A couple of weeks ago, in the context of my experimental principles course, I wondered if I was enabling students to avoid the metacognitive activities that I believe lead to deep learning. I’ve given this a fair amount of thought and have reached a tentative conclusion that I’d like your feedback on. In other words, not only are comments welcome; they are encouraged.
The fundamental question I’m wrestling with is the extent to which I should force students to do the work in my course. As an economist, I believe that students respond in predictable ways to incentives. But as an academic, I want them to do the right thing for the right reasons–in this case, I want them to do the meta activities because they want to learn.
I could construct a course environment that encourages them to do the activities and penalizes them if they do not. This would involve making the meta activities “required,” with credit given or withheld as appropriate. The advantage of this option is that more students would complete the activities, albeit grudgingly.
Alternatively, I could tell them “I assume you’re taking this course to learn the most you can, not just for the grade or the credits. If you don’t do what my professional expertise says will maximize your learning, then (to quote my good friend Bob) it’s your funeral!” I would continue to give extra credit for completing the assignments, but there would be no explicit penalty for not doing them–except less learning. The advantage of this approach is that I would have more time to give personalized feedback to the smaller number of students who did the assignments.
I am leaning towards a more incentive-driven version of option 2. I would make the meta exercises “recommended” rather than required. I would give extra credit for those who do them. At the same time, I would stop curving the exam grades. This is the stick. I noted in my earlier post that the average raw exam score on these exams is less than a C, which I assume is lower than even the satisfycing students consider acceptable. This should cause students to work harder and hopefully do the metas. (I plan to explain all this to the students.)
To this basic model, I will add a carrot: I plan to determine the course grade as a weighted average of two midterm exams (25% each), the final exam (40% ), and class participation (10%). But if a student’s grade on the final exam exceeds the average of their midterm grades, I will replace the midterm grades with the final exam, which will count 90% towards the final grade. This will provide a realistic opportunity for students who need to bring up their grades, assuming they put in the work (hopefully including the meta activities), later in the course.
So, what do you think? What’s your reaction to this plan?