Bror's Blog

Learning engineering double-header: EIS and AERA

Last month there were two events in fairly close proximity that are worth reviewing together.  During AERA and at the ASU Education Innovation Summit (EIS) there were sessions talking about why evidence-based approaches continue to get short shrift in education technology and education at scale.  It’s clear (at least to researchers) that there’s a tremendous opportunity to improve learning, and researchers are interested in being involved – if they can figure out how to be helpful, not merely asked to rubber-stamp projects at the end. It’s a mix of things to tackle, it seems: more informal communication between investors, decision-makers, and learning scientists about what’s possible; more practical evidence at scale about how to do the work; more examples of success to draw on; more support for better decision-making by buyers.  It’s not simple, clearly, but not impossible either.

An AERA summer drink: Mix cold cognition with warm motivation, and create a stir

The 2013 AERA meeting was a huge (13000 plus attendees), complicated (2400+ sessions), long (five full days in San Francisco for 2013) education research conference, with some unusual sessions. Yet, if you dig a little, you can find real gems, including research from David Feldon, Briana Timmerman, and colleagues, showing a simple intervention change based on cognitive task analysis can lift both learning and retention in an early science course in college. 

The full story is even more interesting!

“Practice-based” teacher education is really learning-based education

An interesting article in EdWeek last month about new methods for teacher preparation caught my eye.  It described an approach focused on giving teachers a specific repertoire of competencies through structured training and practice before they’re let loose on classrooms.  What’s reassuring (and maybe puzzling this didn’t happen earlier) is how close this new approach to training teachers is to what research says works best for learning.

Two sessions will explore: Why so little learning science?

In the next few weeks there will be two different sessions (full disclosure: I’m a panelist on both) talking about how education can benefit from more learning science, one at the ASU GSV meeting in Scottsdale Arizona, and the other at the huge education research conference, AERA.  The audiences are the right ones to also give insight into why that hasn’t happened yet.

Big Data: A big part of the education innovation mix – not all of it

Big data is big news.  Some might think the arrival of very large education-related data sets spells the end of our education troubles – that by analyzing this data, all necessary new information to accelerate learning will be revealed. 

Not quite!

"Rabbit has Brain" [said Piglet] . . . "[T]hat's why he never understands anything" [said Pooh]

My friend Richard Clark from USC pointed me to a very interesting, but troubling, study recently published in Europe. It looks at teachers' misconceptions about learning statements that have been steeped in either neuroscience language or in “brain-based” language. Even teachers who are enthusiastic about neuroscience, and view themselves as reading popular science versions of neuroscience findings, turn out to believe a variety of “neuromyths” about learning – false statements about what works for learning, clothed in the language of scientific findings.

If we are to make progress with learning at all levels, we have to figure out how to help teachers – and most especially those who design instructional environments and materials – avoid falling prey to palatable but unproven assertions about how learning works.

Into the wild: Checking learning environments against learning science

As I've written in this blog on numerous occasions, there is a ton of learning science already out there (e.g., the synthesis available in E-Learning and the Science of Instruction by Ruth Clark and Richard Mayer, or the very nice exposition by Daniel Willingham in Why Don't Students Like School, among many other sources). Unfortunately, much of it is only accidentally incorporated into real learning environments at scale.

What we should be doing as we evaluate new offerings or new work we're proposing to do or fund, is to compare what we're looking at against principles and features that learning science has established can make a difference.

We here at Kaplan have built a checklist for this purpose, and we thought it would be fun to release the checklist and the training course for it into the wild.

Competencies and assessment: what's learning science got to do with it?

At a recent meeting sponsored by iNacol to think deeply about competency and assessment, we talked about what impact the last few decades of learning science should have on doing the best job planning and using competencies for learning.

The good news is the learning science lines up with the idea of personalizing instruction, and the pace of instruction, for individual learners: they're likely to be more motivated, and more successful, if they can work and master at different rates, doing different things, to get to the same competencies.

However, not every way you could conceive of making learning personalized is likely to match how learning and expertise actually work.

“Students online” vs “student's learning”?

A recent letter in the Wall Street Journal from an over-burdened college professor, Larry Bensky, lamented the push he was feeling towards teaching more students (90 instead of 60) in his summer school online course. He was particularly worried about the quality of instruction he could provide with a 30% increase in student load. Are university students – and professors – doomed to increasingly mediocre learning experiences as technology advances and costs to deliver instruction are forced downwards?

Performance by education trio: Gates, Khan, Saxberg

I had the good fortune to be invited to attend the Microsoft CEO Summit in Seattle last week.  This is a yearly gathering of 100 or so of the world's most prominent CEOs (covering 30 countries and 11 million employees this year) to talk together, with Bill Gates, and with the Microsoft brain trust, about key themes in the world and how they are all engaging with those themes.  

Part of the attraction of the summit, which has run for 16 years, is that no press, no social media, almost no information comes out from the meeting - it's a very relaxed, informal set of informed panels and engaged discussions between the CEOs and a few visiting experts. The topics, and the presenters, are a pretty wide-ranging group, from Daniel Kahneman and Tom Friedman talking about the structure of minds and implications for our future, to workshops on branding, social media, Brazil, growth, and (of course) technology, to wide-ranging discussions with Bill Gates, Jeff Bezos, Warren Buffet and Jamie Dimon about business decision-making, strategies, innovation, and more.  

This year they released the video of one session in education, where Walter Isaacson interviews Bill Gates, Salman Khan, and myself for about 45 minutes on how education is beginning to innovate, especially now with a variety of players using technology to offer more and more learning opportunities that are starting out free to users.

We talk about learning, employment, cognitive science, evidence-based instructional desigh, technology, the role of for-profit in a world of free materials, and more.  See what you think!