There are quite a few things that are still believed by many learning professionals as facts, while they are not. In this post, I explore seven of these myths.
We should design instructions to match learners’ learning styles.
The verdict: This myth is not true.
Many research studies have set out to test the hypothesis that when instruction materials are designed to match learners’ learning or cognitive styles, learners can learn better. However the results are mixed and at the moment, the conclusion is that design for learning styles does not necessarily help learners learn better.
There are many ways cognitive styles are categorised. To demonstrate this myth, let’s look at a categorisation that is very well known in instructional design – it is the grouping of learners into visual, auditory or kinaesthetic learners. Research has shown that there is no difference in learning effectiveness when we design to suit each of these learner types. In the book Why don’t students like school, Daniel Willingham explains this is because learning of many things is measured according to “meaning of the words” and not by learners’ memory of visuals or sounds (p. 156). He states learning of many things is concerned with “what things mean, not with what they look like or sound like” (p. 156).
- Use the different categories of cognitive styles to guide us in designing instruction to match the type of knowledge and skills and the learning outcomes. For example, if we want learners learn what the shape of a country is like, use a visual would be more appropriate than using a text description. If we want learners to learn what a bad car break or what a fire alarm to evacuate sounds like, using audio would be more appropriate than using a visual. If we want learners to learn about what the textures of different fabric types feel like, bring in the different fabrics for learners to touch and feel would be more effective than just show them a picture of the fabrics.
- Provide a variety of learning modalities to increase learners’ interest and learning effectiveness. According to Josh Medina in his book Brain Rules, stimulating more of the senses will enhance learning. Those in “multisensory environments always do better than those in unisensory environments” (p. 208). Even 20 years later, these people have more accurate and higher quality recall. However, note that this practice should be done with caution, so not to increase unnecessary cognitive load and distract rather than help learners.
Learning facts is not important in today society and thus instructional designers shouldn’t focus on design for effective learning of facts.
The verdict: This myth is not true.
These days, instructional designers put a stronger focus on designing for skills and problem solving and learning facts is often considered nonessential. One can often look up a lot of information on the internet or other external resources and therefore might understandably argue facts can always be accessed when need be, thus there is no need to learn them. However, according to Willingham (2009), research shows that “thinking well requires knowing facts” and critical thinking processes “are intimately intertwined with factual knowledge that is stored in long-term memory (not just found in the environment)” (p. 28). Knowing background knowledge is especially more important for beginners or less experienced learners.
- Evaluate what facts and background knowledge learners need to know in order to learn skills more effectively
- Make sure learners know the relevant background knowledge for practicing required skills
Using narration will make eLearning more effective.
The verdict: It depends on how the narration is used.
There are many eLearning examples out there with narration, and among them, you can hear the narration matches exactly or almost exactly with the on-screen text. One argument is that learners can then choose what suits them or use both at the same time. However, the Redundancy principle from Mayer (2009)’s multimedia principles states that presenting the identical on-screen text at the same time with the verbal information is redundant and can cause unnecessary cognitive load. In most situations, it is more effective to use narration with animation instead of with text.
- Where possible, use narration rather than on screen text (the Modality principle)
- Use narration with animation instead of with identical on screen text (the Redundancy principle)
The more interactive a course is, the more effective it is.
The verdict: It depends.
It depends on whether the interactivities align with the course’s purpose, and are not just there for the sake of being interactive. This type of eLearning is like a bad product with beautiful packaging. Bean (2011) referred to it as “Clicky Clicky Bling Bling”. Just because learners have a lot of buttons to click, a lot of things to “do” or feel entertained by different game elements doesn’t mean the course is effective. The interactivities need to be relevant for them to add value to the learning experience. The Coherence principle from Mayer (2009) states that we should exclude extraneous words, pictures and sounds. Irrelevant elements will just increase cognitive load unnecessarily, leading to learner fatigue and thus reducing learning effectiveness.
- Align all learning activities with learning outcomes, remember form follows function
- Evaluate whether the chosen activities are relevant to the learning outcomes
- Resist the temptation of adding interactivities just for the sake of interactivities
Practice makes perfect.
The verdict: It depends on what kind of practice is given, how much and how practice is given and the subject domain.
According to a meta-analysis study by Macnamara, Hambrick, and Oswald (2014) on the influence of practice on performance across educational, occupational, sports, music and game domains, practice does explain the variance in performance in these domains, but surprisingly the size of this effect is not as large as one would have expected, only 12 percent in average across domains. Practice is more critical for games, music and sports, while less so for education and professional domains. There are other factors that contribute to the difference in performance. There are also situations where over practice doesn’t increase learning effectiveness, such as what demonstrated in a research study done on the learning of a mathematical procedure (Rohrer & Taylor, 2006).
- Consider the nature of the content and tasks
- Think about how much learners should practice
- Design the right kind of practice, e.g. deliberate practice – a type of focused practice with feedback
- Take into account other factors that can also explain some of the variance in performance such as intelligence, how early one starts learning a new skills, working memory, and talent.
- Use distributed practice as recommended by Mayer and Clark (2007)
People only remember 10 of what they read, 20% of what they see, 30% of what they hear, 50% of what they see and hear, 70% of what they say or write, and 90% of what they do.
The verdict: This myth is not true.
This myth is not based on any scientific evidence. Thalheimer (2002) explained in details the long history of how this myth came about and how nowadays it has been quoted as truth in many instances. Through time, the percentages can even be seen in Dale Edgar’s Cone of Learning (Anderson, 2003), which originally did not associate with any numbers. This myth does sound plausible however it is not credible, and thus shouldn’t influence how we design instructions, e.g. minimise instructions that involve reading or design only instructions where learners need to do something.
- Don’t follow these percentages in determining strategies to help learners to remember
- Verify claims especially ones that have specific numbers attached to them
- Use evidence-based strategies to help learners remember – there are indeed many of them, which I may write about in another article
We should let learners to be completely self-directed as learners know best.
The verdict: This myth is not true.
Kirschner and van Merriënboer (2013) have debunked this myth. The myth is that today learners are highly skilled with technology, great at multi-tasking, and therefore can navigate their own learning using technology. However, research has shown these are not true. The authors of the article present evidence against three ideas associated with this theme.
- Learners as digital natives who are great at multitasking: The term digital native refers to “a group of young people who have been immersed in technology all their lives” (p. 170). It has been thought that these people developed on their own the metacognitive skills required for different types of learning including discovery-based learning and experiential learning. However contrary to the belief that the digital natives have high digital skills, researchers found that these people actually only have basic and limited technology skills, e.g. web surfing, text messaging. Notably, when they used technology for learning, it was mainly for “passive consumption of information” (p.171). In addition, instead of multitasking, they actually only “quickly switch between different tasks or different media” (p. 172) and research has shown that this rapid task switching has negative effects on learning and performance.
- Learners are aware of their own learning styles: Research has shown a learner’s preferred way of learning is “often a bad predictor of the way people learn most effectively; what people prefer is not what is best for them” (p. 174).
- Learners as self-educators (on the Internet): Many researchers “have demonstrated that young children, teenagers, and adults are not capable of effectively choosing proper search terms, selecting the most relevant websites, and questioning the validity of sources” and “learners are not always successful controlling their own learning, especially in computer-based learning environments” (p. 177). The more prior knowledge a learner has, the more effective their information quest would be.
In addition, according to Hagemans, van der Meij, & de Jong (2013), learners often use ineffective learning strategies. Nowadays, there is a big push for self-directed learning. However, as shown, leaners actually don’t know bests. So we need effective instructional design to help learners in their learning processes.
- Don’t assume learners know what they need or know the strategies to get what they need
- Do use strategies to facilitate the self-directed learning processes to support learners discover effectively what they need, e.g. present a limited and suitable set of options for learners to choose from
- Assess cognitive abilities objectively rather than using self-reports
- Design instructions based on cognitive abilities rather than on learning styles
Anderson, H.M. (2003) Perspectives for pharmacy educators successful teaching excellence: Dale’s cone of experience. Available at: http://tinyurl.com/gpyc2tz (Accessed: 22 December 2016).
Bean, C. (2011) ‘Avoiding the trap of Clicky-Clicky Bling-Bling’, eLearn, 2011(6), p. 2.
Clark, R.C.C. and Mayer, R.E. (2007) E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. 2nd edn. San Francisco, CA: Jossey-Bass Inc.,U.S.
Hagemans, M. G., van der Meij, H., & de Jong, T. (2013). The effects of a concept map-based support tool on simulation-based inquiry learning. Journal of Educational Psychology, 105(1), 1-24.
Kirschner, P.A. and van Merriënboer, J.J.G. (2013) ‘Do learners really know best? Urban legends in education’, Educational Psychologist, 48(3), pp. 169–183
Macnamara, B.N., Hambrick, D.Z. and Oswald, F.L. (2014) ‘Deliberate practice and performance in music, games, sports, education, and professions: A Meta-Analysis’, Psychological Science, 25(8), pp. 1608–1618.
Mayer, R.E. (2009) Multimedia learning. 2nd edn. Cambridge: Cambridge University Press.
Medina, J. (2010) Brain Rules: 12 principles for surviving and thriving at work, home, and school. Seattle, WA: Pear Press.
Rohrer, D. & Taylor, K. (2006). The effects of over-learning and distributed practice on the retention of mathematics knowledge. Applied Cognitive Psychology, 20, 1209-1224.
Thalheimer, W. (2002) People remember 10%, 20%…Oh really? Available at: http://www.willatworklearning.com/2006/05/people_remember.html (Accessed: 22 December 2016)
Willingham, D.T. (2009) Why don’t students like school? A cognitive scientist answers questions about how the mind works and what it means for your classroom. San Francisco, CA: John Wiley & Sons.
Great summary and explanation supported by credible research.