This is the fourth in a five-part “Brain Talk” series that explores how and why the inner components of the brain work together.
We shouldn’t be surprised that teaching all students the same way doesn’t yield the same results for each child. They start at different places and have different cognitive and affective resources to bring to each task. Ideally we want to personalize learning experiences to bolster and develop weak members of each student’s domain subcommittees, while fostering the general executive functions and emotional states that support all learning.
To some extent, this kind of adaptive instruction already happens in most classrooms. Teachers, for instance, notice when students’ heads are resting on folded arms, and they might respond with gentle touches on those students’ shoulders or by livening up the class activity. Teachers might give extra challenges to students who are not being stretched by the content and extra reminders to students who regularly neglect to turn in their homework. And failed tests can prompt extra lessons or remediation. Particularly diligent teachers are constantly monitoring their students and making adjustments, but it’s a daunting task—so many students and so many variables impacting their learning. Fortunately, technology is starting to help.
The initial phase of technology-fueled personalized learning has been helpful but elementary. By monitoring correct and incorrect responses to tasks, software can immediately identify which students are competent with certain concepts. It can then indicate which students need more work on which words or facts and which students have already mastered an idea. The software can automatically provide additional support or challenge to a student at the right time and inform the teacher about individual student needs.
Basing personalization solely on successful or unsuccessful task completion, though, can miss the underlying causes of failure. Did the student struggle with vocabulary words because of a phonological, orthographic, or semantic problem? Or was it a combination of issues exacerbated by an emotional collapse triggered by the complexity of a couple of the words? Do struggles in math represent a weakness in retrieval, a lack of connections among the subcommittees, or a fixed mindset reinforced by years of math failure?
As instructional technology systems grow more sophisticated, they can examine the subcommittee components of a task and provide differentiated support based on individual student need. They can also monitor the work of the executive function subcommittee and provide clues about the learner’s ability to focus their attention, respond to challenges and seek help. Biometric indicators like facial expressions, heart rate, posture and perspiration are already being used to monitor things like boredom, confusion and curiosity.
We’re making strides in developing software with these kinds of smarts, but we still have a ways to go. Certainly, though, creating instructional systems that recognize and account for the complex variation among students and their cognitive committee members will better meet the needs of our learners. The UDL (Universal Design for Learning) framework that I mentioned in previous posts provides a strong organizing principle for instruction and instructional materials. Throughout this process, it’s important for educators to remember to build for the mix of differences from the outset and not just those related to task performance.