Bror's Blog

"Learning engineering" in action at Kaplan University - report by Ithaka

The higher education consulting firm Ithaka has done a whole series of case studies on innovative practices in higher education, providing food for thought for folks in the sector as they think about how to change.  I've had several conversations with Martin Kurzweil there about the kind of "learning engineering" work we're doing at Kaplan: applying learning science at scale by training up instructional designers on what cognitive science is finding about how expertise, learning, and various media work together, investing in developing valid and reliable probes of learning outcomes, and checking carefully (e.g., with randomized controlled trials) to see if expected improvements in learning outcomes are happening with our students in various programs. 

Ithaka was particularly interested in the work we've been doing at Kaplan University (KU), led by their President Betty Vandenbosch, to use randomized controlled trials (RCTs) as a systematic way to check "what works" (or doesn't) before deployment.  As you'll see in this case study by Ithaka, KU's Research Pipeline team has set up and run more than a hundred different RCTs in the last few years to look for impact.  As a consequence, they've had to build out good tools and processes to monitor these pilots along the way - it's far different to manage dozens of trials at once in various stages of development compared with doing an occasional trial or two.  

Ithaka thinks there's something to be learned from KU's experience for all higher education institutions.  I think so too! 

For White House Symposium on the Future of Education R&D and Digital Learning: Learning Engineers in Education

I wasn't able to attend this terrific meeting of minds last week about learning science, education R&D, and the interconnections with new technologies in education and big data learning analytics, unfortunately.  However, Katrina Stevens, one of the organizers, still suggested I contribute a piece about learning engineering, so (with her permission) here's the pre-reading piece I sent in.  The full range of pre-readings is fascinating - I hope the DoE releases them in final form, along with notes from what, by all accounts, was a fascinating day with terrific people! 

Transnational experience - a piece of long-term higher-ed goodness

Folks who look at my blog know how much I focus on applying evidence-based approaches to mastering well-defined learning outcomes - a key component of what I think learning environments need to become good at, as technology enhances and expands the types of learning experiences available, and the kind of learning evidence that can be used to judge progress.

However, there's more to learning than a narrow focus on key skills for individual productivity.  I frequently recall Dana Gioia's very good formulation of the purpose of education: to build "productive citizens for a free society." Yes, "productive citizens" comes first, but on its heels, we cannot forget "citizens for a free society."  One important component that contributes to both goals is exposure to global experience - learners, at many stages, getting experience with cultures, thinking, and meaning outside their home territory. 

"Learning engineering" making its way in the world

I recently (re)stumbled across an interesting article in EdSurge about using educational impact to evaluate ed-tech companies and services. It seems an obvious thing, but as the article points out, it's not so simple to do. It reminded me of a range of efforts that are now popping up to assist us all with “learning engineering” work – applying good learning science and evidence-gathering at scale.

Lectures and Learning – How Much Together?

A recent Op-Ed piece in the New York Times by Molly Worthen talks about her view that long-form lectures are of real value to students, at least in the humanities.

What to make of this? “It’s complicated.”

I agree (especially in the middle of the political “silly season”) that we have to make sure our students can listen to extended verbal presentations critically and well, and be able to summarize, critique, and question in real-time. Long-form lectures may also well work efficiently enough for simpler outcomes (where “simpler” is defined by the audience having enough relevant long-term memory components to easily process a spoken lecture in real time). However, looking through the lens of learning science, this is not the same as thinking long-form lectures are an efficient method of instruction for most hard, important, outcomes.

The missing craft: “Learning Engineering”

There was a terrific article in the New York Times recently by Anna North. It starts out describing persistent myths about “learning styles” in instruction, and it picks up steam when it generalizes to explore why learning research is not having an impact on students.  Although she never uses the term, the article makes it clear we suffer because we have almost no “learning engineering” professionals in our industry – and don’t realize what we’re missing.

Background and approach:

Sarina Simon, founder and President of NorthSouth Studios, conducted a virtual interview of me recently. I thought you all might find it interesting as well!

Video from AERA 2014 - Future of Online Research Opportunities and Practical Implications at Scale

Just a quick note following up on the earlier announcement about our April 2014 AERA panel session.  We had some terrific participants - Dick Clark, Carl Dweck, Ryan Baker, Richard Culatta, Ken Koedinger, Rebecca Peterson, all talking about what the new on-line platforms can contribute to research, and also talking about the practical implications of having all this on-line dat and potential for research.  

The video is now up, available on our KAPx platform (sorry, you may have to register to see it!) - Enjoy!

Many "learning engineering" themes in New York Times article on applying motivation research

Paul Tough is publishing an inspiring article, Who gets to graduate?, in the New York Times Magazine this weekend. It describes work at the University of Texas at Austin to combat failure-to-graduate by lower income students with few natural external support structures for success.  It showcases the use of cognitive science at scale along with randomized controlled trials "in the wild" to objectively improve student outcomes.  

All of us in our industry need to get busy doing more of this kind of "learning engineering!"

Google and expertise: what to generalize?

Tom Friedman recently interviewed the head of HR for Google, Lazlow Bock, about hiring approaches at Google. What Tom reports (and the very good cognitive scientist Daniel Cunningham comments on) gives a good example of how our instincts about expertise and learning can be both right and wrong.  Just as our learning environments might benefit from a deeper exposure to learning science to remove some of the misconceptions there, it may well be that our HR practices can benefit, too.