Why students don’t like school (and what adaptive learning can do about it).
GUEST COLUMN | by Christina Yu
Ask students why they don’t like school, and you’ll get several answers: it’s “hard,” “boring,” “disconnected from reality” or “only for smart people.” The real answer is of course more complex than any of these responses would suggest. Daniel T. Willingham investigated the matter in the book, “Why Don’t Students Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What It Means for the Classroom.” Many of the reasons Willingham argues that students don’t like school can actually be eliminated or reduced with adaptive learning technology. Here are three reasons kids don’t like school and how personalizing education can help:
1. Students are working at the wrong level.
Willingham begins his book by debunking some conventional notions about what the human mind is designed to do: “Contrary to popular belief, the brain is not designed for thinking. It’s designed to save you from having to think, because the brain is actually not very good at thinking. Thinking is slow and unreliable.” Willingham says, however, that “people enjoy mental work if it is successful.” Hence the popularity of crossword puzzles, sudoku games, and brain teasers. What makes mental work enjoyable? The snap of discovery, the sudden moment of insight. Mental work becomes fun and even entertaining if it consistently yields such “aha” moments.
When students complain that school is boring, it may indicate that it’s either too hard or too easy. The challenge is to get the balance just right: too easy and there’s no satisfaction; too hard, and students will invest effort only to feel frustrated and lose focus. Thus, the key to maintaining student engagement is to escalate the difficulty of the work incrementally, so that students receive a constant stream of questions targeted at the precise level at which thinking and real engagement are likely to occur. By determining a student’s ability and asking questions at just the right level, educators can engage students and encourage more “aha” moments.
This is one challenge that adaptive learning systems are tackling. Think of it this way: an adaptive learning system is like a personalized mental workout, adjusting to each student’s individual needs. It can figure out what each student knows and why. By sending students on a unique learning path customized for them, it challenges students at any level, preparing them to scale intellectual cliffs and undertake marathons of critical thought.
2. Students lack background knowledge or have uneven skill sets.
Willingham asserts, “research from cognitive science has shown that the sorts of skills that teachers want for students–such as the ability to analyze and to think critically–require extensive factual knowledge.” In other words, knowledge must precede skill.
If you have no experience in economics, for instance, you can still read The Economist and get something out of it; but a trained economist will be able to read the magazine faster, extract the important details, ask intelligent questions, and put the knowledge to work more quickly. Not because he’s a more gifted critical thinker but because he’s developed an intuition for the material due to deep functional exposure.
Similarly, students who are tasked with analyzing information without a proper understanding of fundamentals first, run into difficulties. For example, if they haven’t yet learned certain vocabulary they may be unable to understand and solve certain problems. Students who have weak background knowledge will not only be on unequal ground but will also be frustrated or even bored.
How can adaptive learning help? By figuring out what students know at a granular level, adaptive learning technology can determine what key information a student may have missed along the way, even across disciplines. For example, it can determine that a student struggling with word problems in math may actually need to work on reading comprehension.
Whether it’s pre-requisite skills, background knowledge, or practice in organizing information (or noting its structural qualities), adaptive learning technology can help students and teachers find out what each student needs to work on to move forward. This way, students can tackle challenging or complex cognitive work more successfully, reaching epiphanies and key learning moments more often.
More learning epiphanies means more enjoyable learning. Greater enjoyment often leads to increased investment of energy on the students’ part and greater risk-taking (the student who enjoys school invests more in it, gets better at school, enjoys it even more, persists through challenges, and so forth). Thus, a small difference can have an exponential effect. A single “aha” moment can yield many more.
3. Feedback is too slow.
Assessment and feedback is sometimes limited by the arduous task of grading and evaluating student exams, papers, homework assignments, worksheets, and other exercises. By using adaptive technology to evaluate student work and proficiency in real-time, assessment becomes continuous and feedback, immediate. If feedback is immediate, teachers can help students get back on track more quickly.
Rather than struggling all semester and discovering misunderstandings on an important quiz or final, adaptive learning helps students and teachers find and close gaps in knowledge along the way. Plus, with less administrative work, teachers have more time to do what they do best–teach and engage students.
The result is pacing conducive to risk-taking, experimentation, iterative development, and rapid learning. Exams lose their terrifying “be-all, end-all” character, and students can relax and be more in the present when they learn. Students are free to focus more on the material at hand rather than protecting their egos or other factors at stake with each test (pride, social status, family pressure, college admissions, etc.). In this way, the pace of adaptive technology and continuous feedback can change the student mindset about school.
Christina Yu is on the marketing team at Knewton. She holds an A.B in English from Dartmouth and an M.F.A in creative writing from Notre Dame. In recent years, her fiction has appeared in various literary journals nationwide and has been nominated and cited for several Best American anthologies. Previously, she worked as a lecturer in English & Literature at Kean University and Southern Connecticut State. She is currently an M.B.A candidate at the NYU Stern School of Business. Knewton is a leading adaptive learning platform with a mission of bringing personalized learning to the world. Write to: [email protected]
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