Continuing with our reading of Richard DeMillo’s Revolution in Higher Education: How a Small Band of Innovators Will Make College Accessible and Affordable (2015) (publisher; Amazon): this week we’re discussing chapter 4, “Technology Curves.”
Here DeMillo changes tack from neuroscience (chapter 3) and returns to technology, but not very much to MOOCs. The focus now is technology for personalized learning, including data analytics.
That’s not where the chapter begins. Instead we start with TED Talks, which I didn’t expect, then move on to Britain’s Open University, and MIT’s OpenCourseWare, all of which DeMillo approves, but aren’t what he’s looking for.
They were Chautauqua performances… the vast majority of these open courses carried no credit, did not constitute a curriculum, and did not lead to a degree. Interaction was destined to replace [these]… with something else entirely. (1966)
None of these offer the kind of teaching DeMillo wants, starting with what he identified last chapter: “The effect of feedback is stronger than almost any other single factor in stunt achievement” (1999). Allied to feedback is “testing that is spaced out appropriately over time as opposed to a single, cumulative test. In fact, the frequency of treating alone accounts for most of the variation in learning outcomes…
” Plug this into the digital world, and
technology-enhanced learning makes it more likely that feedback and formative evaluations along with a dozen other techniques that are known to have a major effect on achievement will be carried out. (2008)
Just using a clicker for formative assessment makes a big difference (2023) (paging Derek Bruff!). Web-based peer review can also do the trick (2083), which inspired at least one start-up, NovoEd. Pushing hard on the digital front, Georgia State University and the Education Advisory Board piloted a promising use of data analytics (2210ff).
In this chapter DeMillo returns to one major theme, broadening access to higher education. He wants us to consider the possibility that big data and analytics could address social problems, citing Michael Crow, ASU:
“The exciting thing is that we may finally be able to attack unfairness in the system by overcoming the limits of culture and individual circumstance… Can we take kids from any background that have a certain capability and ‘net out’ their individual circumstance?”(2138)
It’s a cliche to toss around “revolution” these days, but DeMillo really wants us to think along those lines, at this point in his book. Revolution in Higher Education now sees us in the midst of a complex breakthrough in teaching and learning.
- This is a very pro-technology chapter, from the first page on. “In virtually every known category of learning, technology appears to be driving improvements in learning achievement.” (2247)
- “learning analytics will certainly be in widespread use by the time [this book] is published” (1796). Not quite.
- There’s a strong swipe at instructors who connect well with learners.
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“[I]mmediacy has almost no noticeable effect on [academic] achievement.” (1990) Even mentoring gets the treatment.
- Notice the, ah, interesting case of a company recruiting unpaid tutors for online learning (2100).
What do you make of it?
Next week, starting November 30th, is chapter 5: Internet Scale.
Would you like to follow along? Simply snag a copy of the book from your library or MIT Press or the local bookshop or Amazon (etc.), and get reading. I’ll post about each chapter at the start of each week, so you can add comments there. I’ve set up a tag for all posts: demillorevolution. Twitter’s also a fine place to chat (I’m @BryanAlexander). If you’re into Goodreads, let us know so we can catch up (here’s me).
(thanks to Todd Bryant for keen-eyed correction)
Technology curves are interesting, and the one I think we talk about most in my liberal arts undergraduate environment is that of learning analytics. Are these obtainable by looking at engagement with technology? I viewed an interesting Educause Online presentation in October called “Impact of Digital Resources on Learning.” I’m interested in this from the librarian side, as we have moved some of our instruction to technology-based tutorials, but also from the teaching side as the librarian to the liaison department. They spoke of engagement metrics, something that exists to some extent in our course management system. But for these to be effective, the majority of the work would need to somehow be represented in digital form within the CMS. Our professors do not have widespread acceptance/usage of this technology, even now. It isn’t a criticism at all, it’s definitely a decision based on what they are trying to accomplish and how. It is just awfully hard to push analytics and metrics for tools that don’t have enough use to generate comparable data.
Here in the land of liberal arts, we are facing other types of disruption to instruction – just this week our faculty will vote whether we are getting rid of one of our freshman seminars. We currently require two – one writing and one regular, and the proposal on the floor is to dump the non writing seminar and require an additional writing requirement later on. A keen colleague pointed me to this article: http://er.educause.edu/articles/2012/3/disrupting-ourselves-the-problem-of-learning-in-higher-education
I’m reading it through the lens of a potentially disappearing FYS (deep down which I believe to be too soon, too soon), but it could be read through the filter of the technology curve as well. Just to link DeMillo to another perspective out there at the moment.
Great point about the gap between data analytics and faculty practice, Jenny. The LMS should be the way forward, but this could take some time.
Can you say more about why some Furman faculty want to end the non-writing seminar?