Last week I enjoyed some quiet vacation time – sans wifi – on a lake in rural Tennessee with my family. This break gave me some time to think, worry, and write. I now have no doubt that the overwhelming majority of general education courses and some specific degree programs will transition entirely to OER in US higher ed. That horse is out of the barn. I spent most of my thinking time last week wondering about obstacles in the way of the ubiquitous adoption of OER in US higher education and how we might overcome them. This led me to connect two seemingly unrelated threads.

Observation 1: We Need Dramatically More OER, and Current Approaches Won’t Get Us There

A growing number of individual faculty, as well as groups of faculty comprising entire degree programs, are choosing to abandon increasingly expensive textbooks (e.g., see this article on the $400 textbook) for open educational resources (OER). This strategy is extraordinarily effective at eliminating barriers to access and success for students in many of the highest enrolling courses, like introductory and general education courses, business courses, and mathematics courses.

However, faculty that want to use OER sometimes find that insufficient resources are available for the specific courses they teach. The problem exists for both popular community college degree programs, like criminal justice or nursing, and upper division courses in universities. Given that universities can have over 2000 courses in their catalogs, and there are sufficient OER available for something like 100 courses, there are still around 2000 courses worth of OER that need to be created – and constantly updated – before we can realize the vision of ubiquitous OER adoption across all of higher education (recognizing the narrow but important limits on replaceability I have outlined previously).

Foundations and other institutions funded the initial wave of OER production which, over the past decade or so, has brought the field of open educational resources to where we currently are. While this pattern will likely continue at some level, the funding and production models that successfully kickstarted the OER movement cannot possibly scale to provide an additional 2000 courses worth of material. This inability to provide enough OER to meet faculty and student demand is a critical obstacle to achieving ubiquitous adoption of OER across all of higher education. You can’t adopt what isn’t there.

(You may be tempted to say that the inability of the market to respond to clear signals of demand for OER proves that there is something fundamentally broken with the economics of OER. If OER “worked right,” “the market” would obviously “deploy capital” and solve the “demand problem,” you might think to yourself. If you had a thought like this one, please pause for a few moments and familiarize yourself with the brilliant work of Yochai Benkler before continuing.)

Observation 2: Replacing Disposable Assignments with Renewable Assignments is Awesome

The defining characteristic of a disposable assignment is the tacit understanding that as soon as the faculty member returns the graded assignment to the student, the student will promptly throw it away. Aside from their pedagogical benefit – which faculty are notoriously poor at helping students understand – disposable assignments add no value to the world. Given its immutable destiny for the garbage can, students see little value in investing themselves in these assignments. And faculty dislike grading these assignments almost as much as students dislike doing them, and for the same reasons.

However, assignments don’t have to be a seemingly pointless endeavor that drive both students and faculty to complain on Facebook about completing them and grading them. There are excellent pieces of student homework that have undeniably made the world a better place. Take Murder, Madness and Mayhem, Project Management for Instructional Designers, and Emerging Perspectives on Learning, Teaching, and Technology as examples. In each of these cases, students created new material or revised existing material, ensuring that the final product was thorough, thoughtful, well documented, and well suited to the needs of students studying specific topics. Three of the articles written for Murder, Madness and Mayhem achieved Featured Article status on Wikipedia and have already been viewed by hundreds of thousands of readers with hundreds of thousands more to come. Project Management for Instructional Designers and Emerging Perspectives on Learning, Teaching, and Technology have been adopted at several universities.

None of these assignments will ever see the bottom of a garbage can. And the value they add to the world increases exponentially because they are all openly licensed. In addition to being viewed and used by countless people, they will also be extended, revised, and improved by future students and others. As a contrast to “disposable” assignments, it seems appropriate to call these renewable assignments. These renewable assignments result in meaningful, valuable artifacts that enable future meaningful, valuable work. Students tell me that they invest significantly more time and effort in these assignments and enjoy doing them more. And as a faculty member I can definitely say that I find grading these assignments to be much more rewarding.

Of Birds and Stones

There appears to be a fascinating opportunity here to kill multiple birds with a single stone. Could a move to renewable assignments solve the problem with scaling OER production?

First, let’s see what kind of capacity we’d be talking about. How much time are students collectively spending doing disposable assignments?

  • In 2012 there were over 20 million students enrolled in US institutions of higher education. 13M of these were full-time and 7M were part-time.
  • If the full-time students are taking 12 credit hours per semester and the part-time students are taking six, then the average student is taking about 10 credits per term, or 20 credits per year.
  • Students are often told to expect to spend two hours outside of class for every hour they spend in class.
  • Much of the time students spend outside of class is reading for class, studying for tests, etc. Let’s be conservative and estimate that only 5% of their outside of class time is spent doing what we would call disposable assignments.
  • What does that give us? 20M students x 20 credits per year x 2 hours outside of class per credit x 5% of that time spent on disposable assignments = 40 million hours spent by students on disposable assignments. Every year. Year after year.

It’s a bit like Shirky’s notion of cognitive surplus. These are 40 million hours that students are already spending every year producing artifacts specified by faculty. Faculty simply need to tweak the specification to which students are working. And if converting some proportion of those disposable assignments into renewable assignments would provide the benefits I’ve listed above and others I’ve discussed before, it would be worth doing even outside the context of the OER supply problem. Providing a solution to the OER supply problem is a happy secondary benefit that just makes it that much more worth doing. The idea of instructional materials written by students for students is incredibly appealing to me.

Ok, there’s clearly enough student production capacity already in place. What would faculty have to do to make this work?

Faculty will have to be thoughtful about creating and providing a Table of Contents-like framework in which the renewable assignments can be completed and combined into a textbook replacement. Benkler covers this territory in some detail, though there will be important differences when contributors are students as opposed to the traditional volunteer contributors of open source software Wikipedia. In general this should make the task easier instead of harder.

Renewable assignments also imply a shift in faculty thinking from “grading” to “editing.” For each individual assignment, each individual student is creating an artifact that provides a unique, student-centric view of a topic. This artifact will be learned from and then extended and improved upon by future students. Faculty editorial feedback and direction encourages students to make this work as good as it can be – hopefully in many cases good enough to be provided to students in place of a section or chapter of a textbook.

Thinking about the whole collection of assignments, the faculty member is essentially editing a volume of contributed pieces. Some of them might be shorter essays and others might be book chapters. Some might be videos or original songs or printable card games. Faculty will of course need to assign a grade to the artifact at some point, but my experience has been that when students are engaged in this kind of task almost all of the work ends up being A work.

Finally, faculty need some basic level of facility with open licenses and technology to make this work. They will need to be able to explain to students what the Creative Commons Attribution License is, what obligations it places on users, what rights it extends to users, and why students should openly license their work. And they will need to be able to help students who agree to publish their work online under an open license actually do so.

These requirements of framework creation, editing, explaining open licenses, and providing technology support will be beyond many faculty unless they receive some targeted professional development. This means that, while the total amount of time students currently spend on disposable assignments may be around 40 million hours, we can’t actually reclaim all of them. We probably can’t even reclaim most of them. Still, even a tiny percentage of them would yield 500,000 or a million hours year after year focused on producing and improving OER – for students, by students. (The connections to Von Hippel’s work on democratizing innovation have interesting application here as well.)

Next Steps

I need to think about this more, but that’s the point of most of my writing – thinking out loud. The majority of the logistics for making this work are either outlined by Benkler or things we’ve already learned through previous experiments like Project Management for Instructional Designers. There will be messaging and professional development challenges. These will be real challenges but they don’t appear, a priori, to be insurmountable. And we don’t actually need to reach every faculty member initially – we only need to reach a sufficient number. Something like 5 faculty per course (out of all the faculty in the country teaching that course) would likely be enough to create an initial openly licensed textbook replacement in 2 years. Then others could begin adopting and extending that baseline collection. Network effects then ensue.

Thoughts? What am I missing?


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With all the excitement in the air about big data, analytics, and adaptive instruction, it is easy to imagine a future of complete automation. In this future, algorithms will choose what we will learn next, which specific resources we will interact with in order to learn it, and the order in which we will experience these resources. All the guesswork will be taken out of the process – instruction will be “optimized” for each learner.

There are many reasons to be deeply concerned about this fully automated future. One of the things that concerns me most about this vision of “optimized” instruction is its potential to completely undermine learners’ development of metacognitive skills and deprive them of meaningful opportunities to learn how to learn.

Like every other skill – from playing the piano to factoring polynomials to reasoning about the likely causes of historical events – learning how to learn requires practice. Learners need opportunities to plan out their own learning and select their own study strategies and learning resources. Learners need opportunities to monitor and evaluate the effectiveness of the strategies and resources they’ve selected in support of their own learning. Learners need to experience – and reflect on – a range of successes and failures in regulating their own learning in order to understand what works for them, and how they should approach the next learning task they encounter in school or life.

Some adaptive systems are designed specifically to take control of these metacognitive processes away from learners. These systems make decisions on behalf of the learner, monitoring what does and doesn’t appear to be working and updating their internal models and strategies. The processes by which these decisions are made are hidden from the learner, and are likely trade secret black boxes into which no reviewer can ever peer. At the end of the current reading, or video, or simulation, the system will present the learner with a “Next” button that hides all the complexity and richness of the underlying decision, and simply presents the “optimal” next learning activity to the learner.

Without meaningful opportunities to develop metacognitive skills, there is no reason to believe that learners will develop these skills. (Have you ever spontaneously developed the ability to speak Korean without practicing it?) A fully adaptive system likely never provides learners with the opportunity to answer questions like “What should I study next?”, “How should I study it?”, “Should I read this or watch that?”, or “Should I do a few more practice exercises?” It goes without saying that the ability to learn quickly and effectively is possibly the single most important skill a person living in the modern world can have. In this context, any potential short-term benefits of adaptive instruction seem like a poor trade.

Instead of designing technologies that make choices for students, we have an important opportunity to design technologies that explicitly support students as they learn to make their own choices effectively. Such technologies must respect learner agency, leaving key choices in their hands – even at the risk of learners making some suboptimal choices. (I should say that fully automated recommendations, like “Consider viewing this supplementary video,” fit within this framework to the degree that they respect learner agency.)

Of utmost importance, these new systems must provide learners with simple ways to reflect on the choices they make about their learning and the results of those choices. I believe that providing this kind of feedback, together with opportunities to reflect on what it means, will be a hallmark of future educational technologies that support radical improvements in learning.