Self-perception, social expectations, and previous experiences shape our academic ability more than you can possibly fathom.
Just look into a school. Students who perceive themselves as smart tend to perform better academically. Success breeds more success. On the other hand, many students dislike school because a combination of factors lead them early on to believe that they will never become good students.
In order to improve student performance and self-esteem, we need to prove that students are the sole masters of their academic destiny. Adaptive learning, a teaching method premised on the idea that the curriculum should be personalized, is the sort of technology that is up to the challenge of untangling the cyclical effects of self-perception and social expectation.
When most people use the word adaptive or machine learning, they refer to “single point adaptivity,” which evaluates a student’s performance at one point in time in order to determine the level of instruction or material he receives from that point on.
The right way to go about it is to build a system that is continuously adaptive (in real-time) to each individual’s performance and activity on the system. Here are 5 ways in which adaptive learning can help all students control their outcomes.
Pace: The learning process should be geared toward exploration and long-term development rather than rote memorization, grades and crash studying. Success and failure should not be final. Adaptive learning can help reduce the anxiety associated with school work.
Focus: Adaptive learning helps students concentrate on maximizing their own individual potential rather than studying externally defined one-size-fits-all content. This encourages them to harness a deeper and more intrinsic motivation. A computerized adaptive learning system can help students develop an accurate perception of their own ability and the value of hard work. Adaptive should provide specific feedback.
Flexibility: Adaptive learning can deliver material in a way that appeals to different types of intelligence (linguistic, mathematical, etc.). Adaptive learning adjusts the delivery method based on each student’s abilities. It provides diagrams, interactive exercises etc. Students are not feeling excluded from subjects where they are not talented enough.
Social opportunities: Teachers can use data regarding performance and learning style, to create cohorts of students based on their profiles. Ideally the cohort will include students who complement each other academically. In a math class, for instance, a teacher might create mini workshops of 4 people each, with each workshop composed of an “organization” master, a “style” master, an “algebra” master and a “geometry” master.
Self-awareness: Self-awareness is what allows students to rebound from failure and grasp that their poor performance is a product of misunderstanding of a concept. Adaptive learning can inserting “reinforcement” moments into cognitive work moments that underscore the concept behind the solution. Students can’t guess. They will have to understand before they move on. Any online learning program can achieve these aims in a basic way, but an adaptive system can build up on this by tailoring the content to each student’s style.
