5 Inhibitors of Critical Thinking
Awareness of these can make you a more effective thinker and, yes, doer..
Posted December 6, 2021 | Reviewed by Michelle Quirk
- Assertions based on feeling may be venerated but may require scrutiny.
- There are at least five major sources of irrationality in assertions.
- While dramatic improvement in one's critical thinking is difficult, awareness of those five threats to critical thinking may help.
One's feeling is increasingly perceived as a competitor to critical thinking. We’re venerating “lived experience,” “feeling offended,” and succumbing to feeling-heavy/rationality-light bumper sticker rhetoric, whether it's from the Right—for example, calling liberals “libtards”—or on the left—“Mass Decarceration Now!”
You can be a better thinker and, in turn, a better doer if you’re aware of the following five inhibitors of critical thinking:
1. Confirmation Bias
It’s comforting to be agreed with. So we tend to more critically view ideas that don’t comport with our beliefs. If we're not to be hypocritical in lauding the marketplace of ideas and ideological diversity, be aware of your confirmation bias and consider, judge-like, statesman-like, assertions on their merits.
2. Cognitive Dissonance
That refers to holding two or more conflicting beliefs or behaviors. For example, you may feel shame in claiming to be an environmentalist while living in a big house and driving a gas-guzzling SUV. Or you might rationalize abusing a substance because you eat a low-calorie diet . Or you may hide your cognitive dissonance by privately believing one thing about, for example, wokeism, but professing another so you can avoid censure.
A timeless example of cognitive dissonance regards kindness: Everyone professes to value kindness, yet many people behave in unkind ways. I’m not just talking about criminals, but, for example, people who mouth the right words on Sunday but during the rest of the week lie about someone they’re jealous of, withhold crucial truths to a customer or romantic partner, or lie under oath to get a better divorce settlement or to overturn a will.
A clue that you may be experiencing cognitive dissonance is when you’re feeling uncomfortable about something you’re doing or are about to do. If so, ask yourself how the Wise One within you would resolve the conflict. For example, let’s say you’re tempted to badmouth a coworker unfairly in an attempt to get a promotion that you’re both vying for. Ultimately, wouldn't you feel better if you took an ethical approach to resolving the conflict? For example, you can try upskilling, working more diligently, looking for another place of employment where your prospects for promotion are better, or accepting that justice will more likely accrue if you just sit tight.
3. Commitment Bias
That's the phenomenon of doing a thing making you more likely to want to do more of that thing. For example, signing up for a first session of psychoanalysis makes you more likely to sign up for a second, even if you disliked the first.
4. Source Bias
Bias is unavoidable; we all have biases. They’re based on our family background, culture, education , exposure to the media, and the zeitgeist. The latter reflects the collective effect of all of those on a society. But the ethical person in making a case for something tries to push his or her biases aside in favor of a fair-minded presentation of the most worthy perspective(s) even if not their own. Alas, too often we succumb to our biases. Of course, that’s particularly dangerous when the person has a megaphone: teachers, professors, and the media. Do try to think less like an activist and more like a statesman.
5. Unfalsifiability
There are many other inhibitors of critical thinking, but one that's particularly relevant to readers of Psychology Today and is underdiscussed is unfalsifiability. That means making a claim that can't be proven false. Unfalsifiability doesn’t necessarily make the assertion incorrect, but it demands carefully assessing the proposition's reasonability.
Let’s take a psychology-related example: EMDR (eye movement desensitization and reprocessing). Some experts, for example, this multi-university team, concluded that EMDR is pseudoscience, in part because the underlying theory is both unprovable and seems logically unlikely to be effective. That puts additional burden on the results of high-quality studies that would confirm or refute EMDR's efficacy. Alas, a meta-analysis of EMDR studies finds that body of research to be of inadequate quality.
Other examples of unfalsifiable assertions include astrology and conspiracy theories. Regarding the latter, assertions both by the Left and Right about a “Deep State” are unprovable because the assertion is that they’re hidden. That means that there'd better be high-quality empirical support. For the Deep State as with astrology, that's lacking.
The Takeaway
Colleges have long attempted to teach critical thinking with limited success : "A fascinating review of the scientific research on how to teach critical thinking concludes that teaching generic critical thinking skills such as logical reasoning, might be a big waste of time."
So a mere blog post is unlikely to make a serious dent in the problem. Yet, it would seem that staying aware of those five potential biases—confirmation bias, cognitive dissonance, commitment bias, source bias, and unfalsifiability—is a doable, time-effective approach to improving thinking. And in our ever busier and persuasion -oriented society, that seems to be worth at least a blog post—if you're thinking critically.
I read this aloud on YouTube.
Marty Nemko, Ph.D ., is a career and personal coach based in Oakland, California, and the author of 10 books.
- Find a Therapist
- Find a Treatment Center
- Find a Psychiatrist
- Find a Support Group
- Find Teletherapy
- United States
- Brooklyn, NY
- Chicago, IL
- Houston, TX
- Los Angeles, CA
- New York, NY
- Portland, OR
- San Diego, CA
- San Francisco, CA
- Seattle, WA
- Washington, DC
- Asperger's
- Bipolar Disorder
- Chronic Pain
- Eating Disorders
- Passive Aggression
- Personality
- Goal Setting
- Positive Psychology
- Stopping Smoking
- Low Sexual Desire
- Relationships
- Child Development
- Therapy Center NEW
- Diagnosis Dictionary
- Types of Therapy
Men have long been silent and stoic about their inner lives, but there’s every reason for them to open up emotionally—and their partners are helping.
- Identification of Red-Flag Sexual Grooming Behaviors
- 3 Tips to Help You Design Your Perfect Workspace
- How Older Employees Maximize the Benefit of Wisdom
- Coronavirus Disease 2019
- Affective Forecasting
- Neuroscience
- Join / login
Subscribe Here!
- Critical, Analytical & Creative Thinking
- 7 Critical Thinking Barriers and How to Overcome Them
Get access to ALL our resources and premium unit plans by joining the Future Focused Learning Network
It's important to develop critical thinking skills for more than just academic reasons. Substantial critical thinking capacity serves us well in all aspects of our lives. It encompasses problem-solving , decision making, personal responsibility, and managing relationships of every kind effectively, just to name a few things. There's no doubt it's one of the most crucial mindsets our learners could ever have, for learning and life.
By using real-world examples , teachers can explore concepts that help learners think more critically. However, teachers must recognize the barriers and challenges accompanied by teaching critical thinking skills . Most importantly, we must discover how to get around these barriers. This article will explore seven common critical thinking barriers and how to effectively get around them.
- Egocentric Thinking
- Drone Mentality
- Social Conditioning
- Biased Experiences
- Schedule Pressures
- Arrogance and Intolerance
1. Egocentric Thinking
Although egocentric behaviors are less prominent in adulthood, overcoming egocentrism can be a lifelong process. Egocentric thinking is a natural tendency to view everything in relation to oneself. This type of thinking leads to the inability to sympathize with others or analyze and evaluate various perspectives. Sadly, since most egocentric people are not willing or cannot see this character flaw within themselves, this increases the difficulty in overcoming the barrier.
As young learners contemplate who they are and where they fit in, egocentric thinking may become more apparent. After all, they need experiences, opportunities for debate, brainstorming sessions, and the chance to ask meaningful questions in order to recognize and understand the viewpoints of others.
Creating a classroom that encourages critical thinking can help learners lose egocentrism. Especially during social conflicts, teachers can help learners think more abstractly by pointing out the opinions and attitudes of others. Teachers will do well to encourage empathy as their learners ponder other people's perspectives, opinions, and thoughts.
2. Groupthink
Groupthink can lead to unhealthy decision-making patterns. Like egocentric thinking, it is difficult to overcome. Breaking the cycle requires individuals to stand apart from the group and question opinions, thoughts, and popular ideas. This can be especially difficult for adolescents, but teachers can play a key role in encouraging independent thought and action in students.
Facilitating student learning in a classroom while avoiding a groupthink teaching style is possible by expanding teaching methods that help learners think creatively. This allows them to make connections and challenge reasoning, both of which are important for critical thinking.
Our learners benefit from direct training in decision-making to prepare them to solve complex problems. Expecting them to make decisions by trial and error is simply not enough. Instruction in how to debate and present constructive arguments can develop critical thinking skills. As learners become familiar and repeat this thinking capability, they are more likely to think, question, and analyze. As a result, this reduces the likelihood of them developing a groupthink perspective.
3. Drone Mentality
If you have a drone mentality , this means you don’t pay attention to what is going on around you. A drone mentality can sneak up on anyone at any time. Daily routines often lead to a drone mentality and can prevent or cause a loss of critical thinking skills.
This mentality is dangerous in a classroom because learners forget how to respond to new circumstances. It also causes them to shy away from challenges for the sake of ease and convenience.
Teachers should avoid the temptation of slipping into patterns that can lead to a drone mentality effect in the classroom. By constantly finding connections to new things and fields , their teaching methods can stay fresh and interesting while fostering an environment for critical thinking .
4. Social Conditioning
Unwanted assumptions and stereotyping leads to social conditioning. It does this by blinding us from the realization that we are even making assumptions and stereotyping in the first place. The ability to think outside of the spectrum is a great asset because most learners do not realize they are being conditioned to think a certain way.
Teachers can help their learners assess their own thinking by helping them take inventory of their thoughts and beliefs. It’s also important to teach clarity, accuracy and fair-mindedness in their thinking patterns.
5. Biased Experiences
Personal biases can prohibit critical thinking because they prevent the thinker from being fair, inquisitive and open-minded. This kind of thinking can also prevent an individual from using experience, reasoning and common sense to make informed decisions.
Teachers should encourage learners to lean on logic to become critical thinkers. This challenges them to evaluate the clarity and accuracy of their thinking. By giving assignments that utilize questioning techniques and critical thinking responses, teachers can effectively guide them through the critical thinking process.
6. Schedule Pressures
Time constraints often serve as a barrier to integrating learning opportunities that support critical thinking skills. Test scores and mandated teaching measures often result in teachers covering a great deal of content in a short amount of time.
With training, practice and patience, teachers can learn various strategies that equip them to naturally model thinking behaviors in the classroom that improve learners' critical thinking skills.
It is especially important that teachers do their best to create a learning schedule that is not hindered by time constraints. Critical thinking lessons should always be a top priority.
7. Arrogance and Intolerance
True critical thinkers do not welcome arrogance and intolerance into their minds. It is nearly impossible to find the best solution to a problem with a close-minded mindset. Without critical thinking skills, individuals often react thoughtlessly and recklessly to situations. What they should do, however, is assess and take responsibility for their choices while accepting the rewards or consequences that follow those choices.
Arrogance and intolerance block creativity and leaves no room for other suggestions for problem-solving. If learners believe no better solution to a problem exists, a teacher must have students question their logic. Encourage them to ask the following questions:
- What are my thoughts on this topic?
- Why do I think like this?
- Where did I learn this information?
- What does the information imply?
- Should I view it differently?
Breaking Down Barriers
There are multiple ways to get around critical thinking barriers. One way is to have learners choose a topic of choice and write a paper demonstrating a variety of approaches to solve a problem on the chosen topic. Teachers can use real-life situations, such as car buying, as examples when strengthening critical thinking skills. You can have learners discuss the steps in buying a car and how to make the best decision based on a variety of factors, such as income, down payment options, car insurance prices, etc.
Another way to teach critical thinking skills is to highlight how a bad decision can lead to a poor outcome. The goal is to illustrate that making mistakes and suffering consequences are natural parts of decision-making. More importantly, that problem solving is a powerful skill that will impact almost every aspect of each student’s future.
Teachers are key in influencing student’s behavior as well as the use of critical thinking skills. These skills can make a positive difference in the achievement level in both the classroom and throughout a student’s life.
The Best Resource for You and Your Learners
Critical thinking is complex and even harder to transfer across domains. Teaching students to think critically requires explicit and deliberate instruction. But who says it can't also be a whole lot of fun? It should be, and to make things easier we created the Critical Thinking Companion . This is a critical compendium for any modern teacher. Chock full of games, activities, puzzles, lessons, assessment rubrics and more, it's the best way to help your learners conquer critical thinking barriers for life.
Editor's note: This post was originally published in 2019 and has been updated for comprehensiveness.
Originally published Jun 5, 2019, updated September 19, 2021
Information & Legend
Related Articles
How essential understandings fit into our learning.
What does being educated mean?
The 8 Best Ways of Teaching Creatively That Will Never Fail
When it comes to teaching creatively we use both the heart and the mind in equal measure. ..
10 High School Student Projects for Demonstrating Altruism
If you’re a high school teacher, you know a large percentage of students in your classes are..
- 10 Great Critical Thinking Activities That Engage Your Students
- 25 Real-World Discussion Topics for Learners to Explore Together
- 10 of the Best Growth Mindset Activities for Kids
- 6 Benefits of Critical Thinking and Why They Matter
- 25 Self-Reflection Questions to Get Students Thinking About Their Learning
- The Growth Mindset Choice: 10 Fixed Mindset Examples We Can Change
- 301 Awesome Essential Questions Examples by Subject
- 4 Inspiring Stories of How Great Teachers Changed Someone's Life
- 6 Ways of Helping Students With Overcoming Learning Barriers
- 15 Assessment Activities That Are Fast, Fun, and Formative
- 36 Resources for STEM Project-Based Learning Activities
- 5 Terrific Inquiry-Based Learning Examples
- The 7 Most Common Traits of Highly Effective Critical Thinkers
- The BIG Essential Questions List
- Critical Thinking Cheatsheet
- Bloom's Question Stems
- Critical Thinking Activities
- Bloom's Taxonomy Verbs
- The Growth Mindset Guide
- Lee Crockett
- Global Professional Learning Network
- Accounting & Finance
- Communication
- Critical Thinking
- Marketing & Strategy
- Starting a Business
- Team Management
- Corporate Philosophy
- Diversity, Equity, & Inclusion
- Kokorozashi
- Sustainable Business
- AI Ventures
- Machine Learning
- Alumni Voices
- Yoshito Hori Blog
- Unlimited Insights
- Career Skills
How to Identify and Remove Barriers to Critical Thinking
Critical Thinking: Structured Reasoning
Even a few simple techniques for logical decision making and persuasion can vastly improve your skills as a leader. Explore how critical thinking can help you evaluate complex business problems, reduce bias, and devise effective solutions.
Critical Thinking: Problem-Solving
Problem-solving is a central business skill, and yet it's the one many people struggle with most. This course will show you how to apply critical thinking techniques to common business examples, avoid misunderstandings, and get at the root of any problem.
Contrary to popular belief, being intelligent or logical does not automatically make you a critical thinker.
People with high IQs are still prone to biases, complacency, overconfidence, and stereotyping that affect the quality of their thoughts and performance at work. But people who scored high in critical thinking —a reflection of sound analytical, problem-solving, and decision-making abilities—report having fewer negative experiences in and out of the office.
Top 5 Barriers to Critical Thinking
To learn how to think critically, you’ll need to identify and understand what prevents people from doing so in the first place. Catching yourself (and others) engaging in these critical thinking no-no’s can help prevent costly mistakes and improve your quality of life.
Here are five of the most common barriers to critical thinking.
Egocentric Thinking
Egoism, or viewing everything in relation to yourself, is a natural human tendency and a common barrier to critical thinking. It often leads to an inability to question one’s own beliefs, sympathize with others, or consider different perspectives.
Egocentricity is an inherent character flaw. Understand that, and you’ll gain the open-minded point of view required to assess situations outside your own lens of understanding.
Groupthink and Social Conditioning
Everyone wants to feel like they belong. It’s a basic survival instinct and psychological mechanism that ensures the survival of our species. Historically, humans banded together to survive in the wild against predators and each other. That desire to “fit in” persists today as groupthink, or the tendency to agree with the majority and suppress independent thoughts and actions.
Groupthink is a serious threat to diversity in that it supports social conditioning, or the idea that we should all adhere to a particular society or culture’s most “acceptable” behavior.
Overcoming groupthink and cultural conditioning requires the courage to break free from the crowd. It’s the only way to question popular thought, culturally embedded values, and belief systems in a detached and objective manner.
Next Article
5 of the Best Books on Critical Thinking and Problem-Solving
Drone Mentality and Cognitive Fatigue
Turning on “autopilot” and going through the motions can lead to a lack of spatial awareness. This is known as drone mentality, and it’s not only detrimental to you, but those around you, as well.
Studies show that monotony and boredom are bad for mental health . Cognitive fatigue caused by long-term mental activity without appropriate stimulation, like an unchanging daily routine full of repetitive tasks, negatively impairs cognitive functioning and critical thinking .
Although you may be tempted to flip on autopilot when things get monotonous, as a critical thinker you need to challenge yourself to make new connections and find fresh ideas. Adopt different schools of thought. Keep both your learning and teaching methods exciting and innovative, and that will foster an environment of critical thinking.
The Logic Tree: The Ultimate Critical Thinking Framework
Personal Biases and Preferences
Everyone internalizes certain beliefs, opinions, and attitudes that manifest as personal biases. You may feel that you’re open minded, but these subconscious judgements are more common than most people realize. They can distort your thinking patterns and sway your decision making in the following ways:
- Confirmation bias: favoring information that reinforces your existing viewpoints and beliefs
- Anchoring bias: being overly influenced by the first piece of information you come across
- False consensus effect: believing that most people share your perspective
- Normalcy bias: assuming that things will stay the same despite significant changes to the status quo
The critical thinking process requires being aware of personal biases that affect your ability to rationally analyze a situation and make sound decisions.
Allostatic Overload
Research shows that persistent stress causes a phenomenon known as allostatic overload . It’s serious business, affecting your attention span, memory, mood, and even physical health.
When under pressure, your brain is forced to channel energy into the section responsible for processing necessary information at the expense of taking a rest. That’s why people experience memory lapses in fight-or-flight situations. Prolonged stress also reduces activity in the prefrontal cortex, the part of the brain that handles executive tasks.
Avoiding cognitive impairments under pressure begins by remaining as calm and objective as possible. If you’re feeling overwhelmed, take a deep breath and slow your thoughts. Assume the role of a third-party observer. Analyze and evaluate what can be controlled instead of what can’t.
Train Your Mind Using the 9 Intellectual Standards
The bad news is that barriers to critical thinking can really sneak up on you and be difficult to overcome. But the good news is that anyone can learn to think critically with practice.
Unlike raw intelligence, which is largely determined by genetics , critical thinking can be mastered using nine teachable standards of thought:
- Clarity: Is the information or task at hand easy to understand and free from obscurities?
- Precision: Is it specific and detailed?
- Accuracy: Is it correct, free from errors and distortions?
- Relevance: Is it directly related to the matter at hand?
- Depth: Does it consider all other variables, contexts, and situations?
- Breadth: Is it comprehensive, and does it encompass other perspectives?
- Logical: Does it contradict itself?
- Significance: Is it important in the first place?
- Fairness: Is it free from bias, deception, and self-interest?
When evaluating any task, situation, or piece of information, consider these intellectual standards to hone your critical thinking skills in a structured, practiced way. Keep it up, and eventually critical thinking will become second nature.
Connect with Insights
Trouble keeping up with all the insights? Subscribe to our newsletter for monthly career inspiration right in your inbox! Your newsletter subscription with us is subject to the GLOBIS Privacy Policy .
Related Articles
The best critical thinking questions in business.
4 Distributive Negotiation Tactics to Get a Better Salary
Positional Negotiation: How to Deal with Inflexibility
LEAVE A REPLY Cancel reply
Save my name, email, and website in this browser for the next time I comment.
GLOBIS Insights
- Submission Guidelines
- Our Contributors
Accountability
- Privacy Policy
GLOBIS Group
- GLOBIS Corporation
- GLOBIS University
- GLOBIS Capital Partners
- GLOBIS Asia Campus
- GLOBIS China
- GLOBIS Europe
- GLOBIS Thailand
- G1 Institute
- Ibaraki Robots Sports Entertainment
- KIBOW Foundation
© GLOBIS All Rights Reserved
Marketing91
10 Common Barriers To Critical Thinking
July 31, 2019 By Hitesh Bhasin Filed Under: MANAGEMENT
Critical Thinking is not only required by an individual in the streams of academics and the business world but also in life as well. It is quite substantial and helps us attain the realms of success in all aspects of life.
It comprises of the factors such as decision making, maintaining healthy personal and professional relationships, problem-solving capacity, and having a detailed and thought out view over any situation. It is rightly said that it is one of the vital skills required to attain success and growth in life.
It is also one of the essential soft skills that one can possess to come up with viable and unique solutions to regular and outlandish problems in the area of business.
Apart from having inherent and innate critical thinking capabilities, one can also enhance the same through various learning’s, training, and development programs along with mind sharpening practices such as meditation.
Table of Contents
Meaning of Barriers to Critical Thinking
There are various types of Barriers to Critical Thinking that hinders with one’s personality and overall individuality. And owing to these factors, one cannot operate in a business environment efficiently and effectively.
To combat and overcome the Barriers to Critical Thinking in one’s life, the person has to realize and figure out the same.
10 Barriers to Critical Thinking
#1 egocentric nature and thinking patterns:.
Egocentric nature or behavior is a natural tendency and is many a time difficult to overcome. Such a barrier is making the person think about himself and leads to the inability to not to sympathize with others to understand their issues and problems. And one’s ego can be one of the most significant Barriers to Critical Thinking.
It is more of a character flaw, and despite several attempts of change; it is quite difficult for one to change. Such people lack to evaluate the perspective and feelings of others and make it disturbing for other people to work with them in a team.
#2 Group Thinking:
Group Thinking is yet amongst the harmful Barriers to Critical Thinking, plus it is also quite unhealthy. In such a case, the person doesn’t have his own opinion or decision in any given case or situation. To overcome the same, it requires the individuals of the group to stand apart and question and formulate their thoughts, opinions, and ideas.
The proverb of, ‘Too many cooks, spoil the soup’ aptly applies to this barrier as there is no independent action by the person.
#3 Drone Mentality:
Drone Mentality barrier can be explained as when a person doesn’t pay attention during the important work meetings and discussions. And it hails upon any time and on anyone affecting the process of critical thinking. Very often, daily and mundane routines make a person fall prey to drone mentality.
The managers and the HR department of the firm must keep the employees intrigued with challenging tasks and motivational factors.
#4 Social Conditioning:
Many of us have a habit of thinking within our comfort zones, and we refrain to even think outside our spectrum as we are taught to think in a certain way and manner owing to the various social conditions.
Barriers to Critical Thinking owing to social conditioning involves stereotyping things and people around us and having unwanted assumptions that make it quite difficult for people around us in the organization to work.
It requires cultural and social awareness to overcome this behavior and barrier.
#5 Biased nature and experiences:
Having a personal bias is one of the biggest Barriers to Critical Thinking as its curbs and prohibits a person from making decisions that are fair, open-minded, and transparent.
It also prevents the person to use logical reasoning, experience, and the basic common sense to make decisions that are informed and valid.
#6 Work pressure:
Quite many numbers of times at our workplace, we are overloaded with stringent deadlines, and it does affect our skill of critical thinking. But the silver lining is that a person can also sharpen his critical thinking skills and abilities amidst the tough and tight deadlines.
When the time is short, and a deadline needs to be met, we often go for an option of completing the work without any strategic thinking and long term vision. And here is when the barrier arises to thinking critically.
#7. Arrogance:
Arrogance is a bad attitude and often hinders with critical thinking abilities. It makes a person with a closed mindset and with an opinion that he knows everything and there is no further need for learning new things.
Arrogance makes the person fail on a long term basis as he has closed his channels of learning and is unable to assess the rewards and benefits of critical thinking.
#8 Stubborn Nature:
One of the Barriers to Critical Thinking to stubborn nature as a person with such a nature has his own set of beliefs and ideologies. And such a barrier is not very welcomed in the world of business, especially the corporate world as it is ever-evolving and dynamic in nature and its approach.
The person has to be open to changes and come out from his present beliefs understanding that the world of business is quite fluid and fast-paced and demands flexibility and adaptability.
Fear often acts as a barrier not only critical thinking but also for the overall growth and development of a person. Fear makes him unconfident, demotivated, and not very agile to think out of the box and come up with the ideas and strategies.
Fear can arouse out of the various reasons such as anxiety, depression, self-esteem issues, and other such personal reasons affecting a person’s professional life as well.
#10 Laziness:
If you liked this article, we bet that you will love the Marketing91 Academy , which provides you free access to 10+ marketing courses and 100s of Case studies.
About Hitesh Bhasin
Hi, I am an MBA and the CEO of Marketing91. I am a Digital Marketer and an Entrepreneur with 12 Years of experience in Business and Marketing. Business is my passion and i have established myself in multiple industries with a focus on sustainable growth.
Related posts:
- What Are Social Barriers? and How to Overcome Them
- What are Psychological Barriers?
- 15 Barriers To Change in Organisations you Should Know
- What are Physical Barriers?
- Positive Thinking | Benefits And Steps
- What is a Learning Organization? Peter Senge’s 5 Disciplines of Learning
- What is Action Learning? Definition and Components
- Organizational Learning: Definition, Types and Benefits
- What is Design Thinking? Importance, Advantages & Key Elements
- Barriers to Entrepreneurship: Top 12 Barriers to Entrepreneurship
Everything is correct
The lesson was helpful and i was able to complete the assignment on time .Thank you so much
The answers are very clear and summarized. Very helpful thank you
I love the critics in the writing am so much impressed by the writer.
Some of the important barriers to critical thinking were not explained example superstition
very helpful needed to hear that
thanks alot?great job
Very best idea
This information was helpful and i understand it better broken down like this.
Leave a Reply Cancel reply
Your email address will not be published. Required fields are marked *
- About Marketing91
- Marketing91 Team
- Privacy Policy
- Cookie Policy
- Terms of Use
WE WRITE ON
- Digital Marketing
Please note that Internet Explorer version 8.x is not supported as of January 1, 2016. Please refer to this support page for more information.
- Purchase PDF
Article preview
Introduction, section snippets, references (62), cited by (19), recommended articles (6).
Thinking Skills and Creativity
Nurturing critical thinking for implementation beyond the classroom: implications from social psychological theories of behavior change.
Critical thinking is a higher order mental function influenced by social factors and performed within a social context. The aim of this paper is to suggest guidelines for critical thinking education on the grounds of social psychological theories of behavior change. Based on reviews of literature on the Reasoned Action Approach (Fishbein & Ajzen, 2011), and Social Cognitive Theory (Bandura, 1986), this paper suggests that educators should direct learners’ attention to concrete and good models of critical thinking as well as their positive consequences through various sources. Guiding learners to be mindful about social pressures and their own personal biases that inhibit critical thinking should also facilitate critical thinking in actual circumstances.
Critical thinking (CT) refers to the ability and will to be open-minded to ideas regardless of one’s beliefs, and engage in reflective, balanced thinking (Ennis, 1993). It is essential not only for academic studies but also for solving social, political, and ethical problems as well (Abrami et al., 2008; Paul, 1995). Developing critical thinking abilities has been an important educational goal for nurturing intelligent, reasonable humans (Facione, 1990; Halpern, 1999; Paul, 1995) and even sustaining democracy (Dewey, 1993). The functional value of CT in our society implies that critical thinking is a holistic and composite ability including not only skills and dispositions, but also one’s actions as well (Davies, 2015).
Educators and researchers have demonstrated the effectiveness of various instructional methods for nurturing CT (Browne & Freeman, 2000; Yang, Newby, & Bill, 2008). However, a crucial point that previous CT education research seem to have neglected is that CT is a higher order mental function influenced by social factors and performed within social contexts which make the transfer of CT skills learned in classrooms to real life situations to be quite a challenge (Halpern, 1999; Sternberg, 1985). Despite the social nature of CT, classroom teaching of CT mostly confines the social context of CT to interactions within the boundaries of the classroom. For example, facilitating offline/online interactions among students through discussions and collaborative work is a narrow interpretation of social interaction as it only targets the increase of CT abilities directly involved with the learning task. Research on creating CT learning experiences that prepare learners for the complexities in society are hard to find.
Such being the case, this paper will recognize critical thinking as a socially embedded action, and explore effective CT education methods which incorporate this aspect. Specifically, socio psychological theories of behavior change emphasizing environmental influences that inhibit or stimulate our behaviors should be useful for this purpose. The point of adopting this approach is to overcome the limitations of existing methods which assume the smooth transfer of classroom learning to life, even when that transition turns out to be difficult due to the social nature of our behaviors. By assuming the definition of critical thinking to include ‘action’ (Davies, 2015) carried out in our social environment, and by adopting the implications from behavior change theories, this paper aims to identify educational methods accommodating the complexities of performing actions reflecting CT in real life. In particular, this paper will focus on the two most highly applied theories in behavior change studies which are most applicable to education: Theory of planned behavior (Ajzen, 1991), and social cognitive theory (Bandura, 1986). After reviewing the meaning of CT, its educational practices, and the main ideas of both behavior change theories, their implications for CT education will be discussed.
Critical thinking: its meaning, educational methods, and challenges
Critical thinking has been mostly defined as a combination of skills and dispositions. As a skill, CT is “self-directed, self-disciplined, self-monitored, and self-corrective thinking” (Scriven & Paul, 2008, para 2). It is also the analysis and evaluation of arguments/claims in a reasonable/inquisitive/open-minded manner (Ennis, 1993; Facione, 1990, Halpern, 1999). A disposition oriented view defines CT as the inclination to think in an open and fair-minded way (Ennis, 1993; Facione, 1990), the
Theories of behavior change
With the exception of social cognitive theory (Bandura, 1986) which will be discussed later, models and methods for inducing behavior change have been studied mostly in non-educational areas such as physical health (e.g., AIDS prevention, weight control), and marketing (e.g., purchasing behaviors of consumers). Although one might contest the use of theories rarely applied in education, similarities between behaviors studied in theories of behavior change and critical thinking behaviors exist as
Facilitate self-initiated discovery and conceptualization of authentic CT behaviors from personally meaningful contexts
According to the RAA model, an intervention should be directly relevant to the target behavior. Thus, the target behavior would be how a good critical thinker actually executes CT in authentic contexts, rather than critical thinking in an abstract sense. Bandura’s theory of modeling implies the necessity of identifying specific traits of desirable patterns of CT for symbolic representations of the behavior to be retained. Both theories emphasize that the learner’s attention should be directed
Transforming an individual into a critical thinker requires a broader approach than teaching CT skills within classrooms. Educational methods reflecting the social psychological aspects of human thinking and behaviors should be implemented. Educators should consider directing attention to concrete and good models of CT behaviors as well as their positive consequences through various authentic sources such as news articles, historical events, or self-reflections. It would also help to guide
Factors affecting students’ self-efficacy in higher education
Educational research review, using the theory of planned behavior to identify key beliefs underlying pro-environmental behavior in high-school students: implications for educational interventions, journal of environmental psychology, facilitating interactions through structured web-based bulletin boards: a quasi-experimental study on promoting learners’ critical thinking skills, computers & education, cognitive bias, a rational account of pedagogical reasoning: teaching by, and learning from examples, cognitive psychology, identity-based motivation: emerging trends in the social and behavioral sciences, journal of consumer psychology, self-efficacy and academic achievement: why do implicit beliefs, goals, and effort regulation matter, learning and individual differences, inquiring minds really do want to know: using questioning to teach critical thinking, teaching of psychology, self-efficacy for healthy eating and peer support for unhealthy eating are associated with adolescents’ food intake patterns, a focus theory of normative conduct: a theoretical refinement and reevaluation of the role of norms in human behavior, advances in experimental social psychology, the theory of planned behavior, organizational and human decision processes, instructional interventions affecting critical thinking skills and dispositions: a stage 1 meta-analysis, review of educational research, the theory of planned behaviour is alive and well, and not ready to retire: a commentary on sniehotta, presseau, and araújo-soares, health psychology review, social foundations of thought and action: a social cognitive theory, self-efficacy: the exercise of control, distinguishing features of critical thinking classrooms, teaching in higher education, the nature and development of critical-analytic thinking, educational psychology review, developing and evaluating utility of school-based intervention programs in promoting leisure-time physical activity: an application of the theory of planned behavior, international journal of sport psychology, a model of critical thinking in higher education, critical thinking assessment, theory into practice, dual-processing accounts of reasoning, judgement, and social cognition, annual review of psychology, critical thinking: a statement of expert consensus for purposes of educational assessment and instruction. research findings and recommendations, predicting and changing behavior: the reasoned action approach, look who’s talking: a comparison of lecture and group discussion teaching strategies in developing critical thinking skills, communication education, investigation of educational intervention based on theory of planned behavior on breakfast consumption among middle school students of qom city in 2012, journal of education and health promotion, theories and principles of motivation, teaching for critical thinking: helping college students develop the skills and dispositions of a critical thinker, new directions for teaching and learning, application of the theory of planned behaviour in behaviour change interventions: a systematic review, psychology and health, the case for motivated reasoning, psychological bulletin, improving critical thinking skills by overcoming confirmation bias, the journal of educational studies, measuring primary school teachers’ attitudes towards stimulating higher-order thinking (shot) in students: development and validation of the shot questionnaire.
This paper describes the development and validation of a new instrument to measure primary school teachers’ attitudes towards stimulating higher-order thinking in students (SHOT questionnaire). It is believed that it is necessary to explicitly teach students to think, because it cannot be assumed that students will automatically become good thinkers. Therefore, teachers are expected to stimulate students to engage in higher-order thinking. However, we know little about teachers’ attitudes towards teaching practices that engage students in higher-order thinking. Therefore, we need a valid and reliable measurement instrument that can be used to measure teachers’ attitudes towards stimulating higher-order thinking (SHOT). Hence, we developed the SHOT questionnaire. Based on an earlier literature review, we identified four attitudinal factors that we aimed to measure with the SHOT questionnaire. In addition, we included a scale to measure teachers’ behaviour aimed at stimulating higher-order thinking. Results of the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) with 659 pre- and in-service primary school teachers’ show that the requirements for construct validity were met. Furthermore, we found that in-service teachers, who are more positive about the relevance of stimulating higher-order thinking and their ability to do this, encourage students significantly more often to engage in higher-order thinking than pre-service teachers do.
Thinking critically through controversial issues on digital media: Dispositions and key criteria for content evaluation
21st-century society is facing a crisis of truth. Digital media lends itself to this by allowing the dissemination of almost unlimited quantities of unverified content. This threatens the development of accurate thinking along with the decision-making process in critical situations. Learning how to evaluate online information is thus vital in such scenarios. Much has been done in this regard, including explanations of criteria for evaluating information. However, some criteria may require explicitness. Critical thinking (CT) dispositions also need to be addressed more emphatically in the online content evaluation process. This study attempted to address both aspects theoretically in the context of controversial issues on the Web. Evaluating controversial content requires rigorous standards beyond the widely agreed criteria involving authorship, meaning criteria related to content production (systematicity) and its validation or corroboration (scrutiny). Consequently, four evaluation criteria were proposed, namely, author position, author motivation, systematicity , and independent scrutiny , which require the identification and practice of specific evaluation skills, basic knowledge, and fundamentally, key CT dispositions. Both the skills and dispositions are discussed around a general framework introduced in this study with educational implications for the evaluation of controversial content online and beyond.
The Effect of Critical Thinking Embedded English Course Design to The Improvement of Critical Thinking Skills of Secondary School Learners<sup>✰</sup>
Evolving trends of 21st century require the continuous development of individuals to become competent in using the skills of era effectively. Critical thinking (CT) is one of the basic skills of the century for the intellectual development of individuals to sustain global welfare. Infusion of CT into the subject matter content is one of many efforts for the training of individuals to think critically. Thus the derive for this study was the possibility of CT training in a secondary school context with elementary level of EFL learners. Having concurrent embedded mixed method research design; this study used various data collection methods. Quantitative data was gathered through a CT skills scale conducted as pretest and posttest. The structured interview was the qualitative tool to gather the opinions of the participants about the CT embedded English learning process. The results showed that the treatment group statistically outperformed the control group in the development of CT skills. Qualitative data indicated that the treatment was effective for the improvement of both language and CT skills. Moreover, the instruction process was motivating for the learners due to its meaningful, fun, authentic and supportive nature. The results have implications for EFL teachers that the full integration of CT to the English course objectives, language learning activities, assignments, assessment and teacher attitude is possible and supportive for the improvement of low-proficiency secondary school EFL learners as qualified thinkers in the target language.
Critical thinking perspectives across contexts and curricula: Dominant, neglected, and complementing dimensions
Conceptions of critical thinking (CT) are influenced by cultural and sociopolitical factors that give rise to a variety of views of CT across contexts. Rethinking conceptions of CT according to context is thus important in order to design teaching models that respond to sociocultural particularities and needs as well as to global demands. Existing conceptualizations of CT include cognitive, metacognitive, emotional, attitudinal, ethical, and sociopolitical dimensions that have shaped various approaches adopted in the curriculum. The skills–dispositions perspective to CT is dominant across contexts, but emerging perspectives and approaches include less recognized dimensions, such as civic, ethical, and cultural ones. Neglecting these leads to negative consequences in the fight for social justice since a comprehensive view of CT entails ethical reasoning, social awareness, and a deep concern for the public good leading to action. A comprehensive, culturally sensitive model of CT should include, at least, intellectual skills, dispositions, and ethical and civic dimensions.
Teachers' Perceptions of Critical Thinking in Primary Education
Innovation in physical education: the role of cognitive factors and self-efficacy, latent class cluster analysis in exploring different profiles of gifted and talented students.
With respect to intervention related to gifted students, numerous studies highlight the need for teachers to recognise different types of high-ability students and to be aware of the differences in these students' cognitive and motivational characteristics such that they can provide better assistance. A latent class cluster analysis was performed to analyse the unobserved heterogeneity in a group of 358 gifted secondary students. Moreover, a multi-variate analysis of variance, and a univariate analysis of variance of repeated measures were performed to determine whether there were differences in the profiles of the cognitive and motivational variables between the identified classes. The results revealed the existence of four latent clusters, with different profiles, within the gifted student population: a) gifted achievers; b) cognitive gifted; c) creative gifted; d) high achievement and cognitive gifted.
Problem and project-based learning through an investigation lesson: Significant gains in creative thinking behaviour within the Australian foundation (preparatory) classroom
Creativity is identified as the 21 st Century Skills needed for the new economy. Diverse positive developmental outcomes are associated with young children's creativity. Creativity is well documented as not limited to any particular discipline or activity, but most research in the Australian context relates to art, dance and music education. Very little is known to what extent creativity is integrated and implemented outside the expressive arts. Research that links curricular areas and creativity is scarce both in the international arena and within the Australian contexts. In this case-study, I explore how Foundation-preparatory stage children express their creative thinking behaviour across the curriculum within the strategies used by teachers in school classrooms environment. Thirty-five hours of observations, semi-structured interviews, and artefacts data were gathered over five months. Purposive sampling through a local school was selected because the school's motto and mission promulgates partnership that fosters inspiration, innovation, and creativity. Findings reveal that problem-and-project-based learning strategies used in the Investigation lesson immensely aroused children's creative processes. Exploratory thinking, risk-taking, experimentation and being resilient were exhibited in the creative endeavour. Creativity in varying level of occurrence was found exhibited across curriculum but all elements of creativity which is both cognitive and affective were manifested intensely in Investigation lessons. Such engagement is applicable to all educational research, learning and teaching by enabling people to grow ideas together. This offers more informed perspectives around developing creative capabilities across curriculum for researchers, teacher educators and curriculum developers.
The development and impact of active learning strategies on self-confidence in a newly designed first-year self-care pharmacy course – outcomes and experiences
The primary objective of this investigation was to determine the effectiveness of different active learning exercises in a newly-designed flipped-classroom self-care course in applying newly acquired knowledge of self-care and improving the confidence of first-year pharmacy students to recommend self-care treatments and counsel patients. The early development of these skills is essential for the subsequent Community Introductory Pharmacy Practice Experience (CIPPE).
An unpaired anonymous survey was administered to students, pre- and post-course, to ascertain their opinions on the effectiveness of various teaching strategies and active learning exercises on learning and on their confidence in treatment-planning and patient counseling for self-care patients. Comparison between pre- and post-course Likert scores was conducted using a one-way ANOVA followed by a post-hoc Tukey's test with significance at p = 0.05. All other tests of significance were conducted using a student's t -test with significance at p = 0.05.
Students’ self-confidence in developing treatment plans and in counseling for non-prescription drugs and dietary supplements significantly improved from the beginning to the end of this self-care course. The response rate was high in both the pre- (N = 208, 88.1%) and post- (N = 198, 83.9%) course surveys. The positive change in confidence was not reflected in increased performance on the final exam represented by a lower average score than the midterm exam.
Active learning sessions and the flipped classroom approach in this first-year pharmacy self-care course contributed to increased self-confidence in making recommendations and counseling patients on proper use of nonprescription medications and dietary supplements.
Implicit Theories of Critical Thinking in Teachers and Future Teachers
Research is focused on finding the implicit theories of teachers and students in the teaching field in relation to the issue of critical thinking in education. The research purpose is to determine respondents’ subjective opinions on what the concept of critical thinking include and how we can imagine a critically thinking child. The aim is also to discover whether Czech teachers and future teachers consider development of critical thinking in schools as desirable. Our own questionnaire and interview were used. Data was processed by a combination of quantitative and qualitative methods. Conclusions are that the critical thinking concept raises different ideas and opinions among respondents. These opinions also reflect whether the respondent was a student teacher or a teacher with experience, and also whether the respondent completed critical thinking course. Other findings are regarding the relationship between the length of teaching experience and teachers’ opinions on the need to develop critical thinking.
Fostering the skills of critical thinking and question-posing in a project-based learning environment
Innovative pedagogical models for teaching and learning aimed at developing higher order thinking skills require more sophisticated evaluation mechanisms than traditional pedagogical models to determine their effectiveness. In recent years, increased implementation of creative pedagogy has stimulated a parallel interest in the field of educational effectiveness research (EER). EER studies the factors impacting educational outcomes. This research examined an innovative program for 9 th and 10 th graders. The program implemented a project-based learning, constructivist approach with three teachers co-teaching each lesson to maximize development of high-order thinking skills. Students learned the required ministry of education material for all subjects through projects based on group work and peer learning. The research goal was to evaluate the innovative program’s effect on two skills: critical thinking and question-posing. The innovative class was compared to a traditional class learning the same material at three points in time over two years using pre- and post-case-based questionnaires (71 students, total of 192 questionnaires). Although no significant differences were found between the classes in the critical thinking pre-questionnaire, students in the innovative learning environment had a significant advantage in this skill after two years. Significant differences in question-posing were found in the pre-questionnaire and the gaps enlarged over the research period. The results emphasize the importance and contribution of a case-based evaluation method for "evidence-based education."
Literature as catalyst of homogenous and heterogeneous patterns of disciplinary thinking
Disciplines could broadly be categorized as hard pure/applied and soft pure/applied; however, literature seems to enable students to transcend conventional disciplinary boundaries. The purpose of this study was to determine how four disciplinary groups of students responded to literature when no apparent pedagogic purpose was explicitly assigned to short stories as supplementary reading. Data was collected through a qualitative survey, and a content analysis method determined and quantified data patterns among a total population sample of natural science, engineering, art, and music students (N = 55). A heterogeneous pattern across disciplines was associated with general critical thinking, as no explicit connection to disciplinary literacy could be established. All disciplines in this study demonstrated homogenous thinking patterns when positive critical evaluations were made. Crossdisciplinary homogenous coupling occurred when disciplines conducted negative critical evaluations. The thinking patterns call into question the typology of disciplinary hard or soft families as unexpected crossdisciplinary associations were identified. The patterns of disciplinary thinking propose theoretical and practical pedagogic implications especially for the transdisciplinary classroom.
Journal of Cognitive Psychology
Open access
Identifying obstacles to transfer of critical thinking skills
- Download citation
- https://doi.org/10.1080/20445911.2021.1990302
The process of transfer
The present study, experiment 1, experiment 2, general discussion, limitations and future directions, acknowledgements, disclosure statement, additional information.
- Full Article
- Figures & data
- Reprints & Permissions
- View PDF PDF View EPUB EPUB
ABSTRACT Formulae display: ? Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom.
This study investigated whether unsuccessful transfer of critical thinking (CT) would be due to recognition, recall, or application problems (cf. three-step model of transfer). In two experiments (laboratory: N = 196; classroom: N = 104), students received a CT-skills pretest (including learning, near transfer, and far transfer items), CT-instructions, practice problems, and a CT-skills posttest. On the posttest transfer items, students either (1) received no support, (2) received recognition support, (3) were prompted to recall acquired knowledge, or (4) received recall support. Results showed that CT could be fostered through instruction and practice: we found learning, near transfer, and (albeit small) far transfer performance gains and reduced test-taking time. There were no significant differences between the four support conditions, however, suggesting that the difficulty of transfer of CT-skills lies in problems with application/mapping acquired knowledge onto new tasks. Additionally, exploratory results on free recall data suggested suboptimal recall can be a problem as well.
- Critical thinking
- unbiased reasoning
- transfer process
- three-step model of transfer
Every day, we have to make a multitude of quick but sound judgments and decisions. Since our working-memory capacity and duration are limited and we cannot process all the information around us, we have to resort to heuristics (i.e. mental shortcuts) that ease reasoning processes (Tversky & Kahneman, Citation 1974 ). Usually, heuristic reasoning is very functional and inconsequential—think, for example, of where you decide to sit in a train—but it also makes us prone to illogical and biased decisions (i.e. deviating from ideal normative standards derived from logic and probability theory) that can have a significant impact. To illustrate, a forensic expert who misjudges fingerprint evidence because it verifies his or her preexisting beliefs concerning the likelihood of the guilt of a defendant, displays the so-called confirmation bias, which can result in a misidentification and a wrongful conviction (e.g. the Madrid bomber case; Kassin et al., Citation 2013 ).
To reduce or eliminate biased decisions and to successfully function in today’s society, one should engage in critical thinking (CT: e.g. Dewey, Citation 1910 ; Pellegrino & Hilton, Citation 2012 ). In the field of educational assessment and instruction, CT is generally defined as “purposeful, self-regulatory judgment that results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or contextual considerations on which that judgment is based” (APA: Facione, Citation 1990 , p. 2). According to this widely used definition, “the ideal critical thinker is habitually inquisitive, well-informed, trustful of reason, open-minded, flexible, fair-minded in evaluation, honest in facing personal biases, prudent in making judgments, willing to reconsider, clear about issues, orderly in complex matters, diligent in seeking relevant information, reasonable in the selection of criteria, focused in inquiry, and persistent in seeking results which are as precise as the subject and the circumstances of inquiry permit” (Facione, Citation 1990 , p. 3). Despite the variety of definitions of CT and the multitude of components CT encompasses (cf. Facione, Citation 1990 ), there appears to be agreement that one key aspect of CT is the ability to avoid bias in reasoning and decision-making (Baron, Citation 2008 ; Duron et al., Citation 2006 ; Facione, Citation 1990 ; West et al., Citation 2008 ), such as overturning belief-biased responses when evaluating the logical validity of arguments. Biases occur when people rely on heuristic reasoning (i.e. Type 1 processing) when that is not appropriate, do not recognize the need for analytical or reflective reasoning (i.e. Type 2 processing), are not willing to switch to Type 2 processing or unable to sustain it, or miss the relevant mindware to come up with a better response (e.g. Evans, Citation 2003 ; Stanovich, Citation 2011 ). Consequently, in order to prevent biased reasoning, it is necessary to stimulate people to switch to Type 2 processing. However, that may not be enough if the lack they lack the relevant mindware, so in many cases, mindware has to be taught as well.
It is not surprising that educational researchers, practitioners, and policymakers agree that CT is one of the most valued and sought-after skills that higher education students are expected to learn (Davies, Citation 2013 ; Facione, Citation 1990 ; Halpern, Citation 2014 ; Van Gelder, Citation 2005 ). Consequently, there is a substantial body of research on teaching CT-skills (Abrami et al., Citation 2008 , Citation 2014 ) including reducing biases in reasoning (e.g. Van Peppen et al., Citation 2018 , Citation 2021a ; Flores et al., Citation 2012 ; Heijltjes et al., Citation 2014a , Citation 2014b , Citation 2015 ; Janssen et al., Citation 2019 ; Kuhn, Citation 2005 ; Sternberg, Citation 2001 ). It is well established, for instance, that explicit teaching of CT combined with practice improves learning of CT-skills required for unbiased reasoning. However, transfer to similar tasks that were not instructed or practiced is very hard to establish (Van Peppen et al., Citation 2018 , Citation 2021a ; Heijltjes et al., Citation 2014a , Citation 2014b , Citation 2015 ). As it would be unfeasible to train students on each and every type of reasoning bias they will ever encounter, there is increased concern as to how to promote transfer of these skills (and this also applies to CT-skills more generally, see, for example, Halpern, Citation 2014 ; Kenyon & Beaulac, Citation 2014 ; Lai, Citation 2011 ; Ritchhart & Perkins, Citation 2005 ).
Transfer is the process of applying one’s prior knowledge or skills to some new context or related materials (e.g. Barnett & Ceci, Citation 2002 ; Cormier & Hagman, Citation 2014 ; Druckman & Bjork, Citation 1994 ; McDaniel, Citation 2007 ; Perkins & Salomon, Citation 1992 ). Transfer involves gradients of similarity between the initial and novel situation, so that transfer between situations that have less in common occurs less often than transfer between closely related situations (e.g. Barnett & Ceci, Citation 2002 ; Dinsmore et al., Citation 2014 ). In the educational psychology literature, transfer is usually subdivided into near and far transfer, differentiating in degree of similarity between the initial task or situation and the transfer task or situation (e.g. Perkins & Salomon, Citation 1992 ). Transferring knowledge or skills to a very similar situation, for instance, problems in an exam of the same kind as that have been practiced during the lessons, refers to “near” transfer. By contrast, transferring between situations that share similar structural features but, on appearance, seem remote and alien to one another is considered “far” transfer. It is important to realize, however, that near and far transfer occur on a continuum and do not imply any precise codification of closeness (Salomon & Perkins, Citation 1989 ), for instance, because people differ considerably in their ability to identify similarities between different problem situations. In their attempt to bring clarity to the literature on transfer of knowledge, Barnett and Ceci ( Citation 2002 ) developed a taxonomy in which they conceptualized transfer as a three-step process in which learners need to (a) recognize that acquired knowledge is relevant in a new context, (b) recall that knowledge, and (c) apply that knowledge to the new context.
Previous research has shown that to promote successful (far) transfer of learning, instructional strategies should contribute to permanent changes, by creating effortful learning conditions that trigger active and deep processing (i.e. generative processing ; e.g. Fiorella & Mayer, Citation 2016 ; Wittrock, Citation 2010 ). More specifically, it is important that learners explore similarities and differences between different problem types to acquire better mental representations of the structural features of the different types of problems (i.e. schemas; Bassok & Holyoak, Citation 1989 ; Fiorella & Mayer, Citation 2016 ; Holland et al., Citation 1989 ; Wittrock, Citation 2010 ). Ways to stimulate this are, for instance, creating variability in practice (e.g. Barreiros et al., Citation 2007 ; Moxley, Citation 1979 ) or encouraging elaboration, questioning, or explanation during practice (e.g. Fiorella & Mayer, Citation 2016 ; Renkl & Eitel, Citation 2019 ). Taken together, transfer of learning can occur when a learner acquires an abstract action schema responsive to the requirements of a problem. If the potential transfer situation presents similar requirements and the learner recognizes them, they may apply (or map) the same or a somewhat adapted action schema to solve the novel problem (e.g. Gentner, Citation 1983 , Citation 1989 ; Mayer & Wittrock, Citation 1996 ; Reed, Citation 1987 ; Vosniadou & Ortony, Citation 1989 ).
When interventions that encourage generative processing are applied to CT-skills, however, it is often found that they promote learning but not transfer; the effects hardly seem to transfer across tasks or domains (Halpern & Butler, Citation 2019 ; Ritchhart & Perkins, Citation 2005 ; Tiruneh et al., Citation 2014 , Citation 2016 ). Research that focused on teaching unbiased reasoning has uncovered that a combination of instruction and task practice enhances transfer to isomorphic problems, i.e. same structural features/problem type but different superficial features, meaning other values or story contexts; in this study we refer to the ability to solve such problems after instruction as evidence of learning (e.g. Heijltjes et al., Citation 2014b ). However, it was shown that CT-skills required for unbiased reasoning consistently failed to transfer to novel problem types that have different structural features yet share underlying principles, i.e. far transfer, even when using instructional methods that proved effective for fostering transfer in various other domains. These methods, administered after initial instruction, were encouraging students to self-explain during practice (Van Peppen et al., Citation 2018 ; Heijltjes et al., Citation 2014a , Citation 2014b , Citation 2015 ) and offering variable as opposed to blocked practice with examples or problems (i.e. interleaved practice; Van Peppen et al., Citation 2021c ). Other methods involved comparing correct and erroneous worked out examples (Van Peppen et al., Citation 2021a ) and repeated retrieval practice (i.e. testing effect; Van Peppen et al., Citation 2021b ). Additionally, a recent study with teachers who were trained on (teaching) CT in three sessions and engaged in effortful learning activities (i.e. designing a CT-task; Janssen et al., Citation 2019 ), found no evidence of transfer to novel problems.
These findings raise the question of what obstacle(s) underlie(s) the lack of transfer of CT-skills required for unbiased reasoning. According to the three-step process of transfer (Barnett & Ceci, Citation 2002 ), the lack of transfer in previous studies could lie in a recognition, recall, or application problem. As mentioned above, understanding the obstacle(s) underlying (un)successful transfer is crucial to design courses to achieve it and, moreover, is relevant for theories of learning and transfer.
In the current study, we, therefore, investigated different conditions during the final test procedure that support the recognition, recall, and application steps in the transfer process (cf. Butler et al., Citation 2013 , Citation 2017 ; for a similar procedure, see Gick & Holyoak, Citation 1980 , Citation 1983 ). By comparing the effects of support for different steps in the process, we infer where difficulties arise for learners. We simultaneously conducted two experiments: Experiment 1 in a laboratory setting and Experiment 2 in a classroom setting (i.e. replication experiment to assess the robustness of our findings and to increase ecological validity). Participants first completed a pretest and, thereafter, received video-instructions on CT and on specific CT-tasks. Subsequently, they practiced with these tasks on domain-specific problems, followed by correct-answer feedback and a worked example. Finally, participants completed a posttest—including learning (i.e. same problem type but different story contexts), near transfer (i.e. same problem type but offered in a different/less abstract format), and far transfer (i.e. similar principles but different problem types: see method section for more information) items.
The experimental intervention took place during the posttest. Participants were randomly allocated to one of four conditions, in which they completed the near and far transfer posttest items: (1) without receiving support (no support condition), (2) while receiving hints that the information provided in the learning phase is relevant for these items (recognition support condition), (3) while receiving hints that the information provided in the learning phase is relevant and being prompted to recall the acquired knowledge (free recall condition), or (4) while receiving hints that the information provided in the learning phase is relevant and receiving a reminder of the paper-based overview of that information that they received prior to the transfer tasks (recall support condition).
Published online:
Table 1. the logic behind the procedure used..
The hypotheses, planned analyses, and method section were preregistered on the Open Science Framework (OSF). Detailed descriptions of the design and procedures and all data/script files and materials (in Dutch) are publicly available on the project page we created for this study (osf.io/ybt5g).
Participants
Participants were 196 first-year and second-year Psychology students attending a Dutch University. Of these, two students were unable to complete the free recall due to an experimenter error and six students did not adhere to instructions (i.e. they copied information from the CT-instructions). They were therefore excluded from the analyses and this resulted in a final sample size of 188 students ( M age = 20.59, SD = 2.53; 69 males). Four students who were originally allocated to the recall support condition did not receive the reminder of the information provided in the learning phase and were therefore automatically assigned to the recognition support condition (i.e. they only received the recognition support).
Figure 1. Overview of the study design. The four conditions differed in amount of support received while completing the near and far transfer items of the posttest.
All materials were administered as an online survey with a forced response-format using Qualtrics Survey Software (Qualtrics, Provo, UT; http://www.qualtrics.com ).
CT-skills tests
In line with previous research on avoiding bias in reasoning and decision-making, we used several heuristics-and biases tasks as measures of CT (e.g. Stanovich et al., Citation 2016 ; Tversky & Kahneman, Citation 1974 ; West et al., Citation 2008 ). As mentioned in the introduction, learning/transfer occur on a continuum and represent different gradients of similarity (not necessarily difficulty) with the initial CT-tasks. Learning via isomorphic problems with the same structural features as the initial tasks but different superficial features (i.e. different topic/cover story) is considered as evidence of learning and transferring knowledge or skills to a very similar situation to the initial task or situation is considered “near” transfer. Given that the initial tasks were general syllogistic reasoning tasks, we developed syllogistic reasoning tasks in a slightly different format to assess near transfer. Transferring between situations that share similar structural features but, on appearance, seem remote and alien to one another is considered “far” transfer. Hence, we used Wason selection tasks, that are novel tasks but share similar principles with syllogistic reasoning tasks, to assess far transfer. Thus, students’ performance was measured on general syllogistic reasoning tasks with different story contexts (to assess learning), syllogistic reasoning tasks in a different/less abstract format, i.e. vignettes (to assess near transfer), and Wason selection tasks that are novel tasks but share similar principles with syllogistic reasoning tasks (to assess far transfer) both on a pretest and immediate posttest. The pretest and posttest contained parallel versions of the learning, near transfer, and far transfer items. To illustrate, a posttest item contained the exact same wording as the respective pretest items but, for instance, described a different company.
In all tasks, belief bias played a role. Belief bias occurs when the conclusion aligns with prior beliefs or real-world knowledge (i.e. is believable) but is invalid, or vice versa (Evans et al., Citation 1983 ; Markovits & Nantel, Citation 1989 ; Newstead et al., Citation 1992 ). These tasks require that one recognizes the need for analytical and reflective reasoning (i.e. based on knowledge and rules of logic) and switches to this type of reasoning. This is only possible, however, when heuristic responses are successfully inhibited. Example items of each task category are provided in Appendix B. For the sake of comparability, the content of the surface features (cover stories) of all test items was the same for both experiments and was based on the study domain of participants of Experiment 2 (because that experiment was conducted as part of an existing course), namely “Biology and Medical Laboratory Research” and “Chemistry”. The content of the tasks referred to very general knowledge these students could be expected to hold. In the tasks, the logical validity of the conclusions conflicted strongly with that general knowledge (i.e. the tasks likely evoked belief biases). The content of all materials was evaluated and approved by a teacher working in the domain (who also taught CT as part of her courses), to ensure that the tasks were authentic and fit for the study purpose (e.g. the teacher evaluated the believability of the conclusions, as well as the equivalence of pretest and posttest tasks).
Learning items
Each test contained eight conditional syllogistic reasoning items that measured learning (hence, hereafter referred to as learning items), as these were instructed and practiced during the learning phase. All items included a belief bias and examined the tendency to be influenced by the believability of a conclusion when evaluating the logical validity of arguments (Evans, Citation 2003 ; Evans et al., Citation 1983 ). Conditional syllogisms consist of a premise including a conditional statement and a premise that either affirms or denies either the antecedent or the consequent. Our tests contained 2 × affirming the consequent of a conditional (if p then q, q therefore p ; conclusion invalid but believable); 2 × denying the consequent of a conditional (if p then q , not q therefore not p ; conclusion valid but unbelievable); 2 × affirming the antecedent of a conditional (if p then q , p therefore q ; conclusion valid but unbelievable); and 2 × denying the antecedent of a conditional (if p then q , not p therefore not q ; conclusion invalid but believable). Participants had to indicate for each item whether the conclusion is valid or invalid. Thereafter, they were asked to explain their multiple-choice answer. The forced response-format of these items required them to guess if they did not know the answer.
Near transfer items
For each test, we constructed six short vignettes (about 100 words) to assess whether students are able to evaluate the logical validity of arguments in a written news item or article on a topic that participants might encounter in their working life. Each vignette contained a logically invalid but believable conclusion or a logically valid but unbelievable conclusion from two given premises (i.e. conditional syllogisms). These items reflected near transfer items as they were offered in a different format/situation compared to the learning phase. Participants were instructed to read the text thoroughly, to indicate whether the conclusion in the text is valid or invalid, and to provide an explanation. To illustrate, students read a short text from an article about a novel vaccine against HIV/AIDS developed in the Netherlands, stating that if a country develops a particular vaccine against a virus, the risk of that virus is higher in that country than elsewhere. Students were asked to indicate whether the conclusion that there is a higher risk of HIV in the Netherlands than elsewhere, is valid or invalid based on the information given in the text (correct answer is “valid”, for more information see Appendix B).
Far transfer items
Each test contained six Wason selection items that measured the tendency to confirm a hypothesis rather than to falsify it (adapted from Evans, Citation 2002 ; Gigerenzer & Hug, Citation 1992 ). These items reflected far transfer items as they were not explicitly instructed and practiced during the learning phase but shared similar features with the four forms of conditional syllogistic reasoning (i.e. each item required recall and application of all four conditional syllogism principles to solve it correctly). For each of the two forms of Wason selection items (abstract or concrete, with the latter being study-related), there were three test items. A multiple-choice forced-response format with four answer options was used (cf. four forms of conditional syllogistic reasoning) in which only a specific combination of two selected answers was the correct answer. Thereafter, participants were asked to explain their multiple-choice answer. Again, all correct answers were related to reasoning strategies and incorrect answers were related to biased reasoning. For example, students were presented with four medical files, with information about the cause of death on the one hand (unnatural or natural) and whether or not autopsy has been conducted. They were provided with the rule that “if there are indications of an unnatural death, autopsy will be conducted” and asked which medical files they should read to check if the rule is correct (correct answer is “unnatural death file” + ”no autopsy file”, for more information see Appendix B).
Supporting prompts
Depending on assigned condition, participants received different levels of support while completing the near and far transfer items of the posttest. Participants in the no support condition completed the near and far transfer items without receiving additional support. In the recognition support condition, participants received a prompt that emphasized the relevance of the information provided in the learning phase: “To solve this task, you can use the rules of logic explained in the instructions”. In the free recall condition, participants were first asked to recall the rules of logic explained in the instruction and to write them down on the blank paper they received. Then participants completed each near and far transfer item while receiving the following prompt: “To solve this task, you can use the rules of logic explained in the instructions that you tried to recall beforehand. Take that paper to solve the task”.
In the recall support condition, participants were requested to pick up a paper from the experiment leader and they received a prompt that emphasized the relevance of the information provided in the learning phase and that indicated where they could find this information: “To solve this task, you can use the rules of logic explained in the instructions. You can find these rules in the overview on the paper that you have received. Take that paper to solve the task”. For the detailed description of the supporting prompts and the rules of logic that participants in the recall support condition receive, see Appendix A.
CT-instructions
The video-based CT-instructions (15 min) consisted of a general instruction on CT and explicit instructions on avoiding belief-bias in syllogistic reasoning. In the general instruction, the features of CT and the attitudes and skills that are needed to think critically were described. These were followed by the explicit instructions on rules of logic and avoiding belief-bias in syllogistic reasoning, which consisted of a worked example of each form of syllogistic reasoning included in the pretest. The worked examples not only showed the rationale behind the solution steps but also included possible problem-solving strategies which allowed participants to mentally correct initially erroneous responses. The explicit instructions served to stimulate students to inhibit heuristic responses when needed, but, given that that may not be enough to prevent bias in reasoning if they lack the necessary mindware, the mindware (i.e. knowledge and rules of logic) was taught as well. At the end of the video-based instruction, participants received a hint stating that the principles used in these examples can be applied to several other reasoning tasks.
CT-practice
After the video-based instruction, participants practiced with the four types of syllogistic reasoning problems of the pretest and explicit instructions, on topics that they might encounter in their working-life. Participants were instructed to read the problems thoroughly, to choose the best multiple-choice answer option, and to give a written explanation of how the answer was obtained in a text entry box below the multiple-choice question. After each practice-task, participants received correct-answer feedback (e.g. “You gave the following answer: conclusion follows logically from the two premises. This answer is incorrect”.) and were given a worked example that consisted of the problem statement and a correct solution to this problem. The line of reasoning and the underlying principles were explained in steps and clarified with a visual representation. Again, participants were asked to read the worked examples thoroughly before they continued to the next problem. The content of the surface features (cover stories) of all practice items was adapted to the study domain of participants of Experiment 2 (i.e. Biology and Medical Laboratory Research/Chemistry), because that experiment was conducted in a classroom setting as part of an existing course.
Experiment 1 was run in the computer lab of the university and lasted circa 90 min. One experiment leader (first author of this paper or research assistant) was present during all phases of the experiment. Participants were seated in individual cubicles, where A4-papers were distributed before they arrived. These papers contained some general rules, a link to the Qualtrics environment where all materials were delivered, and a blank page that was only needed for participants in the free recall condition. The experiment leader first introduced herself and provided some basic information about the experiment. Afterwards, she instructed participants to read the A4-paper containing some general instructions and a link to the Qualtrics environment where they first signed an informed consent form.
Next, participants filled out a short demographic questionnaire and completed the pretest. Thereafter, participants entered the learning phase in which they viewed the video (15 min.) Including the general CT-instruction and the explicit instructions, followed by the four practice problems. Immediately after the learning phase, they took a short break of four minutes in which they could relax or move about. Next, participants completed the learning items of the posttest. Subsequently, the Qualtrics program randomly assigned the participants to one of the four conditions. Depending on assigned condition, participants received different levels of support while completing the near and far transfer items of the posttest (see supporting prompts subsection). Participants could work at their own pace and time-on-task was logged during all phases. Furthermore, participants could use scrap paper during the practice phase and the CT-tests.
Data analysis
Unbiased reasoning items were scored for accuracy based on multiple-choice responses and explanations, using a coding scheme that can be found in the Appendices (see Appendix C). Specifically, each correct multiple-choice answer was worth 0.5 point and a correct explanation was worth 1 point, a partially correct explanation received 0.25–0.5 point, and an incorrect explanation was awarded 0 points. The scores were summed, resulting in a maximum score of 12 points on the learning items, 9 points on the near transfer items, and 9 points on the far transfer items. Unfortunately, one near transfer item had to be removed because it was inconsistent in difficulty between test moments, as the belief bias was less effective in the pretest compared to the posttest, making it relatively easier on the pretest. Footnote † As a result, a total score of 7.5 points could be gained on near transfer items. Two raters independently scored 25% of the posttest. Intra-class correlation coefficients were 0.985 for the learning test items, 0.989 for the near transfer test items, and 0.977 for the far transfer items. After the discrepancies were resolved by discussion, the remainder of the tests was scored by one rater.
To explore whether participants’ ability to recall the acquired knowledge underlies difficulties with transfer, free recall was scored, using another coding scheme (see Appendix D). Participants in the free recall condition could earn a maximum of 1 point per rule of logic correctly retrieved (in steps of 0.5), resulting in a maximum total score of 4 points on retrieved information. The two raters independently scored all free recall data. Intra-class correlation coefficients were .963 (nothing written down coded as no recall) and .998 (nothing written down coded as missing value).
Reliability (Cronbach’s alpha) of the learning items was .56 on the pretest and .75 on the posttest, reliability of the near transfer items was .51 on the pretest and .71 on the posttest, and reliability of the far transfer items was .74 on the pretest and .92 on the posttest. It was expected that participants would have very limited knowledge relative to these tasks at the outset, and therefore were unable to generate coherent explanations (and may even have had to guess), leading to low variability and low alphas at pretest. Posttest alphas are thus more indicative of the reliability of these tasks when respondents are presumed to have some knowledge or exposure to the content being assessed.
We created boxplots to identify outliers (i.e. values that fall more than 1.5 times the interquartile range above the third quartile or below the first quartile) in the data. If there were any, we first conducted the analyses on the data of all participants who completed the experiment (i.e. including outliers) and reran the analyses on the data without outliers. If outliers influenced on the results, we reported the results of both analyses. If the results were the same, we only reported the results on the full data.
Figure 2. Violin plots with the full distribution per condition and test moment (i.e. pretest and posttest) on performance on learning items (maximum total score of 12) in Experiment 1.
Figure 3. Violin plots with the full distribution per condition and test moment (i.e. pretest and posttest) on performance on near transfer items (maximum total score of 7.5) in Experiment 1.
Figure 4. Violin plots with the full distribution per condition and test moment (i.e. pretest and posttest) on performance on far transfer items (maximum total score of 9) in Experiment 1.
Performance on learning items
Table 2. experiment 1: mean (sd) of test performance (number of items correct) on learning (0–12), near transfer (0–7.5), and far transfer items (0–9) and mean (sd) of time-on-task (in seconds) on learning, near transfer, and far transfer items per condition., table 3. experiment 1: pearson correlation matrix ( p -value) for the learning and transfer measures., performance on near and far transfer items.
Figure 5. Graphical representation of the relationship between retrieved information during free recall and posttest near transfer performance in Experiment 1. Two measures of retrieved information were used: nothing written down was either coded as no recall or as missing value.
Figure 6. Graphical representation of the relationship between retrieved information during free recall and posttest far transfer performance in Experiment 1. Two measures of retrieved information were used: nothing written down was either coded as no recall or as missing value.
Time-on-test
We also explored differences over time and among conditions in the time spent on test items (in seconds). Descriptive statistics are provided in Table 2 . A paired samples t-test with Test Moment (pretest and posttest) as within-subjects factor on time spent on learning items revealed that the mean time was lower for the posttest items ( M = 52.76, SD = 21.77) than the pretest items ( M = 80.76, SD = 37.43), t (187) = 11.98, p < .001, d = 0.91. Footnote §
We simultaneously conducted a replication experiment in a classroom setting to assess the robustness of our findings and to increase ecological validity. The educational committee of the university approved on conducting this study within the curriculum. The design and materials were the same as that of Experiment 1.
Participants were 104 third-year “Biology and Medical Laboratory Research” and “Chemistry” students of a University of Applied Sciences. Of these, three students did not complete the complete study due to technical problems and four students did not adhere to instructions (i.e. they copied information from the CT-instructions). They were therefore excluded from the analyses and this resulted in a final sample size of 97 students ( M age = 20.39, SD = 1.67; 23 males).
The main difference with Experiment 1 was that Experiment 2 was run in a real education setting, namely during the first lesson of a CT-course. In the following lessons, the origins of the concept of CT, inductive and deductive reasoning, and the occurrence of biases in participants’ own work, for example, were discussed, among others. The experiment was conducted in a computer classroom at the participants’ university with an entire class of students present. Participants came from five different classes (of 17–23 participants) and were randomly distributed among the four conditions within each class. In advance of the experiment, students were informed about the experiment by their teacher. The experiment leader (first author) and the teacher of the CT-course were present during the experiment. When entering the classroom, participants were instructed to sit down at one of the desks. The experiment leader first introduced herself and provided some basic information about the experiment. Afterwards, she instructed participants to read a sheet of paper containing some general instructions and a link to the Qualtrics environment where they first signed an informed consent form. Again, participants could work at their own pace and time-on-task was logged during all phases. Furthermore, participants could use scrap paper during the practice phase and the CT-tests. Participants had to wait (in silence) until the last participant had finished the posttest before they could leave the classroom.
The same coding schemes were used as in Experiment 1. Again, a total score of 12 points could be earned on learning items, of 7.5 points on near transfer items, and of 9 points on far transfer items. Again, two raters independently scored all free recall data. Intra-class correlation coefficients were .987 (nothing written down coded as no recall) and .971 (nothing written down coded as missing value).
Reliability (Cronbach’s alpha) on the pretest and posttest, respectively, of the learning items were .45 and .68; of the near transfer items were .32 and .67; and of the far transfer items .77 and .89. While these low reliabilities on the pretest might again be explained by lack of prior knowledge, they are substantially lower in experiment 2 than in experiment 1, and under these circumstances, the probability of detecting a significant effect (given one exists) is low (e.g. Cleary et al., Citation 1970 ; Rogers & Hopkins, Citation 1988 ), and therefore, the chance that Type 2 errors may have occurred in the current study is relatively high. Therefore, we conducted alternative analyses (see Results section), as preregistered.
Two participants had two missing near transfer answers on the posttest, which were replaced by their series mean. One participant did not fill in the far transfer items of the posttest, so data for this participant were not included in the analyses involving the respective measure.
Figure 7. Violin plots with the full distribution per condition and test moment (i.e. pretest and posttest) on performance on learning items (maximum total score of 12) in Experiment 2.
Figure 8. Violin plots with the full distribution per condition and test moment (i.e. pretest and posttest) on performance on near transfer items (maximum total score of 7.5) in Experiment 2.
Figure 9. Violin plots with the full distribution per condition and test moment (i.e. pretest and posttest) on performance on far transfer items (maximum total score of 9) in Experiment 2.
Table 4. Experiment 2: mean (SD) of test performance (number of items correct) on learning (0–12), near transfer (0–7.5), and far transfer items (0–9) and mean (SD) of time-on-task (in seconds) on learning, near transfer, and far transfer items per condition.
Table 5. experiment 2: pearson correlation matrix ( p -value) for the learning and transfer measures..
Figure 10. Graphical representation of the relationship between retrieved information during free recall and posttest near transfer performance in Experiment 2. Two measures of retrieved information were used: nothing written down was either coded as no recall or as missing value.
Figure 11. Graphical representation of the relationship between retrieved information during free recall and posttest far transfer performance in Experiment 2. Two measures of retrieved information were used: nothing written down was either coded as no recall or as missing value.
We exploratory analyzed the time spent on test items (in seconds). Descriptive statistics are provided in Table 4 . A Paired samples t-test with Test Moment (pretest and posttest) as within-subjects factor on time spent on learning items revealed that the mean time spent on posttest items ( M = 52.76, SD = 21.77) was lower than on pretest items ( M = 80.76, SD = 37.43), t (97) = 9.88, p < .001, d = 1.11.
Performance differences across study domains
The present study aimed to identify obstacles to transfer of CT-skills required for unbiased reasoning. Prior studies observed a lack of transfer of these CT-skills (e.g. Van Peppen et al., Citation 2018 , Citation 2021a , Citation 2021b , Citation 2021c ; Heijltjes et al., Citation 2014a , Citation 2014b , Citation 2015 ), and we examined whether this would be due to (a) failure to recognize that the acquired knowledge is relevant to the new task, (b) inability to recall the acquired knowledge, or (c) difficulties in actually mapping that knowledge onto the new task (cf. the three-step model of transfer: Barnet & Ceci, Citation 2002 ).
Benefits of instruction and practice
In line with our expectations and consistent with earlier research (e.g. Abrami et al., Citation 2014 ; Heijltjes et al., Citation 2014b ), we found that providing students with explicit instructions and practice (during the pretest and practice phase) is associated with a performance gain in unbiased reasoning and a reduction in test-taking time in two experiments. These results further support the idea of Stanovich ( Citation 2011 ) that acquisition of relevant knowledge structures and stimulating students to engage in CT, is useful to prevent biased reasoning. As people gain expertise, they can often attain an equal/higher level of performance with less/equal time investment. As such, these findings appear to be consistent with the notion that a relatively brief instructional intervention including explicit instructions and practice opportunities is both effective and efficient for learning and transfer of CT-skills, which is promising for educational practice. However, we should stress that our research design does not permit us to draw causal conclusions about the effectiveness of the instructions-plus-practice intervention from our experiments. This is because our manipulation occurred in the test-phase. We did not include a control group with a different intervention or a no-intervention –this was not required given our central research question and the beneficial effects of this type of training have already been well-established in comparison to several control conditions (e.g. Heijltjes et al., Citation 2014b ).
Interestingly, our experiments suggest that these instructions and practice activities may also enhance transfer (both to similar tasks in a different format and to novel task types) to some extent: students showed better performance on posttest transfer tasks, and, again, with reduced test-taking time. As one would expect (Barnett & Ceci, Citation 2002 ; Bray, Citation 1928 ; Dinsmore et al., Citation 2014 ), transfer between closely related situations occurred more often than transfer between situations that had less in common: performance gains were highest on learning items (i.e. same problem type but different story contexts), followed by near transfer items (i.e. same problem type but offered in a different/less abstract format), and thereafter far transfer items (i.e. similar principles but applied to novel problem types).
It is particularly promising that participants improved noticeably on near transfer items after a relatively short instruction and practice phase. These items consisted of belief biases in written news items or articles on topics that participants might encounter in other courses and their working life. The few studies that investigated effects of instruction/practice on transfer of CT-skills, and failed to find evidence of transfer, only examined tasks reflecting far transfer (Van Peppen et al., Citation 2018 ; Heijltjes et al., Citation 2014a , Citation 2015 ). We even observed some increase in performance on far transfer items in the present study. Other studies did not include these items on the pretest (Van Peppen et al., Citation 2021a , Citation 2021b , Citation 2021c ) and were, therefore, not able to detect transfer gains . It could also be argued that pre-testing had some effect on the posttest scores and, moreover, masked the effect of the experimental manipulation, although this seems unlikely given that participants did not receive feedback on their performance and the posttest scores were still rather low. Thus, our findings are promising as they seem to support the idea that instruction/practice can be beneficial for near and far transfer of CT-skills. However, there was a lot of room for improvement, yet students did not seem to benefit from the support conditions, as we will discuss in the next section.
Obstacles to successful transfer of CT-skills
As for our main question regarding the obstacles to successful transfer of CT-skills, our findings suggest that participants were able to recognize that the acquired knowledge was relevant to the new task and to recall that knowledge: they did not benefit from recognition and recall support (i.e. there were no significant differences among conditions). Thus, our findings suggest that students may have had difficulties in applying the relevant knowledge on the new tasks (Hypothesis 3).
However, findings from the free recall condition do not fully support the idea that it is only an application/mapping problem. Most participants did not retrieve all relevant information and exploratory results pointed to moderate-to-large positive correlations between participants’ retrieved knowledge and their performance on near transfer (in both experiments) and far transfer (only in Experiment 1 when nothing written down was coded as no recall) items. Although exploratory analyses might lack statistical rigor, these results provide insight into further avenues to explore the relation between knowledge retrieval and transfer: this finding may suggest that suboptimal recall could also have played a role in unsuccessful transfer (Hypothesis 2b). Descriptive statistics support this idea: participants who received recall support numerically outperformed the other conditions on far transfer items at posttest in Experiment 1 and on near transfer items at posttest in Experiment 2. Because the power of our study was only sufficient to pick up medium-to-large interaction effects and it may be that providing recall support had a small effect on transfer, a further study with a more powerful design (e.g. a larger sample size) is suggested.
Interestingly, previous studies on analogical transfer (Gick & Holyoak, Citation 1980 , Citation 1983 ) showed that recognition is often the barrier to transfer. Contrary to these studies, participants in the current study were aware that they received instructions on CT (in Experiment 2 even during an CT-course), which could have helped them recognize that the knowledge learned had to be transferred to the new task. Various other studies, however, revealed that students often have application problems in novel situations (i.e. inert knowledge problem, see Renkl et al., Citation 1996 ). It seems possible that students in the current study did not know how to use the acquired knowledge in a novel situation because the knowledge was not available in a form that allows for direct application (i.e. structure deficit). Future research on instructional interventions that focuses more on the recall and application steps in the transfer process, for instance by having students repeatedly retrieving and applying knowledge to different examples (Butler et al., Citation 2017 ; Carpenter, Citation 2012 ) while providing explanation feedback (Butler et al., Citation 2013 ; Van Eersel et al., Citation 2016 ), would be of great help in establishing how to successfully promote transfer of CT-skills.
Fruitful next steps would be to replicate our finding that the difficulty of transfer of CT-skills lies in inadequate application/mapping and to support this finding by (conceptual) replications (with other types of CT-tasks). A further study could, for instance, teach students about certain subject matter and let them consult a full solution procedure to tasks related to that subject matter (thus eliminating the need to recognize and retain knowledge) while completing tasks that vary in overlap with the subject-matter knowledge. In one condition, students complete isomorphic tasks, in another condition near transfer tasks, and in a third condition far transfer tasks. If performance decreases over these conditions, that would provide further evidence for the assumption that the difficulty of transfer lies in inadequate application/mapping. Another research question that could be addressed in qualitative studies is why students have application problems in novel situations. Do they have difficulties adapting the acquired mindware (i.e. inert knowledge problem: e.g. Renkl et al., Citation 1996 ) or with suppressing heuristic responses to novel problems, or both?
One potential limitation of this study concerns the short training duration. While it is interesting to see that this relatively brief training already had beneficial effects on learning and near transfer, gaining deep understanding of the underlying principles of the subject matter (i.e. meaningful knowledge structures), required for far transfer, might need more extensive or longer training. Even though our results indicate that participants learned to solve abstract CT-tasks (i.e. syllogisms), their subject-matter knowledge may have been insufficient for identifying structural overlap between problems and, consequently, for solving more complex or novel CT-tasks. The challenge for researchers and educational practitioners (e.g. consultants, teachers) in the CT-domain is to develop instructional designs that contribute to actively constructing meaning from the to-be-learned information (i.e. generative processing; e.g. Fiorella & Mayer, Citation 2016 ; Wittrock, Citation 2010 ), which is conditional for recall and application. Ways to stimulate generative processing are, for instance, encouraging elaboration, questioning, or explanation during practice or having students repeatedly retrieve to-be learned information from memory. Although prior studies did not show beneficial effects of such instructional strategies with regard to improving transfer of CT, these were also studies with relatively short training session. Another possible direction could be to provide exemplars of knowledge application while gradually remove scaffolding (cf. four-component instructional design model; Van Merriënboer et al., Citation 1992 ) or while fading from concrete-to-abstract situations (i.e. concreteness fading; McNeil & Fyfe, Citation 2012 ).
Another potential limitation of the study is that one might ask if the hint provided at the end of the CT-instructions could have “washed out” condition effects. However, note that this was a very generic statement, so no replacement for the specific recognition support given during the transfer phase. Moreover, we should note that there was a practice phase in between the CT-instructions and the transfer phase.
Given that multiple studies reported rather low levels of reliability of tests consisting of heuristics-and-biases tasks (Aczel et al., Citation 2015a ; West et al., Citation 2008 ) and revealed concerns with the reliability of widely used standardized CT tests, particularly with regard to subscales (Bernard et al., Citation 2008 ; Bondy et al., Citation 2001 ; Ku, Citation 2009 ; Leppa, Citation 1997 ; Liu et al., Citation 2014 ; Loo & Thorpe, Citation 1999 ), we aimed to increase reliability of our measures. Therefore, we included multiple items of one CT-task category to narrow down the test into a single measurable construct and, thereby, to decrease measurement error (LeBel & Paunonen, Citation 2011 ), which resulted—except on the pretest—in quite reliable measures. However, because of this, we focused on only one, albeit highly important, aspect of CT, namely overturning belief-biased responses when evaluating the logical validity of arguments (De Chantal et al., Citation 2019 ; Evans, Citation 2003 ). Although this is just one aspect of CT, it should be noted that heuristics and biases tasks represent how people make judgements under uncertain or varied contexts (e.g. heuristics and biases appear in newspapers, books, courses, and applications of many kinds) and the current study thus provides valuable insight into how people think and reason. Especially since (un)biased reasoning was assessed in the context of the level of individual study domain—contrary to standardized CT-tests and most research on heuristics and biases—and could, therefore, be evaluated within authentic contexts. Hence, participants’ performance on these heuristics and biases tasks presumably offers a realistic view of everyday reasoning (see, for example, Gilovich et al., Citation 2002 ). Relevant next steps would be to investigate effects of instruction/practice on other types of reasoning biases, for instance those involving probabilistic reasoning. In particular, since it has been shown that effective “debiasing” training methods are not always effective for avoiding all types of biases (see, for example, Aczel et al., Citation 2015b ); these methods may be less helpful for overcoming biases related to less abstract principles for which there is no concrete alternative strategy.
A noteworthy strength of this study was that we simultaneously conducted a replication experiment in a classroom setting to assess the robustness of our findings and to increase ecological validity. As promising interventions sometimes fail in more realistic settings (e.g. Hulleman & Cordray, Citation 2009 ) and classroom studies aimed at fostering transfer of CT-skills are relatively rare, this study provides valuable new insights for educational practice. To wit, that transfer of CT-skills from abstract tasks to domain relevant texts and to novel task types can be established with a relatively short instruction and practice phase. However, there is still a lot of room for improvement in bringing about far transfer, and for that, obstacles such as suboptimal recall and application should be countered. Considerably more studies, preferably including direct or conceptual replications to increase robustness of findings, are needed to develop a full picture of effective ways to teach (far) transfer of CT-skills.
To conclude, the present study established that it is possible to foster students’ learning and transfer of CT-skills to different formats/situations and novel task types through a relatively simple intervention. Our findings suggest that difficulties in (far) transfer are mainly due to an inability to apply relevant knowledge onto novel problems and exploratory analyses point to the possibility that suboptimal recall may play a role as well. Students seemed to have no problems recognizing that the acquired knowledge was relevant to the new problem. Hence, this study suggests that instructional interventions aimed at transfer of CT-skills should focus particularly on the application and possibly also on the recall steps in the transfer process. Nevertheless, more research is needed to corroborate this conclusion and to find out why students have application problems in novel situations. As far as we know, our study was the first to systematically vary gradients of similarity between the initial CT-task and the transfer task (i.e. learning, near transfer, and far transfer) and, thus, adds to the small body of literature on whether instruction/practice can foster students’ CT. Understanding the obstacle(s) underlying (un)successful transfer is crucial to design courses to achieve it and, moreover, is relevant for theories of learning and transfer.
* p < .05.
* p < .05.
The authors would like to thank Ilse Hartel – Slager and Marjolein Looijen for their help with running this study, Anita Heijltjes and Eva Janssen for their input on the materials, and the members of the Disciplined Reading & Learning Research Laboratory of the University of Maryland for their input on the discussion.
No potential conflict of interest was reported by the author(s).
Data availability statement
The datasets and script files are stored on an Open Science Framework (OSF) page for this project, see osf.io/ybt5g.
† More specifically, students’ explanations accompanying this pretest item revealed that the first premise was generally considered believable, while it was developed to seem unbelievable. Consequently, the conclusion was presumably believable to them (i.e., Valid and believable). Their explanations accompanying the equivalent posttest item revealed that they generally considered the first premise there to be unbelievable (as intended; false and unbelievable). The chance of a correct answer was, therefore, lower on the posttest than the pretest due to a belief bias. To avoid falsely showing decrease or no progress after instruction/practice on this item, we decided to exclude it from the analyses.
‡ For clarification, we did not compare the four support conditions on performance on learning items data because the manipulation took place after all learning items were completed.
§ For clarification, we did not compare the four support conditions on time spent on learning items data because the manipulation took place after all learning items were completed.
** We also conducted some exploratory analyses regarding students’ study background and the time participants spent on the CT-instructions. However, these analyses did not have much added value for this paper, and, therefore, are not reported here but provided on our OSF-page.
†† Because of severe violations of the normality assumption, we additionally conducted a Kruskal-Wallis H Test (nonparametric alternative of ANOVA); however, the results did not differ from the parametric analyses and, therefore, are not reported in this paper but provided on our OSF-page.
- Abrami, P. C. , Bernard, R. M. , Borokhovski, E. , Waddington, D. I. , Wade, C. A. , & Persson, T. ( 2014 ). Strategies for teaching students to think critically: A meta-analysis . Review of Educational Research , 85 (2), 275 – 314 . https://doi.org/10.3102/0034654314551063 [Crossref] , [Web of Science ®] , [Google Scholar]
- Abrami, P. C. , Bernard, R. M. , Borokhovski, E. , Wade, A. , Surkes, M. A. , Tamim, R. , & Zhang, D. ( 2008 ). Instructional interventions affecting critical thinking skills and dispositions: A stage 1 meta-analysis . Review of Educational Research , 78 (4), 1102 – 1134 . https://doi.org/10.3102/0034654308326084 [Crossref] , [Web of Science ®] , [Google Scholar]
- Aczel, B. , Bago, B. , Szollosi, A. , Foldes, A. , & Lukacs, B. ( 2015a ). Is it time for studying real-life debiasing? Evaluation of the effectiveness of an analogical intervention technique . Frontiers in Psychology , 6 , 1120 . https://doi.org/10.3389/fpsyg.2015.01120 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Aczel, B. , Bago, B. , Szollosi, A. , Foldes, A. , & Lukacs, B. ( 2015b ). Measuring individual differences in decision biases: Methodological considerations . Frontiers in Psychology , 6 , 1770 . https://doi.org/10.3389/fpsyg.2015.01770 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Barnett, S. M. , & Ceci, S. J. ( 2002 ). When and where do we apply what we learn?: A taxonomy for far transfer . Psychological Bulletin , 128 (4), 612 – 637 . https://doi.org/10.1037/0033-2909.128.4.612 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Baron, J. ( 2008 ). Thinking and deciding ( 4th ed. ). Cambridge University Press . [Google Scholar]
- Barreiros, J. , Figueiredo, T. , & Godinho, M. ( 2007 ). The contextual interference effect in applied settings . European Physical Education Review , 13 (2), 195 – 208 . https://doi.org/10.1177/1356336X07076876 [Crossref] , [Web of Science ®] , [Google Scholar]
- Bassok, M. , & Holyoak, K. J. ( 1989 ). Interdomain transfer between isomorphic topics in algebra and physics . Journal of Experimental Psychology: Learning, Memory, and Cognition , 15 (1), 153 . https://doi.org/10.1037/0278-7393.15.1.153 [Crossref] , [Web of Science ®] , [Google Scholar]
- Bernard, R. M. , Zhang, D. , Abrami, P. C. , Sicoly, F. , Borokhovski, E. , & Surkes, M. A. ( 2008 ). Exploring the structure of the watson–glaser critical thinking appraisal: One scale or many subscales? Thinking Skills and Creativity , 3 (1), 15 – 22 . https://doi.org/10.1016/j.tsc.2007.11.001 [Crossref] , [Web of Science ®] , [Google Scholar]
- Bondy, K. N. , Koenigseder, L. A. , Ishee, J. H. , & Williams, B. G. ( 2001 ). Psychometric properties of the California critical thinking tests . Journal of Nursing Measurement , 9 (3), 309 – 328 . https://doi.org/10.1891/1061-3749.9.3.309 [Crossref] , [PubMed] , [Google Scholar]
- Bray, C. W. ( 1928 ). Transfer of learning . Journal of Experimental Psychology , 11 (6), 443 . https://doi.org/10.1037/h0071273 [Crossref] , [Google Scholar]
- Butler, A. C. , Black-Maier, A. C. , Raley, N. D. , & Marsh, E. J. ( 2017 ). Retrieving and applying knowledge to different examples promotes transfer of learning . Journal of Experimental Psychology: Applied , 23 (4), 433 – 446 . https://doi.org/10.1037/xap0000142 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Butler, A. C. , Godbole, N. , & Marsh, E. J. ( 2013 ). Explanation feedback is better than correct answer feedback for promoting transfer of learning . Journal of Educational Psychology , 105 (2), 290 – 298 . https://doi.org/10.1037/a0031026 [Crossref] , [Web of Science ®] , [Google Scholar]
- Carpenter, S. K. ( 2012 ). Testing enhances the transfer of learning . Current Directions in Psychological Science , 21 (5), 279 – 283 . https://doi.org/10.1177/0963721412452728 [Crossref] , [Web of Science ®] , [Google Scholar]
- Cleary, T. A. , Linn, R. L. , & Walster, G. W. ( 1970 ). Effect of reliability and validity on power of statistical tests . Sociological Methodology , 2 , 130 – 138 . https://doi.org/10.1037/a0031026 [Crossref] , [Google Scholar]
- Cohen, J. ( 1988 ). Statistical power analysis for the behavioral sciences ( 2nd. ed., reprint). Psychology Press . [Google Scholar]
- Cormier, S. M. , & Hagman, J. D. ( 2014 ). Transfer of learning: Contemporary research and applications . Academic Press . [Google Scholar]
- Davies, M. ( 2013 ). Critical thinking and the disciplines reconsidered . Higher Education Research & Development , 32 (4), 529 – 544 . https://doi.org/10.1080/07294360.2012.697878 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- De Chantal, P. L. , Newman, I. R. , Thompson, V. , & Markovits, H. ( 2019 ). Who resists belief-biased inferences? The role of individual differences in reasoning strategies, working memory, and attentional focus . Memory & Cognition , 48 , 655 – 671 . https://doi.org/10.3758/s13421-019-00998-2 [Crossref] , [Web of Science ®] , [Google Scholar]
- Dewey, J. ( 1910 ). How we think . D C Heath . [Crossref] , [Google Scholar]
- Dinsmore, D. L. , Baggetta, P. , Doyle, S. , & Loughlin, S. M. ( 2014 ). The role of initial learning, problem features, prior knowledge, and pattern recognition on transfer success . The Journal of Experimental Education , 82 (1), 121 – 141 . https://doi.org/10.1080/00220973.2013.835299 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Druckman, D. , & Bjork, R. A. ( 1994 ). Learning, remembering, believing: Enhancing human performance . National Academy Press . [Google Scholar]
- Duron, R. , Limbach, B. , & Waugh, W. ( 2006 ). Critical thinking framework for any discipline . International Journal of Teaching and Learning in Higher Education , 17 , 160 – 166 . [Google Scholar]
- Evans, J. S. B. ( 2002 ). Logic and human reasoning: An assessment of the deduction paradigm . Psychological Bulletin , 128 (6), 978 – 996 . https://doi.org/10.1037/0033-2909.128.6.978 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Evans, J. S. B. ( 2003 ). In two minds: Dual-process accounts of reasoning . Trends in Cognitive Sciences , 7 (10), 454 – 459 . https://doi.org/10.1016/j.tics.2003.08.012 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Evans, J. S. B. , Barston, J. L. , & Pollard, P. ( 1983 ). On the conflict between logic and belief in syllogistic reasoning . Memory & Cognition , 11 (3), 295 – 306 . https://doi.org/10.3758/BF03196976 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Facione, P. A. ( 1990 ). Critical thinking: A statement of expert consensus for purposes of Educational assessment and instruction . The California Academic Press . [Google Scholar]
- Faul, F. , Erdfelder, E. , Buchner, A. , & Lang, A. G. ( 2009 ). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses . Behavior Research Methods , 41 (4), 1149 – 1160 . https://doi.org/10.3758/BRM.41.4.1149 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Fiorella, L. , & Mayer, R. E. ( 2016 ). Eight ways to promote generative learning . Educational Psychology Review , 28 (4), 717 – 741 . https://doi.org/10.1007/s10648-015-9348- [Crossref] , [Web of Science ®] , [Google Scholar]
- Flores, K. L. , Matkin, G. S. , Burbach, M. E. , Quinn, C. E. , & Harding, H. ( 2012 ). Deficient critical thinking skills among college graduates: Implications for leadership . Educational Philosophy and Theory , 44 (2), 212 – 230 . https://doi.org/10.1111/j.1469-5812.2010.00672.x [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Gentner, D. ( 1983 ). Structure-mapping: A theoretical framework for analogy . Cognitive Science , 7 (2), 155 – 170 . https://doi.org/10.1016/S0364-0213(83)80009-3 [Crossref] , [Web of Science ®] , [Google Scholar]
- Gentner, D. ( 1989 ). The mechanism of analogical learning . In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 199 – 241 ). Cambridge University Press . https://doi.org/10.1017/CBO9780511529863 [Crossref] , [Google Scholar]
- Gick, M. L. , & Holyoak, K. J. ( 1980 ). Analogical problem solving . Cognitive Psychology , 12 (3), 306 – 355 . https://doi.org/10.1016/0010-0285(80)90013-4 [Crossref] , [Web of Science ®] , [Google Scholar]
- Gick, M. L. , & Holyoak, K. J. ( 1983 ). Schema induction and analogical transfer . Cognitive Psychology , 15 (1), 1 – 38 . https://doi.org/10.1016/0010-0285(83)90002-6 [Crossref] , [Web of Science ®] , [Google Scholar]
- Gigerenzer, G. , & Hug, K. ( 1992 ). Domain-specific reasoning: Social contracts, cheating, and perspective change . Cognition , 43 (2), 127 – 171 . https://doi.org/10.1016/0010-0277(92)90060-U [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Gilovich, T. , Griffin, D. , & Kahneman, D. ( 2002 ). Heuristics and biases: The psychology of intuitive judgment . Cambridge University Press . [Crossref] , [Google Scholar]
- Halpern, D. F. ( 2014 ). Critical thinking across the curriculum: A brief edition of thought & knowledge . Routledge . [Crossref] , [Google Scholar]
- Halpern, D. F. , & Butler, H. A. ( 2019 ). Teaching critical thinking as if our future depends on it, because it does . In J. Dunlosky , & K. Rawson (Eds.), The Cambridge handbook of cognition and education (pp. 51 – 66 ). Cambridge University Press . [Crossref] , [Google Scholar]
- Heijltjes, A. , Van Gog, T. , Leppink, J. , & Paas, F. ( 2014 ). Improving critical thinking: Effects of dispositions and instructions on economics students’ reasoning skills . Learning and Instruction , 29 , 31 – 42 . https://doi.org/10.1016/j.learninstruc.2013.07.003 [Crossref] , [Web of Science ®] , [Google Scholar]
- Heijltjes, A. , Van Gog, T. , Leppink, J. , & Paas, F. ( 2015 ). Unraveling the effects of critical thinking instructions, practice, and self-explanation on students’ reasoning performance . Instructional Science , 43 (4), 487 – 506 . https://doi.org/10.1002/acp.3025 [Crossref] , [Web of Science ®] , [Google Scholar]
- Heijltjes, A. , Van Gog, T. , & Paas, F. ( 2014 ). Improving students’ critical thinking: Empirical support for explicit instructions combined with practice . Applied Cognitive Psychology , 28 (4), 518 – 530 . https://doi.org/10.1002/acp.3025 [Crossref] , [Web of Science ®] , [Google Scholar]
- Holland, J. H. , Holyoak, K. J. , Nisbett, R. E. , & Thagard, P. R. ( 1989 ). Induction: Processes of inference, learning, and discovery . MIT press . [Crossref] , [Google Scholar]
- Hulleman, C. S. , & Cordray, D. S. ( 2009 ). Moving from the lab to the field: The role of fidelity and achieved relative intervention strength . Journal of Research on Educational Effectiveness , 2 (1), 88 – 110 . https://doi.org/10.1080/19345740802539325 [Taylor & Francis Online] , [Google Scholar]
- Janssen, E. M. , Mainhard, T. , Buisman, R. S. M. , Verkoeijen, P. P. J. L. , Heijltjes, A. E. G. , Van Peppen, L. M. , & Van Gog, T. ( 2019 ). Training higher education teachers’ critical thinking and attitudes towards teaching It . Contemporary Educational Psychology , 58, 310 – 322 . https://doi.org/10.1016/j.cedpsych.2019.03.007 [Crossref] , [Web of Science ®] , [Google Scholar]
- Kassin, S. M. , Dror, I. E. , & Kukucka, J. ( 2013 ). The forensic confirmation bias: Problems, perspectives, and proposed solutions . Journal of Applied Research in Memory and Cognition , 2 (1), 42 – 52 . https://doi.org/10.1016/j.jarmac.2013.01.001 [Crossref] , [Web of Science ®] , [Google Scholar]
- Kenyon, T. , & Beaulac, G. ( 2014 ). Critical thinking education and debiasing . Informal Logic , 34 (4), 341 . https://doi.org/10.22329/il.v34i4.4203 [Crossref] , [Web of Science ®] , [Google Scholar]
- Ku, K. Y. L. ( 2009 ). Assessing students’ critical thinking performance: Urging for measurements using multi-response format . Thinking Skills and Creativity , 4 (1), 70 – 76 . https://doi.org/10.1016/j.tsc.2009.02.001 [Crossref] , [Web of Science ®] , [Google Scholar]
- Kuhn, D. ( 2005 ). Education for thinking . Harvard University Press . [Google Scholar]
- Lai, E. R. ( 2011 ). Critical thinking: A literature review . Pearson’s Research Reports , 6 (1), 40 – 41 . [Google Scholar]
- LeBel, E. P. , & Paunonen, S. V. ( 2011 ). Sexy but often unreliable: The impact of unreliability on the replicability of experimental findings with implicit measures . Personality and Social Psycholy Bulletin , 37 (4), 570 – 583 . https://doi.org/10.1177/0146167211400619 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Leppa, C. J. ( 1997 ). Standardized measures of critical thinking: Experience with the California critical thinking tests . Nurse Educator , 22 (5), 29 – 33 . https://doi.org/10.1097/00006223-199709000-00012 [Crossref] , [PubMed] , [Google Scholar]
- Liu, O. L. , Frankel, L. , & Roohr, K. C. ( 2014 ). Assessing critical thinking in higher education: Current state and directions for next-generation assessment . ETS Research Report Series , 2014 (1), 1 – 23 . https://doi.org/10.1002/ets2.12009 [Crossref] , [Google Scholar]
- Loo, R. , & Thorpe, K. ( 1999 ). A psychometric investigation of scores on the Watson-glaser critical thinking appraisal new forms . Educational and Psychological Measurement , 59 (6), 995 – 1003 . https://doi.org/10.1177/00131649921970305 [Crossref] , [Web of Science ®] , [Google Scholar]
- Markovits, H. , & Nantel, G. ( 1989 ). The belief-bias effect in the production and evaluation of logical conclusions . Memory & Cognition , 17 (1), 11 – 17 . https://doi.org/10.3758/BF03199552 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Mayer, R. E. , & Wittrock, M. C. ( 1996 ). Problem-solving transfer . In D. C. Berlinert , & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 47 – 62 ). Macmillan . [Google Scholar]
- McDaniel, M. A. ( 2007 ). Transfer: Rediscovering a central concept . In H. L. Roediger , Y. Dudai , & S. M. Fitzpatrick (Eds.), Science of memory: Concepts (pp. 267 – 270 ). Oxford University Press . [Google Scholar]
- McNeil, N. M. , & Fyfe, E. R. ( 2012 ). “Concreteness fading” promotes transfer of mathematical knowledge . Learning and Instruction , 22 (6), 440 – 448 . https://doi.org/10.1016/j.learninstruc.2012.05.001 [Crossref] , [Web of Science ®] , [Google Scholar]
- Moxley, S. E. ( 1979 ). Schema: The variability of practice hypothesis . Journal of Motor Behavior , 11 (1), 65 – 70 . https://doi.org/10.1080/00222895.1979.10735173 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Newstead, S. E. , Pollard, P. , Evans, J. S. B. T. , & Allen, J. L. ( 1992 ). The source of belief bias effects in syllogistic reasoning . Cognition , 45 (3), 257 – 284 . https://doi.org/10.1016/0010-0277(92)90019-E [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Pellegrino, J. W. , & Hilton, M. L. ( 2012 ). Education for life and work: Transferable knowledge and skills for the 21st century . National Academies Press . [Google Scholar]
- Perkins, D. N. , & Salomon, G. ( 1992 ). Transfer of learning . In T. Husen , & T. N. Postelwhite (Eds.), The international encyclopedia of educational (Vol. 11, 2nd ed. , pp. 6452 – 6457 ). Pergamon Press . [Google Scholar]
- Reed, S. K. ( 1987 ). A structure-mapping model for word problems . Journal of Experimental Psychology: Learning, Memory, and Cognition , 13 (1), 124 . https://doi.org/10.1037/0278-7393.13.1.124 [Crossref] , [Web of Science ®] , [Google Scholar]
- Renkl, A. , & Eitel, A. ( 2019 ). Self-explaining: Learning about principles and their application . In J. Dunlosky , & K. Rawson (Eds.), The Cambridge handbook of cognition and education (pp. 528 – 549 ). Cambridge University Press . [Crossref] , [Google Scholar]
- Renkl, A. , Mandl, H. , & Gruber, H. ( 1996 ). Inert knowledge: Analyses and remedies . Educational Psychologist , 31 (2), 115 – 121 . https://doi.org/10.1207/s15326985ep3102_3 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Ritchhart, R. , & Perkins, D. N. ( 2005 ). Learning to think: The challenges of teaching thinking . In K. J. Holyoak , & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 775 – 802 ). Cambridge University Press . [Google Scholar]
- Rogers, W. T. , & Hopkins, K. D. ( 1988 ). Power estimates in the presence of a covariate and measurement error . Educational and Psychological Measurement , 48 (3), 647 – 656 . https://doi.org/10.1177/0013164488483008 [Crossref] , [Web of Science ®] , [Google Scholar]
- Salomon, G. , & Perkins, D. N. ( 1989 ). Rocky roads to transfer: Rethinking mechanism of a neglected phenomenon . Educational Psychologist , 24 (2), 113 – 142 . https://doi.org/10.1207/s15326985ep2402_1 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Stanovich, K. E. ( 2011 ). Rationality and the reflective mind . Oxford University Press . [Google Scholar]
- Stanovich, K. E. , West, R. F. , & Toplak, M. E. ( 2016 ). The rationality quotient: Toward a test of rational thinking . MIT Press . [Crossref] , [Google Scholar]
- Sternberg, R. J. ( 2001 ). Why schools should teach for wisdom: The balance theory of wisdom in educational settings . Educational Psychologist , 36 (4), 227 – 245 . https://doi.org/10.1207/S15326985EP3604_2 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Tiruneh, D. T. , Verburgh, A. , & Elen, J. ( 2014 ). Effectiveness of critical thinking instruction in higher education: A systematic review of intervention studies . Higher Education Studies , 4 (1), 1 – 17 . https://doi.org/10.5539/hes.v4n1p1 [Crossref] , [Google Scholar]
- Tiruneh, D. T. , Weldeslassie, A. G. , Kassa, A. , Tefera, Z. , De Cock, M. , & Elen, J. ( 2016 ). Systematic design of a learning environment for domain-specific and domain-general critical thinking skills . Educational Technology Research and Development , 64 (3), 481 – 505 . https://doi.org/10.1007/s11423-015-9417-2 [Crossref] , [Web of Science ®] , [Google Scholar]
- Tversky, A. , & Kahneman, D. ( 1974 ). Judgment under uncertainty: Heuristics and biases . Science , 185 (4157), 1124 – 1131 . https://doi.org/10.1126/science.185.4157.1124 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Van Eersel, G. G. , Verkoeijen, P. P. , Povilenaite, M. , & Rikers, R. ( 2016 ). The testing effect and far transfer: The role of exposure to key information . Frontiers in Psychology , 7 , 1977 . https://doi.org/10.3389/fpsyg.2016.01977 [Crossref] , [PubMed] , [Web of Science ®] , [Google Scholar]
- Van Gelder, T. V. ( 2005 ). Teaching critical thinking: Some lessons from cognitive science . College Teaching , 53 (1), 41 – 48 . https://doi.org/10.3200/CTCH.53.1.41-48 [Taylor & Francis Online] , [Google Scholar]
- Van Merriënboer, J. J. G. , Jelsma, O. , & Paas, F. G. W. C. ( 1992 ). Training for reflective expertise: A four component instructional design model for complex cognitive skills . Educational Technology Research and Development , 40 (2), 23 – 43 . https://doi.org/10.1007/bf0229704 [Crossref] , [Web of Science ®] , [Google Scholar]
- Van Peppen, L. M. , Verkoeijen, P. P. J. L , Heijltjes, A. , Janssen, E. , & van Gog, T. ( 2021b ). Repeated Retrieval Practice to Foster Students’ Critical Thinking Skills . Collabra: Psychology , 7 ( 1 ). https://doi.org/http://doi.org/10.1525/collabra.28881 [Crossref] , [PubMed] , [Google Scholar]
- Van Peppen, L. M. , Verkoeijen, P. P. J. L. , Heijltjes, A. E. G. , Janssen, E. M. , Koopmans, D. , & van Gog, T. ( 2018 ). Effects of self-explaining on learning and transfer of critical thinking skills . Frontiers in Education , 3 , 275 . https://doi.org/10.3389/feduc.2018.00100 [Crossref] , [Google Scholar]
- Van Peppen, L. M. , Verkoeijen, P. P. J. L. , Heijltjes, A. E. G. , Janssen, E. M. , & van Gog, T. ( 2021a ). Enhancing students’ critical thinking skills: Is comparing correct and erroneous examples beneficial? Instructional Science , 78 , 1102 . https://doi.org/10.1007/s11251-021-09559-0 [Google Scholar]
- Van Peppen, L. M. , Verkoeijen, P. P. J. L. , Kolenbrander, S. V. , Heijltjes, A. E. G. , Janssen, E. M. , & van Gog, T. ( 2021c ). Learning to avoid biased reasoning: Effects of interleaved practice and worked examples . Journal of Cognitive Psychology , 33 ( 3 ), 304 – 326 . https://doi.org/10.1080/20445911.2021.1890092 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
- Vosniadou, S. , & Ortony, A. ( 1989 ). Similarity and analogical reasoning . Cambridge University Press . [Crossref] , [Google Scholar]
- West, R. F. , Toplak, M. E. , & Stanovich, K. E. ( 2008 ). Heuristics and biases as measures of critical thinking: Associations with cognitive ability and thinking dispositions . Journal of Educational Psychology , 100 (4), 930 – 941 . https://doi.org/10.1037/a0012842 [Crossref] , [Web of Science ®] , [Google Scholar]
- Wittrock, M. C. ( 2010 ). Learning as a generative process . Educational Psychologist , 45 (1), 40 – 45 . https://doi.org/10.1080/00461520903433554 [Taylor & Francis Online] , [Web of Science ®] , [Google Scholar]
A Overview of the supporting prompts.
Below, we provided an overview per condition of the supporting prompts (translated from Dutch) that participants received at the start of the posttest transfer items and with each posttest transfer item.
No support condition
Recognition support condition.
To solve the following problems, you can use the rules of logic explained in the instructions.
Hint: To solve this task, you can use the rules of logic explained in the instructions.
Free recall condition
To solve the following problems, you can use the rules of logic explained in the instructions. Try to recall these rules and write them on the paper that you have received (Paper 2). ______________________________________________________________________________________________
Hint: To solve this task, you can use the rules of logic explained in the instructions that you tried to recall beforehand. Take that paper to solve the task.
Recall support condition
To solve the following problems, you can use the rules of logic explained in the instructions. You can find these rules in the overview on the paper that you just have received. ______________________________________________________________________________________________
Hint: To solve this task, you can use the rules of logic explained in the instructions. You can find these rules in the overview on the paper that you have received. Take that paper to solve the task.
B Example items critical thinking tests.
Below, we translated an example item of each task category administered in the critical thinking tests and the correct answer with an explanation.
Learning task (syllogistic reasoning)
Below, you will find two premises that you must assume are true. Indicate whether the conclusion follows logically from the given premises.
Premise 1. If a disease is caused by parasites, then it is an infectious disease.
Premise 2. Malaria is an infectious disease.
□ Conclusion follows logically from the premises.
□ Conclusion does not follow logically from the premises.
Explain briefly why you chose this answer:
Correct answer: conclusion does not follow logically from the two premises.
Explanation: This assignment requires to not confuse logical validity of the conclusion with the believability of the conclusion, which presumably seems believable to participants due to their prior beliefs or real-world knowledge. If the first part of premise 1 (if a disease is caused by parasites) is met, the second part (then it is an infectious disease) automatically follows. The second premise states that Malaria is an infectious disease. But this does not necessarily mean that it is caused by parasites. There might be another cause.
Near transfer task (syllogistic reasoning in a vignette)
An article by the Netherlands Forensic Institute (NFI) about the essence of forensic hair analyses states:
Correct answer: conclusion follows logically from the premises.
Explanation: This assignment requires to not confuse logical validity of the conclusion with the believability of the conclusion, which presumably seems unbelievable to participants due to their prior beliefs or real-world knowledge. According to the statement in the second sentence “if the aim of forensic hair analyses is to identify the donor of the hair sample” (P) is met, then “hair comparisons are performed” (Q) automatically follows. In the last sentence it can be read that hair comparisons are not performed in a recent investigation, so Q is denied. Therefore, P is not present. Because if P had been present, Q would have always followed.
Far transfer task (Wason selection)
Bacterial strains
Below, you can see four bacterial strains. Each bacterial strain has two characteristics: (1) it contains gene X or gene Y and (2) it is resistant to antibiotics or not. Of the four bacterial strains, you only see one of the two characteristics. You will have to test the bacterial strain to find out the second characteristic.
The rule is “if the bacterial strain contains gene X, then it is resistant to antibiotics (AB)”.
Which bacterial strains do you need to test to check if the rule is correct? Choose one or more from the options, but only choose the option(s) that is/are necessary to check whether the rule is correct:
Correct answer: bacterial strain gene X + bacterial strain not AB-resistant.
Explanation: This assignment requires to not only confirm the rule but also look for falsification of the rule. By testing the bacterial strain with Gene X, you can test whether the rule is violated: if it is not AB-resistant, the rule is violated. The same for testing the bacterial strain that is not AB-resistant: if it contains gene X, the rule is violated. Because if it contained gene X, then it should have been resistant to antibiotics. People who choose other options than the combination of bacterial strain gene X + bacterial strain not AB-resistant probably fail to apply logical principles, verify rules rather than to falsify them, or demonstrate matching bias by selecting options explicitly mentioned in the conditional statement.
C Coding scheme critical thinking tests.
Below, we provided the coding scheme used to score participants’ performance on the critical thinking tests, translated from Dutch.
Multiple-choice score
Participants can earn 0.5 point for the correct multiple-choice answer.
Explanation score
Participants can earn 1 point for the correct explanation, 0.5 point for a partially correct explanation, and 0 points for an incorrect explanation.
D Coding scheme free recall.
Below, we provided the coding scheme used to score participants’ free recall data (i.e. participants in the free recall condition only) translated from Dutch.
Participants can earn 1 point for a correct explanation per rule of logic and 0.5 point for a partially correct explanation per rule of logic. The maximum total score is 4 points.
– If mentioned (apart from explaining the rules of logic): “if P , then Q” or “if-then statements” → 0.5 point.
– If mentioned (apart from explaining the rules of logic): “you are not allowed to turn the rule” → 0.5 point.
– No points for one of these two comments if the maximum total score of 4 points is already achieved.
– If one describes the four correct conclusions (instead of validity for a given conclusion), then only mentioning “If P , then Q” is worth 1 point instead of 0.5 as in the coding scheme. Such as: “If P , then Q”; “If not P , then Q may be present”; “If Q, then P does not have to be present”; or “If not Q, then P is also not present”.
Reprints and Permissions
Permission is granted subject to the terms of the License under which the work was published. Permission will be required if your reuse is not covered by the terms of the License.
To request a reprint or commercial or derivative permissions for this article, please click on the relevant link below.
For more information please visit our Permissions help page .
- More Share Options
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations. Articles with the Crossref icon will open in a new tab.
- People also read
- Recommended articles
Your download is now in progress and you may close this window
- Choose new content alerts to be informed about new research of interest to you
- Easy remote access to your institution's subscriptions on any device, from any location
- Save your searches and schedule alerts to send you new results
- Export your search results into a .csv file to support your research
Login or register to access this feature
Register now or learn more
Psychology: Top Picks
- Article Indexes
- Magazines and Newspapers
- Associations
- Resources for students
- Resources for instructors
- Subject Specific Resources
- APA Workshop - PSYC 1100 & 1200 (January 2023)
- PSYC 1100 & 1200 - Wayne's classes (January 2023)
- AskAway - Chat Help Get help from a librarian
- Research Tutorial Explains the research process and how to evaluate resources
- All Databases A complete list of databases
- APA Guides to help with APA
Rate this Guide
This guide was useful to me.
- VCC Library Website
- Merck Manual of Diagnosis and Therapy This link opens in a new window A comprehensive guide to disorders and diseases with information on causes, symptoms, diagnosis, treatment and drugs
- Films on Demand: Psychology Streaming Videos
- How do I spot mis-information? (U of T)
- Fake News Site
- How to Spot Fake News - IFLA
- Next: Article Indexes >>
- Last Updated: Jan 23, 2023 4:19 PM
- URL: https://libguides.vcc.ca/psychology
IMAGES
VIDEO
COMMENTS
Awareness of these can make you a more effective thinker and, yes, doer. · 1. Confirmation Bias · 2. Cognitive Dissonance · 3. Commitment Bias · 4.
Egocentric Thinking · Groupthink · Drone Mentality · Social Conditioning · Biased Experiences · Schedule Pressures · Arrogance and Intolerance
Egoism, or viewing everything in relation to yourself, is a natural human tendency and a common barrier to critical thinking. It often leads to
All kinds of things can inhibit critical thinking. Personal factors such as intoxication or being under the influence of weird ideologies can do so.
1 Barriers to critical thinking · an over-reliance on feelings or emotions · self-centred or societal/cultural-centred thinking (conformism, dogma and peer-
Arrogance is a bad attitude and often hinders with critical thinking abilities. It makes a person with a closed mindset and with an opinion that
Guiding learners to be mindful about social pressures and their own personal biases that inhibit critical thinking should also facilitate critical thinking
Individuals that are overconfident could make dangerous situations. Therefore, confidence may inhibit critical thinking. ... A) An operational definition is a
In the educational psychology literature, transfer is usually subdivided into near and far transfer, differentiating in degree of similarity
What is Critical Thinking? · identifying other people's positions, arguments and conclusions; · evaluating the evidence for alternative points of