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Five myths on education

Myths in education

This article provides the first half of ten pseudoscientific statements from the domain of cognitive sciences applied to learning and education. We will focus on the lesser known and more nuanced urban myths, which are sometimes also the most challenging for teachers and experts in educational technology.

Next month’s article will continue and conclude this review.

Refuting myths is hard, and naive attempts are likely to backfire. The “Debunking Handbook” (freely available here) gives an effective overview of why this is the case. We therefore highlight the scientific statements rather than the myths themselves, in an effort to improve the reader’s retention.

Also, different audiences may need different amounts of information: due to space restrictions, we offer the simplest level of explanation, and provide the reader with some references if he or she wants to find out more on that particular subject.

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 don’t show specific learning styles and don’t 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 choice1. Preferred instructional methods can even be unproductive2.
  • 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 support3.

This 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, students are asked to work in small groups of about ten people.

In short, 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 seconds4, if not rehearsed, and the maximum number of elements one can memorise at once is notably seven plus or minus two5.
  • 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 generalising 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 domain6.

3. Our memory does not store a perfect record of our experience

Remembering 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 cognition7, 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 organise 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” have ever been rigorously tested8 is a very controversial subject9. 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.

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 potential10.

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 creativity11.

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 reasoning12.

School 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 popularisation 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 learn13. More precisely, what counts is the quality of the instruction and how well it is vehicled by a given medium14.

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 learning15.

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, e-learning coupled with contact education, gives better results than traditional classes16.

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.

Find out more:

  1. Clark, R. E. (1982). Antagonism Between Achievement and Enjoyment in ATI Studies. Educational Psychologist, 17(2), 92–101. https://doi.org/10.1080/00461528209529247
  2. Clark, R. E., & et al. (1987). When Teaching Kills Learning: Types of Mathemathantic Effects. (March), 0–24. Retrieved from https://www.researchgate.net/publication/234744652
  3. Kirschner, P. A., & van Merriënboer, J. J. G. (2013). Do Learners Really Know Best? Urban Legends in Education. Educational Psychologist, 48(3), 169–183. https://doi.org/10.1080/00461520.2013.804395
  4. Baddeley, A. (1992). Working memory. Science, 255(5044), 556–559. https://doi.org/10.1126/science.1736359
  5. 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
  6. 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
  7. Atkinson, R. C., & Shiffrin, R. M. (1968). Human Memory: A Proposed System and its Control Processes. https://doi.org/10.1016/S0079-7421(08)60422-3
  8. https://www.vice.com/en_us/article/ypwj9v/are-photographic-memories-a-hollywood-myth
  9. https://slate.com/technology/2006/04/no-one-has-a-photographic-memory.html
  10. https://www.ted.com/talks/ken_robinson_changing_education_paradigms
  11. Sawyer, R. (2013). Explaining creativity. New York: Oxford University Press.
  12. Runco, M. A. (2003). Critical creative processes. Cresskill, NJ: Hampton Press.
  13. 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.
  14. 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.
  15. 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
  16. Wouters, P., & van Oostendorp, H. (2013). A meta-analytic review of the role of instructional support in game-based learning. Computers & Education, 60(1), 412–425. https://doi.org/10.1016/j.compedu.2012.07.018
Florian Zenoni

Florian Zenoni

Florian is a Data Scientist at Wooclap, an online platform with which to stimulate classes and measure student understanding of material thanks to smartphones.