Why Don’t Students Like School?
A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom
by Daniel T. Willingham,
Jossey-Bass, 2009.
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Cognitive science brings the question: does a student feel satisfaction and pleasure of solving a problem? When they do, they like school more, but when they don’t they don’t enjoy school.
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The human brain is naturally curious, but humans are not necessarily designed to be good thinkers—actually the brain is designed to avoid thinking. For the teacher, one thing this means is ensuring that there are *proper* problems to solve. Good problems pose moderate challenge, do not overload working memory, and do provide some basic concepts ahead of posing a “puzzling” question. Successful problem solving can deliver dopamine to the brain. The struggle to solve the problem has to be just the right level—must be possible and not too easy. The problem solver must have adequate environmental information, room in working memory and necessary information in long term memory to be successful.
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There is an important link between factual knowledge and thinking skills like analysis, critique, interpretation, etc. When we talk about wanting students to be able to do these kinds of skills, and not just know names and dates, says Willingham, we are missing an important point. These kinds of skills are highly correlated to factual knowledge. Students who have more background knowledge will be more successful at reading comprehension, making more room in working memory through increased options for memory, like “chunking,” problem solving, and remembering new material. Background knowledge is critical: Start early, read often, deep knowledge is better than shallow, shallow is better than none.
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Research from cognitive science shows that the ability to analyze and think critically requires extensive factual knowledge. The argument that students can now simply “Google” facts and we should concentrate on critical thinking, etc. is a fallacy. Cognitive science says background factual knowledge is bound up with the ability to practice critical thinking or other analytical thinking.
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Memory is connected to thinking. The “stickiness” of something in the memory is related to how much we thought about it. “Memory is the residue of thought.” In the classroom this means that we might accidentally derail the retention of information if the lesson/assignment/activity causes the student to focus their thinking not on the intended information but on peripheral parts that were perhaps meant to peak their interest. (E.g. If the math concept was couched in terms of an elaborate football game analogy, they might spend their time thinking about the football game rather than the math formula.) Memory can be supported by teaching through structures that are reinforcing to the ways our brains memorize—story structure, mnemonics, planning the question of the lesson as a conflict to be resolved.
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Moving from concrete to abstract is difficult for students, but is supported when students have more background knowledge. Students understand new things in the context of things they have already learned and understood. So again, the more background knowledge a student has, the more successful they will be with next level skills. Teaching this requires a move from shallow level facts (plot points, etc), to more deep structure questions. The assignment should make explicit the desire for students to learn these deep structures, rather than just shallow fact-based questions, and students should have many examples to compare.
Proficiency requires extended practice. This is how most of our brains master a skill. So, repeated practice in school of skills is necessary to produce proficient students. Practice also frees up working memory space as some skills become more automatic in the brain. Continued practice over time also increases the ability of the brain to remember those data or skills.
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Becoming expert is something that is fundamentally different than early student learning. Early training in a discipline is inherently different than late training and the cognitive ability of students is often prepared only to understand knowledge, not create it.
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Barring explicit learning disabilities, students are more alike than different in their learning, according to Willingham. Theories of learning styles are not exactly wrong, but they are often wrongly applied. That is to say, a student who has a strong auditory sense means that she can remember the sound of a voice or the particular details of noises in a lesson—not that she will learn math better by hearing it described around verses written on the board. This confusion leads to many incorrect practices or suggestions in the classroom. Differentiation is fine, but not based in cognitive science.
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Intelligence proceeds from both genetic factors and environmental stimuli. Students naturally have different levels of intelligence, but intelligence can also be changed though sustained hard work. Praising students for efforts rather than ability or outcome can improve attitudes toward hard work and combat the oft inferred conclusion that hard work means lower intelligence. Normalizing failure and repeated attempts, teaching study skills and confidence raising all promotes hard work and therefore increased intelligence.
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Finally, teachers themselves are subject to the same cognitive principles as students. They make room in their working memory by practicing their craft and improving technique. Observation, constructive critique, analysis and partner or team support all help this improvement happen.