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Why Students Don’t Like School — and What Adaptive Learning Can Do About It (Part 1)

Posted in Adaptive Learning on September 20, 2011 by

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. To get a deeper understanding of the matter, I recently read one man’s investigation: Daniel T. Willingham’s Why Don’t Students Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What It Means for the Classroom.

As I was reading, I noticed that most of the real reasons Willingham argues that students don’t like school can be eliminated or reduced through continuous adaptive learning technology. Here’s how:

1. Work pitched at the wrong level.

Willingham begins his book by debunking some conventional notions about what exactly 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 indicates, 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 moments.

When students complain that school is boring, what they’re probably saying is 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. Continuous adaptive learning can provide this by determining a student’s ability and “serving up” questions at just the right level.

Of course real life doesn’t happen this way–you don’t get a series of challenges perfectly calibrated to your level, so that every exertion leads to maximum satisfaction; the hope is, however, that adaptive technology can be harnessed so that students engage productively with schoolwork and are therefore better equipped to tackle “imperfect” challenges in the real world. Think of it this way: an adaptive learning system is like a superior mental work-out machine that leaves you ready to scale intellectual cliffs and undertake marathons of critical thought.

2. Not enough opportunities for engagement.

The above paragraphs are premised on the fact that students have enough problems to solve in the first place. If students are only given lectures with minimal opportunity to exercise their cognitive muscles, they will obviously be less engaged.

These “cognitive-work” opportunities are inherent to adaptive learning systems. After all, a continuous adaptive system is based on the idea that what you see going forward depends on your previous activity and performance. In other words, it’s practically impossible to design a continuous adaptive learning system that doesn’t give students a chance to “show what they know” in a fairly constant way. Thus, keeping students mentally active throughout a classroom session is a fundamental challenge that adaptive learning solves.

3. Slow feedback.

The above point — that students need to be active to be engaged — seems an obvious one, but consider from a teacher’s perspective how difficult it is to build problem-solving into every single lesson. The trouble with student problem-solving is that it generally requires feedback of some sort (grading, evaluation, commentary) and good feedback takes time to generate. In this way, the administrative aspect of many productive class activities can make the work for teachers spiral out of control.

As far as evaluation is concerned, adaptive learning can efficiently provide high-quality student feedback, reducing administrative burden on teachers and enhancing student engagement. Whether it’s multiple choice, free response, or even an essay that’s submitted, a continuous adaptive learning system can process student work and deliver personalized assessment. (For more on how adaptive learning works with material as subjective as English composition, check out my post on adaptive learning for soft subjects.) Most importantly, the feedback provided by an adaptive learning engine (designed for continuous as opposed to single-point adaptivity) can be instantaneous or near-instantaneous. This enhances student engagement because students are less likely to lose focus if feedback is immediate and they can quickly self-correct. The result is pacing conducive to risk-taking, experimentation, iterative development, and rapid learning.

4. Lack of background knowledge.

Anyone who’s ever had trouble with the reading comp section on any standardized test (think GMAT or GRE) understands the soporific effect of subjects like the “electromagnetic spectrum” or “sessile organisms.” However, smart test-takers know that the subject itself is supposed to be irrelevant; critical reasoning ability is what’s being tested. For the most part, this isn’t a problem on standardized tests; the obscurity of the content is a neutralizing factor that makes the exam more fair. With schoolwork, however, the subject matter used to impart analytical and creative skills can put students on unequal ground and disadvantage students who have weak background knowledge or have simply not been exposed to certain vocabulary or jargon: “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 this way, Willingham asserts, “factual knowledge must precede skill.”

Think of it this way. If you have no experience in economics, you can still read The Economist and get something out of it; but a trained economist will be able to read the magazine much 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 simply because he’s developed an intuition for the material due to deep functional exposure.

What does this have to do with adaptive learning?

A) A continuous adaptive learning system can provide a scaffolding of hints (definitions, encyclopedic knowledge, formulas) to help level the playing field for those students who have had less exposure to culture, world events, and certain types of vocabulary and jargon. This will allow students to absorb the background knowledge seamlessly and focus on the analytical and creative aspects of any exercise designed to improve their skills in those areas.

B) Adaptive learning can help students learn more efficiently and effectively and in the process, expose students to a range of material in a shorter amount of time (this is related to my point below). Depth and range of exposure can improve a student’s “chunking” ability. Even the simple act of locating a subject in relation to other subjects (an option afforded only by scope of exposure) can make something “click” for many students.

C) Willingham defines “chunking” as “the phenomenon of tying together separate pieces of information from the environment.” Students are thus able to absorb complex knowledge by breaking it down into smaller, manageable chunks. The same goes for problem solving: students tackle complex problems by perceiving them as a series of manageable steps. Adaptive learning can determine what a student needs to grasp before he can have this kind of insight–whether it’s background knowledge, a highlighting of structural qualities in the information, or a certain breadth of range, or a combination of all these elements. In this way, students can be guided toward making those “chunking insights” themselves.

To achieve benefit #3, it is especially important to develop “continuous” as opposed to “single-point” adaptivity.

Stay tuned for more ways that adaptive learning is changing the way students think about school!