e-Literate

Present is Prologue

Category: Curricular-Materials

This category includes digital curricular materials, including adaptive learning, assessments, OER, etc.

  • 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:

  • Pop Quiz

    Which CEO has recently said or done all of the following:

    • Suggested to an audience of VCs and ed tech entrepreneurs at the GSV conference that the importance of big data in education has been overstated
    • Told that same audience that the biggest gains from adaptive learning come when it is wrapped in good pedagogy delivered by good teachers
    • Asked former CIOs from Harvard and MIT, both of whom are senior company employees, to develop collaborations with the academic learning science community
    • Accurately described Benjamin Bloom’s two-sigma research, with special attention to the implications for the bottom half of the bell curve
    • When asked a question by an audience member about an IMS technical interoperability standard in development, correctly described both the goals of the standard and its value to educators in plain English

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  • Personalized Learning vs. Adaptive Learning

    In our recent EDUCAUSE Review article, Phil and I defined personalized learning as a set of technology-supported practices that help undepersonalize teaching. The three general practices that we identified are as follows:

    1. Moving content broadcast out of the classroom: Even in relatively small classes, a lot of class time can be taken up with content broadcast such as lectures and announcements. Personalized learning strategies often try to move as much broadcast out of class time as possible in order to make room for more conversation. This strategy is sometimes called “flipping” because it is commonly accomplished by having the teacher record the lectures they would normally give in class and assign the lecture videos as homework, but it can be accomplished in other ways as well, for example with reading-based or problem-based course designs.
    2. Turning homework time into contact time: In a traditional class, much of the work that the students do is invisible to the teacher. For some aspects, such as homework problems, teachers can observe the results but are often severely limited by time constraints. In other cases, such as comprehension of assigned readings, the students’ work is invisible to the teacher and can be observed only indirectly and with significant effort. Personalized learning approaches often allow the teacher to observe the students’ work in digital products, so that there is more opportunity to coach students. Further, personalized learning often identifies meaningful trends in a student’s work and calls the attention of both teacher and student to those trends through analytics.
    3. Providing tutoring: Sometimes students get stuck in problem areas that don’t require help from a skilled human instructor. Although software isn’t good at teaching everything, it can be good at teaching some things. Personalized learning approaches can offload the tutoring for those topics to adaptive learning software that gives students interactive feedback while also turning the students’ work into contact time by making it observable to the teacher at a glance through analytics.

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    Personalized learning is a set of things that you do, not a set of things that you buy. Products can support or enable personalized learning practices, but they are not “personalized learning products.” And in fact, once you have products that support personalized learning practices, that’s actually when the hard work begins. OK, so you moved content broadcast out of the classroom. Now what are you going to do with class time? Students get some benefit from having course content that they can review multiple times at home, but most of the big gains typically come from the teacher reclaiming class time for more high-value direct and interactive work with the students.

    On the other hand, adaptive learning is a label that applies to products. Further, adaptive learning products can support all of the practice areas of personalized learning. They enable teachers to move content broadcast outside of class time, they make homework time into contact time through analytics, and they provide some tutoring function. “Adaptive” tends to provoke a lot of discussion around the latter of the three practice areas. See the piece I wrote for the American Federation of Teachers if you want a primer on the strengths and limitations of adaptive learning products as tutors. But as often as not the first two capabilities, neither of which is dependent on adaptive algorithms, are the ones that enable the biggest gains in personalized learning teaching practices. “Courseware” is a set of products that, when designed well and used properly, can enable faculty to move content broadcast out of the classroom and make homework time content time. Adaptive courseware adds the tutoring element while also, if done well, increasing the value of that homework contact time by providing better feedback through more targeted analytics.

  • Defining Personalized Learning

    As many of you know, Phil and I have been exploring the topic of “personalized learning” for the past year, trying to figure out what the heck it means and what it’s really good for, separate from the hype. We’ve boiled down the idea into the beginnings of a framework, which we’ve just had published in EDUCAUSE Review. The central focus is to think of “personalized learning” as a set of technology-supported teaching practices that un depersonalize teaching. While we’re exploring that, we also dive into the question of why hype happens, why the hype cycle exists, and how we can try to kill it.

    You can read it here.