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Why Students Don’t Like School, and What Adaptive Learning Can Do About It (Part 3)

Posted in Adaptive Learning on October 18, 2011 by

computer classMiss Part I or Part II of the series? Check it out here.

I recently read 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 Willingham’s investigation, 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. In my first two posts of the series, I discussed seven ways in which adaptive learning can improve the classroom experience.

Here are three more reasons students find school distasteful – along with explanations of how adaptive learning can help.

1. Discomfort moving from the concrete to the abstract (and back again).

If the aim of school is to make students independent from it (so they can apply what they learn in school to real-life situations), the processes of learning, problem-solving, and synthesizing matter just as much as the factual knowledge used to transfer ability in these areas. It generally works like this: having encountered a range of material, students start to recognize patterns, in both the subject matter and in their own learning. Of course, this abstract pattern recognition isn’t the whole point of learning; the ability to be concrete (to recall facts, execute plans, and work with different materials) is just as fundamental to the educational experience. What matters ultimately, then, is the ability to move seamlessly between pattern and detail, between the abstract and the concrete.

Students gain these skills, according to Willingham, by mastering detailed tasks (ex. revising a sentence in an essay), and then figuring out how these details fit into the whole (ex. understanding the way in which that revised sentence changes the essay’s overall argument). Willingham argues that teachers facilitate this cognitive “muscle-building” in several ways: they provide examples and ask students to compare them; they ask questions that prompt students to identify patterns and remark on structural qualities in the information.

Helping students gain these skills, however, isn’t always easy. As with most productive (and unfamiliar) work, there is often a general level of discomfort involved. The process can be slow and ineffective, especially when students in a class are at varied levels of understanding. Learners at either end of the spectrum are likely to be either bored or confused, and as a result are more likely to “check out” of the lesson and begin to harbor resentment for school in general.

How can adaptive technology help? By tailoring questions and examples to each individual’s level of understanding and learning style, an adaptive system can improve engagement and facilitate success. Specifically, an adaptive system is able to: a) insert reinforcement moments that prompt students to think about meaning, structure, and process b) draw abstract moments back to the concrete by requiring students to apply principles, theories, and formulas to the contexts of new problems, and c) track through data the efficacy of these shifts to optimize the flow of cognitive work for each learner’s individual style. Ultimately, students walk away not only having learned more and in a deeper way – but also having become more confident and engaged in their learning.

2. Lack of connection between past and present learning.

The controversial writer, John Gatto, famously posited that public school as we know it, with its rigidly segmented class day and byzantine rules, teaches students that no subject really matters beyond the forty minutes during which it is taught and that the lack of continuity between subjects and grade levels teaches students to accept “confusion” as their destiny. Regardless of whether you agree with Gatto’s assessment of public schools, student engagement can be strengthened if academic work is imbued with a sense of continuity and meaning. After all, as Willingham suggests, the hardest part of many cognitive tasks is getting geared up to start over or start up again. Nothing is more dissatisfying to students than feeling like the hoops and hurdles they face are essentially arbitrary and culminate in nothing.

Adaptive learning can assist in knowledge recovery and transfer, reducing the extent to which students feel overwhelmed by the introduction of a new type of problem, skill, or knowledge area. A finely tuned adaptive system can accomplish this by quickly reminding students what they learned previously (in the form that sticks with them the best), highlighting certain patterns in the material (or nudging students to grasp them) or bringing certain structures into relief (so that students are guided to what they should be focusing on), or maybe even re-introducing a student’s past notes and commentary at a later point. (Imagine that you were given eternal access to all the notes you ever composed and all the material you ever underlined–how would this change your learning?) The message this sends students is that their learning extends in unfathomable ways beyond the assessment at hand–that what they’re learning today will form the foundation of what they learn tomorrow.

3. Lack of connection between different subjects and areas of learning.

As mentioned earlier, a lack of continuity between different learning episodes creates a sense of meaninglessness and implicitly teaches students that “nothing really matters.” What if, however, you could use student curiosity in one area to fuel interest in every other? What if the positive effects of every learning experience were capitalized upon exponentially?

In his book Disrupting Class, Clayton Christensen identifies the self-perpetuating cycle through which the curriculum and methods of instruction for various subjects are tailored for those who are gifted in them. Math classes, for instance, are taught by those who are gifted at math and through texts written by those who are gifted in the subject as well; and class itself is shaped by the questions and comments of gifted math students. (This leaves those who are not gifted at math feeling excluded and turns them off from the subject.) Imagine an alternative: what if you could use the confidence students develop in the areas in which they excel to help them learn in subjects for which they have less proclivity?

For the purposes of this discussion, I’ll introduce the “7 types of intelligence” that Willingham and other writers and researchers have identified:

  •  Linguistic: ability to use language and express thoughts
  • Logical/mathematical: ability to work with numbers and logic
  • Spatial: ability to think three-dimensionally
  • Bodily-kinesthetic: ability to use one’s hands and body in complex and fine-tuned ways
  • Musical: ability to work with pitch, melody, rhythm, and tone
  • Interpersonal: ability to interact with others;
  • Intrapersonal: ability to understand one’s self
  • Naturalist: ability to observe environment and work with patterns in nature

How might an adaptive learning system allow individuals of the above intelligence types to harness their strengths to approach the study of, say, math differently?

An adaptive system could process each individual’s performance, activity, and preferences to deliver the same material in different ways. Someone who is, say, a “naturalist” might develop his math ability by using math to conduct experiments and test hypotheses about the natural world. Someone who excels in the “interpersonal” might learn by teaching others what he knows. And someone who is “musical” might use math to grasp the science behind harmony.

This differentiation is a fairly blunt-edged example of how an adaptive system might use a student’s strengths to remediate weaknesses (an idea that Willingham introduces and which adaptive learning can make a reality). It could happen in a more subtle fashion as well. If a student excels in rapid-learning problems but fails at projects that require long-term planning and study, an adaptive system might encourage him to segment the longer project into less-intimidating chunks. And vice versa: a student who has difficultly absorbing and processing material quickly might have more luck conceiving of the activity as part of a long-term project. The possibilities are endless.