e-Literate

Present is Prologue

Tag: personalized learning

  • The Rise of Antisocial Deconstructivism

    Phil and I gave our first ever joint keynote at the OLC conference this week. We didn’t want to just do dueling PowerPoints, so instead we tried a format that I have been calling a social constructivist keynote. Each of us would present on a topic for a few minutes, and then the two of us would talk about it for a few minutes. We planned the arc of the topics we would cover in advance, but we didn’t rehearse the talks for each other or script the conversation. The discussions came pretty close to the kind of bull shooting conversations that we have all the time. We set a time limit of eight minutes for each segment so that we could get through our presentation with enough time to bring the audience into the conversation at the end. It seemed to work pretty well.

    In the course of the conversation, we spontaneously came up with a term that we both like and that seemed to resonate with the audience: antisocial deconstructivism. ((“Antisocial deconstructivism” should not be confused with “antisocial deconstructionism,” the latter of which is redundant. Anyone who writes like Derrida did clearly is actively hostile to the idea of shared meaning making as something that provides net positive value, or even the desire to communicate with other humans.)) It’s the approach of breaking learning down into teeny, tiny bits, tied to fine-grained competencies and micro-assessments, that students learn on their own by following a prescription that is created for them, possibly with the help of a robot. To be clear, the term isn’t entirely meant to mock. There are times when antisocial deconstructivism is an appropriate pedagogical technique. For example, it’s pretty good for helping nursing students memorize medical terminology or IT students learn the basic components of a network. It can be good for learning some math kinds of skills, depending on your philosophy of math education. Any situation in which you are working fairly low on Bloom’s Taxonomy might be OK for it as an approach. Procedural knowledge that either doesn’t require higher order problem solving skills or where problem solving skills are best built incrementally by slowing increasing problem complexity is a particularly appropriate type of candidate for antisocial deconstructivism.

    But we do mock it when it is presented not as a pedagogical technique but as a pedagogical ideology. It’s the idea that anything worth learning can be learned best, most cheaply, and “at scale” this way. It’s the fetishization of one tool in the teaching toolbox as the technological society’s Great Leap Forward. The worst, crudest examples of MOOCs, Competency-Based Education, and personalized learning software hype are all manifestations of this stunted (and self-interested) view of education. Antisocial deconstructivism is like botulism. A little bit injected in just the right spot by a trained expert can smooth out some wrinkles that bother you, treat a chronic headache, or refocus a lazy eye. A little more injected in the wrong places and you can quickly start to look like a parody of the thing that you are trying to be. Any more that, and what you have is not a tool but a toxin.

    You might be suffering from antisocial deconstructivist toxicity if you find yourself believing any of the following:

    • Short videos of lectures by Ivy League professors, coupled with little quizzes at the end, will almost always provide a better education than a class taught by a live, human, non-Ivy League professor.
    • Short vendor-produced articles or animations, coupled with little quizzes at the end, will almost always provide a better education than a class taught by a live, human, non-Ivy League professor.
    • We think of our product like a robot tutor in the sky that can semi-read your mind and figure out what your strengths and weaknesses are, down to the percentile.

    If you exhibit any of these symptoms, then get yourself to a great teacher immediately and have them demonstrate for you what it is that videos, quizzes and robots cannot do.

  • Release of Analysis Episode for e-Literate TV Series on Personalized Learning

    Today we are thrilled to release the the final episode in our new e-Literate TV series on “personalized learning”. In this series, we examine how that term, which is heavily marketed but poorly defined, is implemented on the ground at a variety of colleges and universities. While today’s episode is the final one released due to its analysis of what we learned in the five case studies, it was designed to be used as an introduction to the series.

    We have deliberately held back from providing a lot of analysis and commentary within each case study – letting faculty, students, administrators and staff speak for themselves – but in today’s episode we share some of the key lessons we learned. We had a variety schools profiled in the series, and our analysis addresses the commonalities and differences that we saw. You can see the analysis episode at this link or in the embed below.

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    Introduction: What Did We Learn In Our Personalized Learning Series?

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  • Personalized Learning is Hard

    Paul Fain has written a really good, nuanced article at IHE covering the update that Essex County College gave of their developmental math adaptive learning pilot at a recent conference in Washington, DC. We did a two–part case study on ECC in our e-Literate TV series). The headline results are as follows:

    • In the first year, the pass rate was worse than  in the traditional classes. (The first semester was “disastrous.”)
    • This year—the second year—the pass rate is coming closer to the traditional class but is still underperforming.
    • The article seems to imply that students who earn a C in the personalized learning class do better than students who earn a C in the traditional class, but the article is not explicit about that.

    There is no magic pill. As Phil and I have been saying all along—most recently in my last post, which mentioned ECC’s use of adaptive learning—the software is, at best, an enabler. It’s the work that the students and teachers do around the software that makes the difference. Or not. In ECC’s case, they are trying to implement a pretty radical change in pedagogy with an at-risk population. It’s worth digging into the details.

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  • The Fraught Interaction Design of Personalized Learning Products

    David Wiley has a really interesting post up about Lumen Learning’s new personalized learning platform. Here’s an excerpt:

    A typical high-level approach to personalization might include:

    • building up an internal model of what a student knows and can do,
    • algorithmically interrogating that model, and
    • providing the learner with a unique set of learning experiences based on the system’s analysis of the student model

    Our thinking about personalization started here. But as we spoke to faculty and students, and pondered what we heard from them and what we have read in the literature, we began to see several problems with this approach. One in particular stood out:

    There is no active role for the learner in this “personalized” experience. These systems reduce all the richness and complexity of deciding what a learner should be doing to – sometimes literally – a “Next” button. As these systems painstakingly work to learn how each student learns, the individual students lose out on the opportunity to learn this for themselves. Continued use of a system like this seems likely to create dependency in learners, as they stop stretching their metacognitive muscles and defer all decisions about what, when, and how long to study to The Machine.

    Instructure’s Jared Stein really likes Lumen’s approach, writing,

    So much work in predictive analytics and adaptive learning seeks to relieve people from the time-consuming work of individual diagnosis and remediation — that’s a two-edged sword: Using technology to increase efficiency can too easily sacrifice humanness — if you’re not deliberate in the design and usage of the technology. This topic came up quickly amongst the #DigPedNetwork group when Jim Groom and I chatted about closed/open learning environments earlier this month, suggesting that we haven’t fully explored this dilemma as educators or educational technologist.

    I would add that I have seen very little evidence that either instructors or students place a high value on the adaptivity of these products. Phil and I have talked to a wide range of folks using these products, both in our work on the e-Literate TV case studies and in our general work as analysts. There is a lot of interest in the kind of meta-cognitive dashboarding that David is describing. There is little interest in, and in some cases active hostility toward, adaptivity. For example, Essex County College is using McGraw Hill’s ALEKS, which has one of the more sophisticated adaptive learning approaches on the market. But when we talked to faculty and staff there, the aspects of the program that they highlighted as most useful were a lot more mundane, e.g.,

    It’s important for students to spend the time, right? I mean learning takes time, and it’s hard work. Asking students to keep time diaries is a very difficult ask, but when they’re working in an online platform, the platform keeps track of their time. So, on the first class day of the week, that’s goal-setting day. How many hours are you going to spend working on your math? How many topics are you planning to master? How many classes are you not going to be absent from?

    I mean these are pretty simple goals, and then we give them a couple goals that they can just write whatever they feel like. And I’ve had students write, “I want to come to class with more energy,” and other such goals. And then, because we’ve got technology as our content delivery system, at the end of the week I can tell them, in a very efficient fashion that doesn’t take up a lot of my time, “You met your time goal, you met your topic goal,” or, “You approached it,” or, “You didn’t.”

    So one of the most valuable functions of this system in this context is to reflect back to the students what they have done in terms that make sense to them and are relevant to the students’ self-selected learning goals. The measures are fairly crude—time on task, number of topics covered, and so on—and there is no adaptivity necessary at all.

    But I also think that David’s post hints at some of the complexity of the design challenges with these products.

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  • Using TAs As Key Component Of Active Learning Transformation at UC Davis

    Last week I described how UC Davis is making efforts to personalize one of the most impersonal of learning experiences – large lecture introductory science courses. It is telling that the first changes that they made were not to the lecture itself but to the associated discussion sections led by teaching assistants (TAs). It is well known that much of the instruction in lower division classes at large universities is led not by faculty but by TAs. This situation is often seen as a weakness of the business model of a research university, but it can also be leveraged as an opportunity to lead educational change. Consider this interview with staff from the iAMSTEM group at UC Davis from our e-Literate TV series on personalized learning:


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  • UC Davis: A look inside attempts to make large lecture classes active and personal

    In my recent keynote for the Online Teaching Conference, the core argument was as follows:

    While there will be (significant) unbundling around the edges, the bigger potential impact [of ed innovation] is how existing colleges and universities allow technology-enabled change to enter the mainstream of the academic mission.

    Let’s look at one example. Back in December the New York Times published an article highlighting work done at the University of California at Davis to transform large lecture classes into active learning formats.

    Hundreds of students fill the seats, but the lecture hall stays quiet enough for everyone to hear each cough and crumpling piece of paper. The instructor speaks from a podium for nearly the entire 80 minutes. Most students take notes. Some scan the Internet. A few doze.

    In a nearby hall, an instructor, Catherine Uvarov, peppers students with questions and presses them to explain and expand on their answers. Every few minutes, she has them solve problems in small groups. Running up and down the aisles, she sticks a microphone in front of a startled face, looking for an answer. Students dare not nod off or show up without doing the reading. (more…)

  • Release of University of California at Davis Case Study on e-Literate TV

    Today we are thrilled to release the fifth and final case study in our new e-Literate TV series on “personalized learning”. In this series, we examine how that term, which is heavily marketed but poorly defined, is implemented on the ground at a variety of colleges and universities. We plan to cap off this series with two analysis episodes looking at themes across the case studies.

    We are adding three episodes from the University of California at Davis (UC Davis), a large research university that has a strong emphasis in science, technology, engineering, and math or STEM fields. The school has determined that the biggest opportunity to improve STEM education is to improve the success rates in introductory sciences classes – the ones typically taught in large lecture format at universities of their size. Can you personalize this most impersonal of academic experiences? What opportunities and barriers do institutions face when they try to extend personalized learning approaches?

    You can see all the case studies (either 2 or 3 per case study) at the series link, and you can access individual episodes below. (more…)