e-Literate

Present is Prologue

Tag: personalized learning

  • We’re Giving a Course on Personalized Learning Next Month

    Working with our good friends at ELI, we’re going to be offering a three-session synchronous course called Personalized Learning: Finding the Model That Fits Your Institution July 6th through 20th. As you know, we’re still in early days for personalized learning. Most campus communities are still trying to figure out what it is and what it’s good for—if they’re aware of it at all as a group. Plus, one size most emphatically does not fit all. The goal of the course is to help participants sharpen their own ideas for appropriate ways to facilitate exploration of the topic at their own institutions.

    The format will be highly participatory, especially in the second and third sessions. Phil and I expect that we will all learn a lot from each other.

    Join us!

  • Adaptive Learning Fails to Make the Grade. Or Does It?!

    My latest Chronicle column is up. It analyzes the results of the SRI Education study of the Gates Foundation adaptive learning grantees, some of which we’ve covered in our e-Literate TV case studies. If you’re looking for evidence that adaptive learning is going to deliver on the promise of a robot tutor in the sky, you won’t find it there. But it’s easy to flatten that result into “adaptive learning doesn’t work.” I don’t believe that the SRI study shows any such thing.

    First of all, what is our standard of proof? A good half of my column is devoted to the methodological challenges of doing big meta-studies like this one. It’s really hard to (ethically) control the variables across multiple classrooms well enough to get a clean result. SRI had to throw out most of the data they had for some measures.

    But equally importantly, there’s just a lot that meta-studies can’t get at precisely because the goals of each implementation are different. For example, one of the goals for implementing OLI at UC Davis was getting students more prepared to engage in higher-level critical thinking in class discussion. Here are some Davis faculty talking about their course design goals:

    I’m not sure how one would empirically measure such a result; nor could I see how to incorporate it into a meta-study that also includes, for example, Essex County College’s developmental math course.

    While the Gates Foundation should get credit for bringing in a credible third-party evaluator to review the results of the grants, ((Full disclosure: Our company received grant money from the Gates Foundation to cover personalized learning)) the design parameters for this particular study do not appear to be as useful as they might have been. That said, the larger point is that it’s really hard to do educational research well. Rather than using these studies as Rorchach tests, we should be taking the time to improve our educational research literacy and better understand what each study can and cannot prove.

  • SRI’s Study on Gates Personalized Learning Grants Is Out

    This is almost old news now, but we just haven’t been able to dig into it yet. As part of its Adaptive Learning Market Acceleration Program (ALMAP) program, the Gates Foundation funded SRI to do a study of the results of the grants after two years. I hope to finally clear some time to parse through it this week, but two high-level points jump out at me at first glance (neither of which is a big surprise):

    1. There are no conclusive wins here. This is not a robot-tutor-in-the-sky moment. A few programs did well here and there. A handful produced promising incremental gains. But this is not a report that screams, “Wow, adaptive courseware works!” The most you can say is that adaptive learning looks like it could be another arrow in the quiver that helps out in some situations—like developmental math courses at two-year colleges, for example.
    2. Large-scale educational research is incredibly hard and may actually be impossible to do rigorously for certain kinds of questions. I’ll probably get into this more when I’m ready to really write about the report, but one reason the conclusions are murky is because there so many variables in each class—not just each course subject, not just each course at one university, but even with each section of each class taught by one teacher—that really matter, some of which are impossible to control and others of which are unethical to control. It would be a mistake to overinterpret the study as showing that adaptive learning doesn’t help much. I’ve seen studies with narrower focus that have gotten clearer gains. This brings us back to the arrow-in-the-quiver theory. The wider the scope of the research focus, the more that pockets of real benefit will be obscured by noise and uncontrolled variables.

    The report is here.

  • What Homework and Adaptive Platforms Are (and Aren’t) Good For

    I was delighted that we are able to publish Mike Caulfield’s post on how ed tech gets personalization backwards, partly because Mike is such a unique and inventive thinker, but also because he provided such a great example of how “personalized learning” teaching techniques are different than adaptive content and other product capabilities.

    The heart of his post is two stories about teachable moments he had with his daughters. In one, he helped his middle school-aged daughter understand why an Iranian author was worried that people in the Western world have harmful stereotypes of Iranians. In the other, he helped his high school aged-daughter see how her knowledge of the history of rocket science could be useful in answering a question she was asked about Churchill’s Iron Curtain speech. Mike’s stories show truly significant learning of the kind that changes students’ perspectives and, if we’re lucky, their lives. It is not just personalized but deeply personal. He was able to reach his daughters because he understood them as humans, well beyond the boundaries of a list of competencies they had or had not mastered within the disciplines they were studying.

    For now and the foreseeable future, no robot tutor in the sky is going to be able to take Mike’s place in those conversations. This is the kind of personal teaching that humans are good at and robots are not. But neither are the tools we have today useless for this sort of teaching. Vendors, administrators, and faculty alike have broadly misunderstood their role and potential. In this post, I’m going to talk about both how these tools are useful for the kind of education that Mike cares about (and I care about) as well as, perhaps more importantly, why we are so prone to getting that role wrong.

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  • We Have Personalization Backwards

    [Note – an earlier version of the first half of this post was first published at Mike’s Hapgood site. We asked him to make some alterations for the e-Literate audience and republish here. – ed]

    Indie Rock and Donald Trump

    I drive my oldest daughter to high school every day. She goes to a magnet STEM school in the district that’s on the campus where I work. I’ve been brainwashing her into liking indie rock one car ride at a time using carefully planned mix CDs.

    Last week she tells me I need to put more Magnetic Fields songs in the mix. Why? I ask.

    “Physics homework.” she says.

    It turns out that there’s a number of principles of physics that she remembers through a complex set of associations she’s developed referencing indie rock songs. I don’t pretend to get them all, but the 69 Love Songs hit “Meaningless” plays an apparently crucial role.

    Later that day, my youngest daughter is asking me about the book Persepolis, a book about growing up Iranian during and after the 1979 Islamic Revolution. The author of that book spends the preface talking about the reasons she wrote it, and how she felt the understanding of her native country of Iran was too narrow, and in a way, too exotic. My daughter tells me that she doesn’t quite get what the author is talking about. After all, there’s a lot of fundamentalism in the early parts of the book — and people really are in a revolution in 1978, so what are we getting wrong in the West?

    I know that this daughter, a middle schooler, has had some stress about Donald Trump. She has people in her class who like him, and she can’t understand why when he’s so mean. It worries her.

    I ask her if Trump gets elected, how would she feel if everyone assumed all Americans were like Donald Trump. Well, we wouldn’t be, she says.

    Oh, she says.

    We Have Personalization Backwards

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  • The Battle for “Personalized Learning”

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    So here we go again. Another terminology war. First there was the battle for open. Then the battle for MOOCs. Somewhere in there was the battle for edupunk.

    I stay out of terminology wars because, even though they are often about very real and important issues, the emphasis on finding a single correct definition tends to distract rather than focus the conversation.

    It’s a different with “personalized learning” because there is no fight over its meaning right now. Rather, it seems to have no specific meaning at all. Sometimes it is used interchangeably with “adaptive learning.” But not always. And not exactly. More often it means, roughly, “robot tutor in the sky.” Shorter version: “WHEEEEEE!!!” Or maybe, “Wingardium leviosa!”

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    Phil and I have decided to claim this prime piece of linguistic real estate. We are asserting squatters’ rights.

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  • No Filters: My ASU/GSV Conference Panel on Personalized Learning

    ASU’s Lou Pugliese was kind enough to invite me to participate on a panel discussion on “Next-Generation Digital Platforms,” which was really about a soup of adaptive learning, CBE, and other stuff that the industry likes to lump under the heading “personalized learning” these days. One of the reasons the panel was interesting was that we had some smart people on the stage who were often talking past each other a little bit because the industry wants to talk about the things that it can do something about—features and algorithms and product design—rather than the really hard and important parts that it has little influence over—teaching practices and culture and other messy human stuff. I did see a number of signs at the conference (and on the panel) that ed tech businesses and investors are slowly getting smarter about understanding their respective roles and opportunities. But this particular topic threw the panel right into the briar patch. It’s hard to understand a problem space when you’re focusing on the wrong problems. I mean no disrespect to the panelists or to Lou; this is just a tough nut to crack.

    I admit, I have few filters under the best of circumstances and none left at all by the second afternoon of an ASU/GSV conference. I was probably a little disruptive, but I prefer to think of it as disruptive innovation.

    Here’s the video of the panel: