability to communicate effectively, making you a better team member and leader. By analyzing and evaluating information, you can present clear, logical arguments and make persuasive presentations.

Incorporating critical thinking into your career helps you stay adaptable and innovative. It encourages continuous learning and improvement, which are crucial for professional growth and success in a rapidly changing job market.

Photo by Oladimeji Ajegbile from Pexels

Critical thinking is a vital skill with far-reaching benefits for personal and professional success. It involves systematic skills such as analysis, evaluation, inference, interpretation, and explanation to assess information and arguments.

By gathering relevant data, considering alternative perspectives, and using logical reasoning, critical thinking enables informed decision-making. Reflecting on and refining these processes further enhances their effectiveness.

The future of critical thinking holds significant importance as it remains essential for adapting to evolving challenges and making sound decisions in various aspects of life.

What are the benefits of developing critical thinking skills?

Critical thinking enhances decision-making, problem-solving, and the ability to evaluate information critically. It helps in making informed decisions, understanding others’ perspectives, and improving overall cognitive abilities.

How does critical thinking contribute to problem-solving abilities?

Critical thinking enables you to analyze problems thoroughly, consider multiple solutions, and choose the most effective approach. It fosters creativity and innovative thinking in finding solutions.

What role does critical thinking play in academic success?

Critical thinking is crucial in academics as it allows you to analyze texts, evaluate evidence, construct logical arguments, and understand complex concepts, leading to better academic performance.

How does critical thinking promote effective communication skills?

Critical thinking helps you articulate thoughts clearly, listen actively, and engage in meaningful discussions. It improves your ability to argue logically and understand different viewpoints.

How can critical thinking skills be applied in everyday situations?

You can use critical thinking to make better personal and professional decisions, solve everyday problems efficiently, and understand the world around you more deeply.

What role does skepticism play in critical thinking?

Skepticism encourages questioning assumptions, evaluating evidence, and distinguishing between facts and opinions. It helps in developing a more rigorous and open-minded approach to thinking.

What strategies can enhance critical thinking?

Strategies include asking probing questions, engaging in reflective thinking, practicing problem-solving, seeking diverse perspectives, and analyzing information critically and logically.

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Critical Thinking in Science: Fostering Scientific Reasoning Skills in Students

ALI Staff | Published  July 13, 2023

Thinking like a scientist is a central goal of all science curricula.

As students learn facts, methodologies, and methods, what matters most is that all their learning happens through the lens of scientific reasoning what matters most is that it’s all through the lens of scientific reasoning.

That way, when it comes time for them to take on a little science themselves, either in the lab or by theoretically thinking through a solution, they understand how to do it in the right context.

One component of this type of thinking is being critical. Based on facts and evidence, critical thinking in science isn’t exactly the same as critical thinking in other subjects.

Students have to doubt the information they’re given until they can prove it’s right.

They have to truly understand what’s true and what’s hearsay. It’s complex, but with the right tools and plenty of practice, students can get it right.

What is critical thinking?

This particular style of thinking stands out because it requires reflection and analysis. Based on what's logical and rational, thinking critically is all about digging deep and going beyond the surface of a question to establish the quality of the question itself.

It ensures students put their brains to work when confronted with a question rather than taking every piece of information they’re given at face value.

It’s engaged, higher-level thinking that will serve them well in school and throughout their lives.

Why is critical thinking important?

Critical thinking is important when it comes to making good decisions.

It gives us the tools to think through a choice rather than quickly picking an option — and probably guessing wrong. Think of it as the all-important ‘why.’

Why is that true? Why is that right? Why is this the only option?

Finding answers to questions like these requires critical thinking. They require you to really analyze both the question itself and the possible solutions to establish validity.

Will that choice work for me? Does this feel right based on the evidence?

How does critical thinking in science impact students?

Critical thinking is essential in science.

It’s what naturally takes students in the direction of scientific reasoning since evidence is a key component of this style of thought.

It’s not just about whether evidence is available to support a particular answer but how valid that evidence is.

It’s about whether the information the student has fits together to create a strong argument and how to use verifiable facts to get a proper response.

Critical thinking in science helps students:

• Actively evaluate information
• Identify bias
• Separate the logic within arguments
• Analyze evidence

4 Ways to promote critical thinking

Figuring out how to develop critical thinking skills in science means looking at multiple strategies and deciding what will work best at your school and in your class.

Based on your student population, their needs and abilities, not every option will be a home run.

These particular examples are all based on the idea that for students to really learn how to think critically, they have to practice doing it. 

Each focuses on engaging students with science in a way that will motivate them to work independently as they hone their scientific reasoning skills.

Project-Based Learning

Project-based learning centers on critical thinking.

Teachers can shape a project around the thinking style to give students practice with evaluating evidence or other critical thinking skills.

Critical thinking also happens during collaboration, evidence-based thought, and reflection.

For example, setting students up for a research project is not only a great way to get them to think critically, but it also helps motivate them to learn.

Allowing them to pick the topic (that isn’t easy to look up online), develop their own research questions, and establish a process to collect data to find an answer lets students personally connect to science while using critical thinking at each stage of the assignment.

They’ll have to evaluate the quality of the research they find and make evidence-based decisions.

Self-Reflection

Adding a question or two to any lab practicum or activity requiring students to pause and reflect on what they did or learned also helps them practice critical thinking.

At this point in an assignment, they’ll pause and assess independently. 

You can ask students to reflect on the conclusions they came up with for a completed activity, which really makes them think about whether there's any bias in their answer.

Addressing Assumptions

One way critical thinking aligns so perfectly with scientific reasoning is that it encourages students to challenge all assumptions. 

Evidence is king in the science classroom, but even when students work with hard facts, there comes the risk of a little assumptive thinking.

Working with students to identify assumptions in existing research or asking them to address an issue where they suspend their own judgment and simply look at established facts polishes their that critical eye.

They’re getting practice without tossing out opinions, unproven hypotheses, and speculation in exchange for real data and real results, just like a scientist has to do.

Lab Activities With Trial-And-Error

Another component of critical thinking (as well as thinking like a scientist) is figuring out what to do when you get something wrong.

Backtracking can mean you have to rethink a process, redesign an experiment, or reevaluate data because the outcomes don’t make sense, but it’s okay.

The ability to get something wrong and recover is not only a valuable life skill, but it’s where most scientific breakthroughs start. Reminding students of this is always a valuable lesson.

Labs that include comparative activities are one way to increase critical thinking skills, especially when introducing new evidence that might cause students to change their conclusions once the lab has begun.

For example, you provide students with two distinct data sets and ask them to compare them.

With only two choices, there are a finite amount of conclusions to draw, but then what happens when you bring in a third data set? Will it void certain conclusions? Will it allow students to make new conclusions, ones even more deeply rooted in evidence?

Thinking like a scientist

When students get the opportunity to think critically, they’re learning to trust the data over their ‘gut,’ to approach problems systematically and make informed decisions using ‘good’ evidence.

When practiced enough, this ability will engage students in science in a whole new way, providing them with opportunities to dig deeper and learn more.

It can help enrich science and motivate students to approach the subject just like a professional would.

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Solving Problems in Science: How the Driving Question Motivates Students In PBL

Teachers using the project-based learning approach generally agree that creating the driving question for a project is...

Equity In The Classroom: Making Science Accessible For All Students

All teachers want to see their students succeed.

They don’t want to see students fall behind, but everyone learns...

Teach Engineering: Engineering projects for kids

Children are natural engineers who are curious, inventive, and ready to create things out of the most unexpected...

Data Science Education: Making data work in math and science class

Staying relevant to students while preparing them to be successful in the future is the winning formula that all...

What Is Coding For Kids?

At the heart of today’s tech-driven world is coding – the way we interact with computers. As technology becomes...

Bolstering Creative Thinking in Science Education

Being a scientist and being told to think creatively automatically sound contradictory.

Science is about the facts, the...

Project-based Learning vs Problem-based Learning in Science

Crafting a science curriculum that engages students isn’t always easy.

While there are plenty of examples of...

Rise of the Educational Robots

Robotics education can prepare children for the jobs of the future, foster essential skills and competencies, and make...

What Is RTI (Response To Intervention) In Education?

Let’s explore the key features of Response to Intervention (RTI), a proactive multi-tiered approach to providing...

The Importance of Data Literacy in the Classroom

In today’s information age, we all want to claim we’re data-literate, but what does that really mean?

The Top 7 Benefits of Phenomenon-Based Learning

Phenomenon-based learning takes students’ questions and turns them into learning opportunities. The premise may seem...

Providing Equity in Math Through Small Group Instruction

Keeping students engaged in math isn’t always easy, but differentiated instruction within a single class period can...

Time Management Tips for Teachers

Ask teachers what resource they need more of, and chances are most of them will say, “Time!”

For teachers, managing...

Exploring the Connection Between Math and Art

Combining art with traditional STEM subjects (Science, Technology, Engineering, Math) creates STEAM education, which...

STEM Career Spotlight: Women In STEM

In honor of Women’s International Month, we would like to spotlight some amazing women scientists who have made...

How Autonomy Can Transform Your Classroom and Empower Students

Giving students autonomy over their learning doesn’t just engage and motivate them; it gives them the skills to achieve...

Math Strategies For Struggling Students: A New Approach to Challenges

Mathematics can be a challenging subject for many students, requiring schools to have effective strategies in place to...

Math in the Real World

“Why do I need to know this?”

AI In Education: The Impact of ChatGPT in the Classroom

ChatGPT, a language model that uses deep learning techniques to generate human-like responses, has garnered significant...

How to Support Multilingual Learners in Math

Multilingual learners often require tailored educational strategies to support their language development and academic...

Interactive Math: How To Make Math More Interactive

Interactive math isn’t a new concept. The idea of engaging students in more active learning experiences to enhance...

STEM Career Spotlight: The Impact of Black Scientists and Innovators

Throughout history, many Black scientists have made tremendous contributions to the advancement of STEM and positively...

How To Teach Math Vocabulary

Even for students with an intuitive sense of math, its specialized vocabulary often gets in the way, but that doesn’t...

The Top 8 Tips First-Year Teachers Need To Know

Whether fresh out of college or entering teaching as your second career, these tips will guide you in making the most...

Game-Based Learning vs. Gamification: Using Gaming In The Classroom

Games are highly motivating for everyone, including students. But you don’t have to turn your classroom into a game...

Overcoming Math Anxiety and the Fear of Math

Remember the first time you noticed a student's hands shake during a math test? Or that student who suddenly had to...

Taking A Fresh Look At STEM Professional Development

Professional development for STEM teachers is a tall order these days. 

As the pace of scientific advancement has...

STEM Integration from Kindergarten to High School

STEM education benefits students of all ages. Students as young as kindergarten can begin reaping the positives just...

The Challenges of STEM Education: Barriers to Participation

Incorporating new instructional strategies into your teaching practices is always challenging at first, but it gets...

The Pros and Cons of STEM Education

Introducing any new curriculum into an existing educational system always has pros and cons. There’s often a learning...

Any Classroom Can Be a STEM Classroom: Tips for Creating a STEM Learning Environment

You too can create a STEM classroom where students are actively engaged in collaborating to solve problems using...

How STEM Education Can Shape the Future

The future is ultimately uncertain. We can never completely predict what will happen to the economy, the job market,...

Why STEM is Important for Students, Schools, and Society

The buzz around STEM education continues to grow as teachers discover how it builds creative problem-solving through...

Cooperative Learning in STEM

STEM and cooperative learning strategies go hand-in-hand. If cooperative learning is the teaching method to engage...

All About The Concrete Representational Abstract (CRA) Method

Think back to your earliest memories of math class...

Do you remember using blue graphing blocks or cut-outs of...

How STEM Education Contributes To Career and College Readiness

We've previously discussed the benefits of STEM in early childhood education – but what about its benefits for students...

5 Reasons the Productive Struggle Belongs in STEM

It may be hard to watch students struggle, but facing the challenges of learning with the right attitude and seeing how...

Why is STEM So Important in Early Childhood Education?

STEM in early childhood education isn’t a new approach to teaching, but it is gaining traction as an important piece in...

STEM Spotlight: Katherine Johnson

Katherine Johnson, a mathematician and aerospace technologist at NASA, made significant contributions to the first...

There’s Nothing Ordinary About the STEM Everyday Podcast

Host chris woods brings fascinating interviews with a fantastic array of authors, makers, educators, and stem....

Using Inquiry-Based Learning With STEMscopes Math Activities

Traditional methods of teaching math only work for a handful of students. The majority of students struggle trying to...

Simple Strategies to Teach Math Through Play

Research indicates that attitudes towards mathematics, especially at a young age, can significantly influence a child’s...

Celebrating Hispanic Heritage: Walter Alvarez's Contributions to STEM

Walter Alvarez is known for having formulated the theory that the impact of an asteroid extinguished dinosaurs, an idea...

Bringing NASA’s DART Mission into the Classroom

Double Asteroid Redirection Test (DART) is a method of planetary defense against near-Earth asteroids, which changes...

How To Foster A Growth Mindset in the Classroom

Do you ever wonder why some students embrace making mistakes while others shy away from them?

Using The 3 Little Pigs To Teach 5E STEM

Let’s take a closer look at the classic children’s story, The Three Little Pigs, and how it serves as the foundation...

Integrating ICT Into STEM Education

Information and Communication Technology (ICT) is used everywhere in the world and has become an integral part of our...

Top 10 Tips for an Effective STEM Classroom

Today's students are coming of age in a world vastly distinct from the one their educators experienced during their own...

Tips from Former Teachers at STEMscopes (Part II)

Many STEMscopes employees come from a teaching background. In this 2-part blog, we draw on their past experiences to...

Tips from Former Teachers at STEMscopes (Part I)

Thanks to our teachers

All of us have had teachers that have touched our lives. For some of us, it’s been a few simple words of encouragement...

Best Practices for Remote Learning

The world can be an unpredictable place. We’ve all experienced that recently. And one of the hardest adjustments many...

Teaching Student Confidence

Can confidence be taught? Of all the questions math teachers ask when thinking through ways to improve instruction,...

Accelerate Learning STEMscopes and Google Classroom Integration

Today we are announcing that your favorite science and math curriculum can now be used with Google Classroom LMS. We...

Teaching Problem-Solving In Math

Problem-solving is essential in math education.

Black History Month Hero: Katherine Johnson

February is recognized across the US as Black History Month. In keeping with this tradition we like to look back on...

Math Teacher Writer Highlight: Helen Squire

Helen Squire’s love for STEM can be found in all areas of her life—from her job as a math teacher at a charter school,...

What is Computational Fluency?

Let's explore computational or mathematical fluency, a key component of STEM education.

Math fluency is a combination...

Fact Fluency in Math: Everything You Need To Know

Fact fluency is a skill that allows students to naturally solve problems with little to no conscious effort. The ease...

SEL for Teachers

Introduction

Across the country, school districts are adding social emotional learning (SEL) to their curriculum. SEL...

National Native American Heritage Month Hero: Matthew Yazzie

National Disability Employment Awareness Month Hero: Temple Grandin

Teacher Writer Spotlight: Rachel Neir

Hitting her one-year anniversary as a STEMscopes writer, Rachel Neir brings her bright smile and big ideas to...

SEL in Math: Promoting Social-Emotional Learning in Math Class

Integrating social-emotional learning (SEL) into math instruction is more than a trend; it's a meaningful shift in how...

STEMscopes Celebrates the Achievements of Hispanic STEM Pioneers

September 15th through October 15th marks National Hispanic Heritage Month, a time of year where we honor the...

Solving Word Problems With Three Reads

Teacher Writer Spotlight: Susan G. Galvan

It’s all about the science for Susan G. Galvan. Not only has she worked in science education practically her whole...

Math Teacher Writer Highlight: Steve Baker

Steve Baker writes for STEMscopes Math on the go. After teaching elementary math and science for years, Baker and his...

Math Intervention and Tutoring: Helping Struggling Students

In education, not all students progress at the same pace, especially in mathematics.

For those facing challenges in...

Teacher Writer Spotlight: Danielle Porterfield

New to science writing, Danielle Porterfield is making an impression with her commitment to tackle new things. She puts...

Going the Extra Mile: Acceleration and Intervention

The learning needs of one student are often not those of their classmates. To meet each student where they...

Teacher Writer Spotlight: Stephanie Even

Stephanie Even has been with STEMscopes since June of 2017, making this her fourth year with the curriculum writing...

Understanding Focus, Rigor, and Depth

When it comes to math education, we all want the same thing: students who are confident critical thinkers and problem...

Which Way is Right? Problem-Solving in Mathematics

The Mona Lisa is surprisingly, almost shockingly, small. Yet its far-reaching influence has made it synonymous with...

Teacher Writer Spotlight: Katy Grose

After teaching fifth-grade science for over six years, in addition to teaching multiple other subjects to third-,...

The American Rescue Plan and What It Includes

How Schools Will Spend HR 133 and ARP Funding

Announcing our STEMscopes Coding Contest Winners

This month we celebrated two special holidays, Mother’s Day and Teacher Appreciation Day. We invited students and...

Meet Jenny Stallworth

Jenny Stallworth is a dynamo of an educator. She has taught almost all STEM subjects, homeschooled her four children...

A Better Understanding of Mistakes Brings More Growth and Development for Both Students and Teachers

Throughout this past year, COVID-19 has reminded us that things don’t always go according to plan. The pandemic has...

How To Scaffold In Math

Scaffolding is a powerful educational strategy that provides temporary support to help students grasp new concepts and...

Meet our Writers: Kimberly Pardue

With a Bachelor’s in Early Childhood Education, a Master’s in Administration, and extensive experience teaching...

Understanding HR133

The effects of the pandemic have left almost no one untouched, and education is one area in particular that has...

Celebrating women in stem

Focusing on Social and Emotional Learning: Making a Pandemic Comeback

The coronavirus pandemic has changed a lot for students across the country. They’ve spent time learning virtually,...

Teacher Writer Spotlight: Lisa Culberson

After a whopping 23 years of being a science teacher, science department head, science teacher trainer and a summer...

Learning Loss and Its Impact on Math Education

What is learning loss? 

Teacher Writer Spotlight: Kathy Blanton

Kathy Blanton’s instructional experience is vast. Before joining STEMscopes , she taught math, health, and science to...

Learning from My Coworkers

When protests erupted across the country last spring, I was confused as to what they were about. Naturally, I was...

COVID Funding for K-12 Education

To date the federal government has designated funding for COVID-19-related expenses through two major federal bills...

Teacher Writer Spotlight: Jennifer Donovan

It’s no surprise that STEMscopes sought Jennifer Donovan to join the company’s team of curriculum writers. Donovan’s...

Teacher Writer Spotlight: Carri Bevil

Carri Bevil saw firsthand how effective STEMscopes Science was in her district. So when asked to join the new...

Breaking Down Norman Webb’s Depth of Knowledge Model

Learning is a process that entails different levels of understanding. This is the basic idea behind Norman Webb’s Depth...

Teacher Writer Spotlight: Morgan Christiansen

Morgan Christiansen fully commits herself in every aspect of her life. Her daily runs, her nearly decade-long marriage...

Introducing Students to the Future of Coding

The world as we know it is changing every day. With emerging technology shifting more and more toward the digital...

Teacher Writer Spotlight: Bonnie Smith

No task is too complex or unfamiliar for Bonnie Smith, who joined our team of STEMscopes Science teacher writers at the...

Bridging the Opportunity Gap in STEM Education

With new innovations emerging daily, technology seems to be evolving at the speed of light, and increasingly jobs...

Being Good at Math Means Finding a Good Job

Is being good at math necessary to finding a good job? Increasingly so, this is the case. While a discrete math skill...

Teacher Writer Spotlight: Erin Rawlinson

Sometimes things just come together at the right time. Erin Rawlinson was a new mom. She loved her job as a third-grade...

How STEMscopes Works: A Teacher’s Introduction to STEMscopes Math Lessons

STEMscopes is built around an instructional concept pioneered by Rodger Bybee in the 1980s and further refined over the...

Math as the Language of STEM

If we consider science to be the understanding of phenomena, technology the tools used to investigate phenomena, and...

Process Over Answer

3 Easy Steps to Making Math a Daily Routine at Home

We all know that very familiar adage, practice makes perfect —or as my third-grade teacher liked to say, practice makes...

Celebrating the teachers that make it possible: Nicole Blakeslee

How Introducing Coding at the K-12 Level can Help Bring About Equity

While the United States has come a long way in terms of education, there are still gaps in equity. One way to level the...

Providing Equity with Guided Math Small-Group Math Lessons

“When a teacher begins a math lesson with direct instruction they completely disregard and ignore their students’...

Math Teacher Writer Highlight: Taylor Wheeler

A year after Taylor Wheeler resigned from her teaching job to focus on raising her children, a former mentor called to...

What We Believe: The Pedagogical Philosophies that STEMscopes Math was Built On | Part 2

We’ve all heard the expression “practice makes perfect.” Rote math drills, however, have proven to be an ineffective...

What We Believe: The Pedagogical Philosophies that STEMscopes Math was Built On | Part 1

When the STEMscopes math team came together to design our curriculum, we set out to solve a problem that has always...

Science Teacher Writer Highlight: Lindsay Van Wyk

Overnight, COVID-19 created a demand for flexible lessons that can be taught virtually. Teachers everywhere are now...

Preventing the Summer Slide

Teachers and parents alike want to prevent summer slide , which may be exacerbated this year by school closures. As a...

World Oceans Day: 5 Ways to Take Action

Did you know that oceans make up 71% of Earth’s surface? Or that oceans contain 99% of Earth’s area that can be...

Math Teacher Writer Highlight: Alicia Chiasson

When her school district adopted STEMscopes Science in 2016, Alicia Chiasson knew there was something special about it....

10 Climate-Friendly Actions to Support Earth Day

In 1970, 20 million Americans came together for the very first Earth Day to raise awareness of the massive impact...

Nurturing Self-Directed Learning in the Classroom

Self-directed learning isn’t a new concept.

Maintaining Student-Teacher Connections During Remote Learning

Imagine this scenario: a star 5th grader is forced to stay home from school but continue learning. She’s accustomed to...

How to Give Assignments | Part 2

In our preview post , we shared a bit about setting expectations when assigning tasks remotely, along with the benefits...

How to Give Assignments | Part 1

What should be the expectation.

As more schools close due to the unforeseen impact of the coronavirus, districts are...

How Teachers Can Help in COVID-19

The COVID-19 crisis is changing the country as we know it. With cancellations of well-established events like the ...

5 Ways to Boost Student Engagement while Teaching Remotely

Distance learning brings with it many adjustments, from settling into an at-home work environment and keeping kiddos...

Math Chats, Going Beyond the Answer

Bridging the student gap between the problem and the solution .

As teachers, it is easy for us to get caught up in the...

Structure and STEM Resources for Distance Learning

We realize these days look different from our normal routine, especially for students who are used to following a...

Science Learning at Home: K-5 STEM Activity Pack

We’re all in a strange place of uncertainty right now due to the COVID-19 outbreak. Schools have shut down, parents...

COVID-19 Update | Keep the Learning Going

Coronavirus, or COVID-19, has dominated the news, so we’re ready to help you be informed. In this blog, we’ll explore...

5 Fun and Educational Ways to Celebrate Pi Day

Yes, we all know that Pi Day on March 14th is a fun excuse to eat one of the best desserts ever, but it’s also a great...

How to Improve Mathematical Discourse in the Classroom

Fostering mathematical discourse in the classroom is key to helping students understand and enjoy math. It can instill...

6 Take-Home Activities to Engage Your Student in STEM Over Winter Break

While winter break is a special time to spend with family, friends, and plenty of food, it doesn’t necessarily mean...

Teacher Tip: Intellectual Risk Taking

As educators, we are aware that our current students will be redefining knowledge and possibilities in the future, in...

Using Extended Vocabulary Instruction

­­­ We all know the importance of language acquisition , but did you know that how you teach students new science...

All Students Are Created Equally and Differently: Addressing Diverse Learning Styles in the Science Classroom

Imagine you are a middle school student challenged with the phenomenon, “What causes rainbows?” in your science...

STEMscopes Announces Exciting Fall 2018 Product Updates

Everyone at STEMscopes has been hard at work over the summer to improve the online application, so take a look below to...

What are NGSS Evidence Statements?

The NGSS have undergone numerous evolutions since their inception. Among the most powerful (and most recent) are the...

The Flipped Classroom: Everything You Need To Know

The flipped classroom is an educational model that turns the learning environment into a workshop for concepts...

Accelerate Learning Releases STEMscopes NGSS 3D Curriculum to Help Teachers Engage Students in Three Dimensional Learning and Phenomena-Driven Inquiry

Although the Next Generation Science Standards (NGSS) were released more than five years ago, many teachers still feel...

10 Careers that Use Math You Should Consider

Not everyone cringes at the idea of math class or reacts with panic to memories of algebra, but for people who...

10 More Careers in Science for 2018

When it comes to unique science jobs , professional opportunities aren't in short supply. Many top, high-paying...

10 More Careers that Use Technology

Technology is everywhere. In fact, nowadays it may be hard to imagine life without it, as it's part of every...

ELL Strategies: 7 Teaching Strategies For English Language Learners

English Language Learners (ELLs), or Multilingual Learners (MLLs), bring diverse perspectives and experiences to the...

Five ELL Resources for the Classroom

For a student who does not speak English as their first language, learning is an entirely different experience.

What Defines an English Language Learner?

English Language Learners (ELL) represents a growing population of U.S. students. According to the National Center...

Top 10 Science Jobs in the United States

Astronaut. Marine Biologist. Archaeologist. Every child dreams of what they want to be when they grow up. Often...

STEMscopes Early Explorer Named CODiE Award Finalist for Best PreK/Early Childhood Learning Solution

The 2018 SIIA CODiE Awards have selected STEMscopes™ Early Explorer as a finalist in the Best PreK/Early Childhood...

Top 10 Ways to Thank a Teacher this Week

Another Teacher Appreciation Week is upon us and the STEMscopes team is excited to have so many teachers and former...

What are Cooperative Learning Strategies and How Do They Affect my Classroom?

As a first-time teacher, how do you start aligning a lesson plan and classroom setup with cooperative learning...

How STEM Education Differs from Science Education Instruction

If you are a teacher in the 21st Century, then you know that the education landscape has changed quite significantly...

STEMscopes PreK-12 Digital Curriculum Named Finalist for EdTech Cool Tool Award in STEM Solution Category

Accelerate Learning announces that the STEMscopes™ PreK-12 digital STEM curriculum has been chosen as a finalist...

Accelerate Learning Founder and CEO Honered as EdTech Leadership Award Finalists

  Accelerate Learning announces that Reid Whitaker, founder of the company and creator of the award-winning ...

STEMscopes Dive-In Engineering Named Finalist for EdTech Cool Tool Award

Created by Accelerate Learning and the New York Hall of Science, the hands-on engineering curriculum provides...

Mississippi Approves STEMscopes Digital Science Curriculum for Grades K-12 in State Science Textbook Adoption 

Accelerate Learning announced earlier this week that the STEMscopes™ digital science curriculum has been approved...

How Playing Outside Increases Science Understanding and Real World Learning 

Outdoor play has always been an important part of childhood. Imaginative play, exploratory discovery, and real-world...

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