On October 26, 2016, Dr. Jennifer Charlot and Transcend Board Member Bror Saxberg presented on learning science and its practical application to school design at the iNacol conference. The presentation was met with enthusiasm and was our first foray into sharing insights regarding a specific learning agenda question, in this case: “How can neuroscience, psychology & cognitive science inform how we cultivate successful learners, including those with learning differences?” In this blog post, Dr. Charlot reflects on the presentation and responds even further to the vibrant question and answer session that accompanied it.
Science has a lot to offer educators in terms of how young people learn and what they need to be successful. For example, cognitive scientists and others know a great deal about attention, stress, memory, exercise, sleep, and music—and all are well-studied topics that can readily translate to the school environment.
This October, Dr. Bror Saxberg and I joined forces at the International Association for K-12 Online Learning (iNacol) conference in San Antonio, Texas, to help educators think about how current and past research on the brain can be useful to schools in a presentation titled "Top 5 Reasons to Never Ignore Learning Science When Designing School Models."
In the presentation, we looked at how learning science—an interdisciplinary group of fields that seeks scientific underpinnings for learning—works, how learning outcomes can be measured, and how they can be improved. We observed that learning science can help educators:
Reduce time figuring out “how” to do something that others already have evidence about;
Reduce learning gaps because of suboptimal learning design;
Innovate for learning impact instead of “just because;”
Understand and fix motivation issues with students; and
Understand how to organize learning evidence to enhance systemic success.
By reviewing the research, we can learn more about how to structure learning and support students. The following just scratches the surface, but I want to highlight some interesting audience questions (and our responses) that came up during our presentation.
Q. Why should I care about the way memory functions?
If learning is the acquisition of knowledge, acquisition happens through a process of grappling with content. Much of that grappling happens in working memory, and results in key patterns and processes being installed in long-term memory. Once you fully absorb many patterns and processes that are part of a domain’s knowledge, they become easily retrievable from long-term memory for use by working memory in real world situations. If we think of school as a place that helps students transfer knowledge from working memory to long-term memory, and helps students apply what they have in long-term memory to new situations, we make different choices about the tasks in which we ask students to engage. For example, we focus less on information distribution (although some of that is needed to get going), but rather more on practice and feedback, applications of what we’re learning across contexts, and continuing opportunities to retrieve knowledge and apply it in different ways.
Q. How should I use rewards?
“It’s complicated.” Research suggests that extrinsic rewards aren’t the best tactics to get people to start doing something challenging (compared with intrinsic rewards). Once you cut off those external rewards, people stop doing the challenging thing, unfortunately. However, there is a use for extrinsic rewards: once someone has started on a challenging and important goal for intrinsic reasons, as the work starts to get harder and harder, extrinsic rewards can help the learner get over that difficult hump in the middle. It turns out that once they’re over that hump, cutting off the extrinsic reward does not affect their overall (intrinsic) motivation for mastering the challenging outcome.
Q. I am still struggling to get in the right form for my yoga pose automatically. What should I do?
This question was posed by a participant wondering about her own skill development, but we can apply the lesson more broadly to other skills. Like many academic skills, learning your yoga pose benefits from you breaking down the pose (or skills) into smaller pieces. You can then practice each small step and get feedback on how to do just that part right - then keep practicing until you are fluent at it, meaning you automatically execute the yoga pose (or skill) correctly without additional support. Once you master one step, you add the next step and repeat the practice and feedback process again. It also turns out that it matters that you practice the steps in combination - just because you can do each step on its own doesn’t mean your mind works like a tape-recorder, playing them all back together at once. You need to practice them together - and get feedback on how you are doing them together.
Q. Sometimes students give up when using technology independently. How can I incorporate motivation factors?
Motivation problems occur when 1) A student doesn’t value what they’re doing, or why they’re doing it, 2) A student doesn’t think they can master the outcome at all, 3) A student thinks other things are in the way, e.g., can’t read the textbook, the teacher hates them, no time, or 4) the student is in a negative emotional state, e.g., angry, frustrated, scared, depressed, etc.
These issues are best dealt with on a broader basis - i.e., not merely at the point a student is trying to do work on a computer independently, but throughout the work. Still, even with technology-only approaches, there are things to do:
- It’s important to distinguish whether a student is struggling because of a motivation issue, or because of a cognitive issue. If they are continuing to work hard, but are stuck, the problem is likely to be that what they are being asked to do needs something they haven’t mastered yet. That’s a very different problem than a motivation problem.
If your platform collects rich data about the student interaction, you can look for intensity of work by students (including lateness of assignments). If you see a student’s performance falling off while their effort is decreasing, you have a reason to reach out to the student and check in on motivation issues. Depending on what you find, you can help the student problem-solve around their issues.
The learning platform itself can directly gather information about student motivation states, though this shouldn’t happen too frequently, or it becomes annoying. Questions like, “Do you think you can master this?,” “Do you see the value of mastering this?” “What’s your emotional status today?” can be sprinkled through a course, especially around the hardest most important outcomes, to gather information. That can be used to do some automated interventions, but, likely the best is to tie in with a person to follow up.
Q. How do I make sure that all my students are motivated when I have so many in the classroom?
Working on motivation is a systematic issue - something the entire school environment and activities can support. You as a teacher can be preventative in your course design, such as weaving value exercises into your curriculum, but ultimately you have to change structures and mindsets about who is responsible for diagnosing motivation issues and creating the conditions to ignite and sustain motivated students. Think about peer coaches, daily prompts from an app, projects where students have choice, roles of other school personnel in helping students see the value and overcome inevitable motivation challenges, etc. Teachers can't be the only people looking out for kids on this front.
Like we said, these are just a few of many possible questions. If you want to get an overview of the principles of learning science, here are a few resources, which we will augment throughout the year.
- Breakthrough Leadership in the Digital Age: Using Learning Science to Reboot Schooling, by Frederick M. Hess and Bror V. H. Saxberg
- e-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning, by Ruth C. Clark and Richard E. Mayer
- Make It Stick: The Science of Successful Learning, 1st Edition, by Peter C. Brown, Henry L. Roediger III, and Mark A. McDaniel
- Why Don't Students Like School?: A Cognitive Scientist Answers Questions About How the Mind Works and What It Means for the Classroom, 1st Edition, by Daniel T. Willingham
- Why We Do What We Do: Understanding Self-Motivation by Edward L. Deci
- Science of Learning, by Deans for Impact
- KAPLAN Prod, by th uct Quality Checklist e K aplan Learning Innovation team
Stay tuned in the coming months for more updates on Transcend’s Learning Agenda.