Few topics in higher education generate as much debate right now as the role artificial intelligence in all aspects of teaching and learning. Faculty listservs,
For many faculty, adding a new teaching strategy to our repertoire goes something like this. We hear about an approach or technique that sounds like a good idea. It addresses a specific instructional challenge or issue we’re having. It’s a unique fix, something new, a bit different, and best of all, it sounds workable. We can imagine ourselves doing it.
In last week’s post, we looked at a sample of the discipline-based evidence in support of quizzes with the goal of gaining a better understanding of what it means to say that an instructional practice is evidence-based. We are using quizzes as the example, but this type of exploration could and should be done with any number of instructional practices.
There’s a lot of talk these days about evidence-based instructional practices, so much that I’ve gotten worried we aren’t thinking enough about what that means.
Evidence-based teaching seems like the new buzzword in higher education. The phrase appears to mean that we’ve identified and should be using those instructional practices shown empirically to enhance learning. Sounds pretty straightforward, but there are lots of questions that haven’t yet been addressed, such as: How much evidence does there need to be to justify a particular strategy, action, or approach? Is one study enough? What about when the evidence is mixed—in some studies the results of a practice are positive and in others they aren’t? In research conducted in classrooms, instructional strategies aren’t used in isolation; they are done in combination with other things. Does that grouping influence how individual strategies function?