Day 16: Debunking 4 Tenacious Educational Programming Myths for Better Teaching Outcomes

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A series of  misconceptions about learning and teaching exist across cultures and countries that refuse to disappear. The issues with these myths are evident:

• Educators can believe their actions are scientifically grounded when they are not.

• This can result in high opportunity costs and economic investments in ineffective solutions.

• Not only risk the quality of teaching but also

• propagate incorrect ideas among students about learning strategies, potentially harming their lifelong learning efficiency.

So, here are the 4 more tenacious Myths about teaching and learning to code and the scientific evidence that refutes or challenge them:

Myth #1: Learning Styles

People do not learn better if lesson materials are tailored to visual, auditory, or kinesthetic learning styles. 

Studies show that we do NOT have different learning styles predefined by naturethat make us learn better if we receive information in one format or another. We all benefit from the same strategies if we are motivated to use them.

Source: Pashler, Harold, et al. “ Learning styles: Concepts and evidence." Psychological science in the public interest 9.3 (2008): 105-119 and Kirschner, Paul A., and Jeroen J.G. van Merriënboer. “ Do Learners Really Know Best? Urban Legends in Education." Educational Psychologist 48, no. 3 (2013): 169–83. 

Myth #2: To be a good programmer, you must be good at mathematics.

Research shows that aptitude for learning foreign languages is a stronger predictor of learning to program than basic maths knowledge.

“These results provide a novel framework for understanding programming aptitude, suggesting that the importance of numeracy may be overestimated in modern programming education environments.”

Source: Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages. Prat, et.al.  https://www.nature.com/articles/s41598-020

Myth #3: Learning Pyramid

The so-called “learning pyramid” (10% of what you read, 30% of what you see, numbers vary) is entirely made up.

What we do know is that acquiring information in more than one channel can contribute to better learning (known as dual-coding). What is also important is what we do with the information after we acquire it. 

One of the actions that most reinforce learning is recalling it: retrieving it from long-term memory and bringing it back to short-term memory to apply it in some way, such as explaining it to oneself (or someone else) or using it in solving a problem. But we also saw that other aspects influence learning, such as the previous knowledge we had about that topic and motivation, among others.

The type of actions shown in the pyramid are not the ones we would highlight in terms of their effectiveness in consolidating learning. 

Source:  Aplicando la Ciencia del Aprendizaje. Richard Mayer. 2020.

Myth #4: Some people were born to be programmers.

There is no evidence-based reason to believe in a Geek Gene, the idea that some people are just born to program and others are not.

Significant evidence shows that good teaching practices overcome genetic or innate ability differences.

The main problem is that teachers see evidence of a “geek gene” where none exists. These beliefs matter because teachers act on them: If a teacher believes that a learner is likely to do well, they naturally (often unconsciously) focus on that learner. The learner then fulfills the teacher’s expectations because of the increased attention, which in turn appears to confirm the teacher’s belief. 

Source:  Teaching Tech Together. Greg Wilson. 2019. 

There are more myths, and you can find some of them in the sources I share for the four I chose to share today. 

Science constantly advances: we test and refine our ideas and change our knowledge as more evidence comes in. The important thing is to base our actions in the classroom on scientific evidence.

Remember: the way you teach matters.