Refuting myths is hard, and naive attempts are likely to backfire. The “Debunking Handbook” by John Cook and Stephan Lewandowsky (freely available here, PDF) gives us an effective overview of why this is the case. But we can take a page off it right away. By highlight the scientific statements rather than the myths themselves, we can improve the reader’s retention on what really matters.
Different audiences may need different amounts of information: Below we offer the simplest level of explanation. Please consult the references at the end or contact us if you want to know more.
The book written by Pedro De Bruyckere, Paul A. Kirschner and Casper Hulshof, “Urban Myths about Learning and Education” (2015) and its direct sequel, “More Urban Myths About Learning and Education” (2019), are excellent readings on the subject. The summary presented here is greatly indebted to these authors.
№ 1. People do not show specific learning styles and do not fit predefined personality types
To state that people have a preferred learning strategy is a trivial observation, not groundbreaking. However:
What you prefer is not necessarily what is good for you. No instructional benefit of a particular learning technique was ever observed for people declaring that it was their primary choice. Preferred instructional methods can even be unproductive.
Most so-called “learning styles” correspond to one or more theories of personality types. Despite the huge (and lucrative) success of this idea in the private sector, the claim that people cluster in distinct groups has inadequate support.
does not mean that some people won’t be slightly better at remembering
written words, for example. But certainly nobody has a problem learning
written words, pathologies aside.
Does that mean that all students
are equal and should be treated in the same way? Again, no: what
research states is simply that learning styles is not a theory of instruction and should be ignored for that purpose.
№ 2. New content can’t be effectively learned through Problem-Based Learning
In problem-based learning, it is common for students to be placed in small groups of about ten people.
Their aim is to solve a problem or complete a task under the guidance of a tutor. Peer discussion and self-study spread over time are at the core of this learning method showcased by some universities.
There are problems with this approach: The human working (or short-term) memory is limited in duration and capacity.
Information stored in working memory does not last for more than 30 seconds, if not rehearsed, and the maximum number of elements one can memorize at once is notably seven plus or minus two.
These physiological limitations are particularly stringent whenever students face never-seen-before material, which hasn’t reached the long-term memory yet.
For new content, direct problem solving is an extremely resource-intensive process which does not even help in generalizing methods to reach similar goals. On the contrary, if problem-solving is applied to pre-existing knowledge, existing schemas are exploited by the working memory, and count as one element.
Therefore, learning to solve problems and problem solving are different and unrelated skills.
Looking for alternatives? Goal-free problems, worked-out examples and completion problems are much more compatible with working memory’s needs, and carry overwhelming evidence that they are effective in building the ability to solve new problems in a domain.
№ 3. Our memory does not store a perfect record of our experience
what the teacher said or what was learnt in the past is an essential
ingredient of education. Memory is quite a complex mechanism.
According to most theories of cognition, memory is divided into:
Sensory memory: when external stimuli reach one of our senses. Information is already heavily filtered at this stage because we deliberately or unconsciously ignore incoming stimuli.
Short-term or working memory: is very limited in time and size (30 seconds for about seven elements). It helps organize and compare information.
Long-term memory helps give meaning to knowledge. It probably has an unlimited storage capacity and is a permanent record of what one truly learns.
Whether adults claiming to have “photographic memory” has ever been rigorously tested is a very controversial subject. In general, human memory is full of flaws:
Our minds are not empty jars waiting to be filled by knowledge provided by experts. – Memory reconstructs information according to what fits our schemas.
Perception is distorted by our biases. Our knowledge determines our experience, not the other way around.
Memory is personal, and changes over time. We are what we forget.
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4. Schools do not kill creativity
The relationship between intelligence (as measured by IQ) and creativity is not an easy one to investigate. Some researchers claim that genius and creativity are synonyms, that everybody is born a creative genius and that school ruins this potential.
Recent research however shows that children are not necessarily born creative. On the contrary, there is an interesting correlation between pretend play at a certain age, and later measured creativity.
Whenever a “drop” in creativity occurs, around 9 or 10 years of age for example, it is not because of the highly structured school system, but rather because of normal development paths, as children enter a “literal” or “conventional” stage in thinking and moral reasoning.
Schools could certainly do more to foster creative thinking, but the available research does not show that getting rid of the educational system would improve everyone’s creativity.
Creativity still requires a high degree of domain knowledge, and schools are still essential in providing these skills.
№ 5. New technology is not causing a revolution in education
The last thirty years have witnessed an incredible amount of new technological possibilities. Did the popularization of personal computers and Internet access have a similar effect in education as it had on society?
It doesn’t seem to be the case: Sixty years of comparative studies confirm that it is pedagogy, and not the medium, that impact the way learners learn. More precisely, what counts is the quality of the instruction and how well it is vehicled by a given medium.
For example, when presenting content through slides and commentary, introducing the key concept of a slide in its heading will lead to better learning than not doing so, but this effect is true for different media. Mobile learning, in turn, has a positive effect on the motivation to continue learning.
When a positive gain is shown by studies, it usually results from the good use of technology with good teaching. Indeed, blended learning, that is, elearning coupled with contact education, gives better results than traditional classes.
If technology is used as a tool for self-discovery, it once again benefits students with high levels of prior knowledge.
In summary: Computers and digital support can certainly be used in the most creative ways, but they should be used to supplement and reinforce what the teacher does, not as a replacement.
Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. https://doi.org/10.1037/h0043158
Sweller, J., Van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3), 251–296. https://doi.org/10.1023/A:1022193728205
Sawyer, R. (2013). Explaining creativity. New York: Oxford University Press.
Runco, M. A. (2003). Critical creative processes. Cresskill, NJ: Hampton Press.
Clark, R. C., & Mayer, R. E. (2011). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. San Francisco, CA: Pfeiffer.
Clark, R. E., & Feldon, D. F. (2014). Ten common but questionable principles of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 151-173). Cambridge: Cambridge University Press.
Sung, E., & Mayer, R. E. (2013). Online multimedia learning with mobile devices and desktop computers: An experimental test of Clark’s methods-not-media hypothesis. Computers in Human Behavior, 29(3), 639–647. https://doi.org/10.1016/j.chb.2012.10.022