Journey into OER: My Quandary

VivienRolfe: I fear we will build the education system that we can measure – not the one that we need. #opened15 #analytics

This is the second in the series.  The first was here. I need to admit upfront that this project is causing some serious cognitive dissonance for me, because it is forcing me to reconcile two conflicting views I have about higher education.  You can see these views in my posts over the years. These views are not unique to me: They were on display at and around the OpenEd 2015 conference, where there was significant pushback by thoughtful commentators who argued that open education is more than open text books. Well, yes, but one has to start somewhere. (I think of open text books as the “gateway drug” to open ed more generally.)

I believe that college has an experiential dimension that goes beyond the content, and to a certain extent, skills learned. The seminars that I teach are oriented around this perspective, so that the most important thing is the degree to which students have participated in, or more precisely engaged with, the process. It’s not that there isn’t content to interact with and skills to learn, but I give students a great deal of discretion about what content to explore, and about which skills they hone. My introductory courses, by contrast, are very much content and skills-oriented. If students haven’t learned the content and skills, they haven’t been successful in the course. My intermediate courses are somewhere in between.  It seems clear to me (though I don’t recall anyone actually saying this) that the importance of what I’m calling content/skills vs. experience varies by discipline.

I believe that learning is fostered when student actively engage with the material. The traditional lecture course, where the instructor lectures on the content, students (ideally) read the text, and then (hastily) study for the exams, is not a good example of an active learning approach. Students need to engage with the material, which suggests the need for regular, low stakes assignments with feedback so students will be able to monitor their learning. Again, the form of this engagement & assessment probably varies by discipline. Whether these assignments are essays, problems, or quizzes, an active learning approach of this type adds to the workload of instructors. Instructors have only 24 hours in the day, like everyone else, so we have had to make choices about how many assignments to give and of what type. There are simply not enough hours in the day or days in the week for me to give and grade as many assignments as would be ideal. Enter computer-based learning and data analytics. A computer is ideal for giving unlimited assignments with almost instantaneous grading. Of course, some assignments work better than others, and computers can only grade what they can measure. As a social scientist, I am trained to construct and use data to draw conclusions. If data analytics can help students monitor their learning, and help me help students be more successful with their learning, then I am all for it.

Which leads to my quandary: If I were to incorporate computer-based learning with data analytics, it could only assess things that can be measured. This would leave out anything that can’t (easily) be measured, like the experiential aspects of my seminars.   I believe both these things, so what to do?

Digression:  The shortcoming of courses that emphasize experience over content/skills is that grades are more subjective. But the reality is that all grades are subjective, and the less subjective they are, the more they emphasize only those aspects of learning that can be measured.  I am willing to accept this in my intro courses, but not in my seminars where I want to give students the freedom to learn what’s important to them.  Perhaps ironically, that meets the learning objectives of the course.

Another reality is that students typically don’t do that well on my introductory exams, and this is pretty common in the discipline. One response is to claim that economics is just difficult, that some/most people are just not suited to learning it. I have not yet given into that cynical view, but I don’t have a lot of evidence to support my hopes.  I want to believe that all students at the introductory level can learn the material, and that if they don’t, it’s the fault of the instructor or the system.  Don’t get me started on the pathology of final exam week

The solution I’ve found for my quandary comes from being a pragmatist and an empiricist. This academic year, I am pilot testing the Lumen Waymaker courseware I mentioned in my previous post (Principles of Macroeconomic last semester; Principles of Microeconomics this semester) to see how well it works.  I wouldn’t use courseware like this for a senior seminar, but it may make sense for an intro course.

(To be continued.)

Image Credit: John Fowler (via flickr) Balanced Rock