e-Literate

Present is Prologue

Author: Michael Feldstein

  • Cengage MindTap and the Evolution of Courseware

    So MindTap just won a CODiE award for “Best Post-secondary Personalized Learning Solution.” In and of itself, this isn’t a big deal. No offense intended to current or prior winners, but the CODiEs often feel like awards for “Best Instant Coffee” or “Best New Technology Product by an Important Sponsor of Our Awards Program.” They’re not exactly signals of breakthrough educational product design. But I’m glad that the award was given in this case because I think MindTap does represent an important innovation that addresses some of the trends that we’ve been blogging about here at e-Literate (which was one of the reasons that I was enticed to work on MindTap at Cengage for a while).

    MindTap is not a “personalized learning solution.” While it does allow students to do things like integrate their Evernote accounts and choose whether they want to read or listen to texts, the level of personalization for the learners is not terribly different from other products on the market. (And it certainly is nowhere near as radical as the vision for a Personalized Learning Environment which came from the UK’s JISC and elsewhere, and from which terms like “personalized learning solution” and “personalized learning experience” have been bastardized). Nor are there adaptive analytics or other sorts of machine-driven personalization in the product at this time. Rather, the key differentiator in the current incarnation of MindTap is the way in which it creates a more refined and complete learning experience out of the box while still enabling faculty to customize those experiences to the needs of their students in pretty significant and, in some cases, new ways. This is exactly where the textbook, LMS, and MOOC markets are all headed, and MindTap got there first.

    The Problem to be Solved

    In order to understand the value of a product like MindTap, it’s important to understand where textbook publishers do and do not compete. You’re not going to see a lot of MindTap-style products for courses like “Advanced Topics in International Trade Policy,” “Research in Genetics,” “Greek Film,” or “Intermediate Killer Shark Genre.” These smaller courses are relatively uninteresting to textbook publishers because they don’t have the scale necessary to generate significant revenues, and they are also better suited to hand-crafted course designs that are tailored to the strengths of the particular professor doing the teaching and can be highly tailored to the needs and interests of the students in the class. Rather, the courses in question are more like “Introduction to Psychology,” “General Biology I,” “Microeconomics,” or “Survey of Western Civilization.” (English Composition is an anomaly in this categorization because of the way it is taught.) These courses are generally taught in large lecture halls with little or no writing—and when there is writing, it is often graded quickly on a narrow range of criteria by overworked graduate students—and relatively generic syllabi (particularly in non-elite institutions).

    A lot of the heated debate over whether college is “broken” revolves around these sorts of classes without ever explicitly defining the scope of the problem. Those who say school is broken and need to be disrupted tend to argue as if all college courses are giant, boring lecture courses. Those who argue against the “school is broken” meme tend to characterize these large lecture-centric courses as exceptions. Neither characterization is entirely accurate. On one hand, there are huge swaths of courses in just about any college catalog that are not large lecture courses. On the other hand, because the large lecture courses are concentrated in core curriculum and core major classes, most students have to take a handful of these courses in order to graduate.

    Regardless of how pervasive or rare you think these courses are, everybody seems to agree that they are not terribly effective. But what should be done about the problem? Shrinking the class size is simply not going to happen, given both budget realities and the moral imperative to increase access to education. And yet, the current situation is bad not only for the students but also for the instructors. Keep in mind that the people teaching these survey courses are disproportionately either junior faculty who are doing all kinds of other duties to earn tenure or adjuncts who are working unreasonable course loads just to make ends meet. They generally don’t have a lot of time to either carefully craft a course or give students a lot of (or any) individual attention. They often have little choice but to take what the publisher is giving them as their course outline and run with it. In and of itself, the direct adoption of a publisher’s curriculum isn’t necessarily bad for many of these courses. The whole idea of a core course is that it helps all students getting a particular degree or a particular major to master certain competencies that they should have. There is a strong argument for consistency of curriculum across core courses. But the current situation neither guarantees consistency of curriculum nor saves the instructor time for either thoughtful customization of the curriculum or any other purpose. There is still a lot of hand assembly required to pull together reading assignments, assessments, slides and lecture notes, and so on. It is generally not a creative process because there is little time for creativity, but it is nevertheless a labor-intensive process and one that is prone to introduce variation in hitting those core competencies without any checks or even necessarily a lot of reflection on it.

    A Better Compromise

    If instructors are going to adopt a third-party course curriculum anyway, then we should at least use technology to remove the hand assembly. Why not provide the readings, multimedia, assignments and assessments, neatly integrated with a basic syllabus, into one ready-to-use digital package for the students? At its most basic, this is what “courseware” is and what MindTap does. It provides students and instructors with a ready-to-go complete course structure with all the materials and assessments placed in a logical and easily navigable order. Joel Spolsky once defined poor user interface design as forcing users to make choices that they don’t care about. That is also an apt description for 80% of the pre-semester course preparation process that instructors go through with these big survey courses. Pre-assembling the elements of the vanilla version of the course frees up the instructors’ time to focus on the customizations that they actually do care about. To begin with, the course structure is already assembled and visible, which makes it easier for the instructor to think about its total shape. Removing unwanted content or changing content order is trivially easy, making the roughing in of the course structure very quick.

    But things get really interesting when you start looking at adding to the learning path structure in MindTap rather than just moving or deleting things. In ed tech discussions, we tend to talk about APIs as if the main differentiation is having them versus not having them. Can you or can you not integrate Google Docs into a course? But in reality, the specifics of the integration can make an enormous difference in how practically useful the added functionality is to teachers and students. Do you want to make a folder of your documents (like your syllabus) available to the students at all times in the course with one or two clicks, or do you want to insert your own supplemental document right into the course reading, zero clicks away for the student and on their default navigation path? These two types of integration serve fundamentally different purposes in the course. In MindTap, you can do both and more. And importantly, making these different customizations is intuitive and almost trivially easy. Radical customization of the course structure is very much possible. But both because there is far less instructor time wasted with hand assembly of course elements and because customizations are visible and visualizable in the learning path structure, the percentage of time spent on meaningful instructional activities, whether that’s course customization or student interaction, is likely to be higher. For this reason, the MindApp model and the learning path structure are MindTap’s crown jewels.

    Table Stakes

    Of course, MindTap doesn’t have a monopoly on useful courseware platform design. For example, WileyPLUS enables instructors to see which course materials and assessments are associated with which learning objectives. This helps instructors to align what they’re teaching and assessing on to what they think the student should be learning. More importantly, none of these innovations from any of the platforms are going to magically change poor large lecture classes into great educational experiences. The key to solving that problem is not the technology by itself but the learning design that it enables. The classroom flipping craze is a craze precisely because it is a learning design that can improve the pedagogical impact of these large survey classes. But anyone who has actually tried to flip their class will tell you that it’s not easy to do well. Faculty need pedagogical models other than the ones that they learned from their own professors, including the practical tips and support necessary to make those models work in the real world. They need course designs based on learning science and collected experience of innovators, and supported by technology. The MindTap platform doesn’t provide that. No technology platform does. And as far as I can tell, Cengage is not yet designing courseware for MindTap that even attempts to do this. But in order to accomplish the bigger goal, we first need to strike a new balance regarding course design customization. It’s not a question of “more” versus “less.” There will always be times when it is wise to allow a skilled instructor to tune a course. But there needs to be more of a sophisticated collaboration between the individual instructor, a curriculum design team (whether that team works for a textbook publisher or a university), and the other instructors teaching the course at the same institution in order to arrive at better pedagogical approaches that can be adopted and adapted to best effect by individual teachers. In order to accomplish that, you need to start with a combination of platform and content that makes meaningless course assembly unnecessary and meaningful course customization both easy and visible. This is what we mean at e-Literate when we write about “courseware.” And at the moment, MindTap is the best example I know of what a next-generation courseware platform will look like.

  • Knewton (Quietly) Pivots

    Knewton CEO Jose Ferriera has an interesting and revealing blog post up about “the coming adaptive world.” In part, it is a response to a report on adaptive learning by Education Growth Advisors. Jose writes, “Despite our constant protestations to the contrary, observers often confuse Knewton with the many adaptive learning app makers who are now popping up. Or they confuse app makers with platforms. Or they think we’re all competitors.” It’s a bit of a red herring, since the report does distinguish between platform and publisher business models. That said, the meaning of the distinction between these two categories isn’t drawn terribly clearly, and it’s fair for Knewton to try to clarify its market positioning. But in doing so, Jose reveals what appears to be a shift in their thinking about the market for a platform like theirs which tells us something important about the ed tech market in general. (more…)

  • We’re from the Valley and We’re Here to Help

    The other week I had the pleasure of attending the annual GSV Advisors Education Innovation Summit in Scottsdale. For those who aren’t aware, the main purpose of the event is to help ed tech startups and investors find each other. After last year’s summit, I wrote a post called “What Are Ed Tech Entrepreneurs Good For?“, the main lessons of which could equally apply to this year:

    • The main stage speakers generally tilted to the right, ideologically (although there was a visible effort to achieve more balance this year). But by and large, that didn’t matter, since the important work of the conference was generally driven by what ed tech startups were available for funding.
    • Many of the ed tech entrepreneurs have good intentions but varying degrees of knowledge about the theory and pragmatics of education.
    • The degree to which ed tech entrepreneurs need that knowledge varies widely depending on the specifics of what problems they are trying to solve with their offerings.
    • The success or failure of these startups are often heavily influenced by the market conditions, which means that we should be thinking about things like improving institutional purchasing practices if we want more from our vendorsThe main difference this year was that the conference was roughly twice the size of last year’s.

    I’ll have more to say about the dynamism and/or frothiness of the ed tech startup market in a future post. For now, I want to focus on that continuing disconnect between what happens on the main stage of the conference and what happens in the rest of it, because I think there is a lost opportunity. (more…)

  • MOOCs, Courseware, and the Course as an Artifact

    As Phil mentioned in his last post, he and I had the privilege of participating in a two-day ELI webinar on MOOCs. A majority of the speakers had been involved in implementing MOOCs at their institutions in one way or another. And an interesting thing happened. Over the course of the two days, almost none of the presenters—with the exception of the ACE representative, who has a vested interest—expressed the belief that MOOCs provide equivalent learning experiences to traditional college courses. Keep in mind, these folks were believers. They were enthusiastic about MOOCs in general. But they tended to describe the value of MOOCs as reaching a different audience than the traditional matriculated college student and provide a different value. They talked about it extending the university mission. By and large, they did not talk about it as being an improvement on, or even equal to, a traditional class. Now, there were well over 400 participants, so it wouldn’t be fair of me to say that there was unanimity, about this point or any other. But the level of agreement was remarkable.

    On the other hand, there was widespread enthusiasm for using MOOCs as essentially substitutions for textbooks in classes that included instructors from the local campus. Vanderbilt created what they called a course “wrapper” around a Coursera MOOC on machine learning. Folks from Stanford talked about the notion of a “distributed flip,” i.e., a group of flipped classrooms participating together in a MOOC. And SJSU talked about using an edX course in a blended course environment on one hand, and a Udacity course with Udacity-provided “course mentors” on the other.

    The obvious conclusion is that MOOCs are more of a threat to textbook companies than they are to universities. I think that’s true, but I also think it’s an oversimplification. There is a deeper (and older) trend to boil down a course into a set of digital artifacts that can be “played” by the student at will. It’s worth taking a deeper look at that trend, where it’s going, what’s useful about it, and what’s pernicious about it. (more…)

  • Please Welcome Featured Blogger Elijah Mayfield

    When the story first broke a while back about the Kaggle contest for robo-grading essays that could be “similar to” human graders, I got interested. So after doing a little reading, I ended up contacting a guy by the name of Elijah Mayfield, a PhD student at Carnegie Mellon University and one of the winners of the contest. The net result of our conversation is that I ended up writing a blog post called “What Is Machine Learning Good For?” Fast-forward a bit. Elijah now has a start-up called LightSIDE Labs based on the same technology, and The New York Times is writing puff pieces on how edX is going to change the world with this technology. In the meantime, I have been talking to Elijah for a while about getting him to write at e-Literate.

    I’m happy to say that Elijah will be doing a series of posts for us on machine learning in education, starting today. Please welcome him.

  • Please Welcome Guest Blogger Bill Jerome

    I’m pleased to announce that Bill Jerome, the Associate Director of User Experience at OLI, will be writing some guest post on educational data analytics and related topics. This is an area where there is a lot of industry hype and not a lot of understanding right now. I’m really pleased to have an expert like Bill here to help us gain some insight.

  • Blackboard’s New Early Warning Analytics Product

    A couple of weeks ago in my post about the different types of learning analytics, I described retention early warning systems thusly:

    Most people don’t think about early warning systems as being in the same category as adaptive analytics, but if you consider that “adaptive” really just means “adjusting to your personal needs,” then a system like Purdue’s Course Signals is, in fact, adaptive. It sees when a student is in danger of failing or dropping out and sends increasingly urgent and specific suggestions to that student. It does that without “knowing” anything about the content that the student is learning. Rather, it’s looking at things like recency of course login (Are you showing up for class?), discussion board posts (Are you participating in class?), on-time assignment delivery (Are you turning in your work?), and grade book scores (Is your work passing?), as well as longitudinal information that might indicate whether a student is at-risk coming into the class. What Purdue has found is that such a system can teach students metacognitive awareness of their progress and productive help-seeking behavior. It won’t help them learn the content better, but it will help them develop better learning skills.

    Well, last week, Ray Henderson announced Blackboard’s new Retention Center and described it as follows:

    The Retention Center gives critical insight on learning and activity gaps to instructors, within the LMS, that helps them quickly diagnose students that are falling behind. Pre-configured and automatic so they don’t have to hunt for it. No set-up: it automatically calls out students that are at risk while instructors still have time and space to do something about it. With the feature instructors can see:

    • Who’s logging in: this is a simple but powerful predictor of student success. Instructors see how long it’s been since students have logged in to the course and how many have been away for five days or more. And not by fishing through student profiles or reports but in an automatic view complete with red flags where they’re needed.
    • Whether they’re engaged: which students have had low levels of course activity, at 20 percent or below the average in the last week.
    • Whose grades are suffering: which students are currently trending at 25 percent or more below the course average so they can target extra help to where it’s most needed – even when it isn’t asked for.
    • Who has missed deadlines: instructors might know this anecdotally or on a case-by-case basis, but now they can get a real-time view of all students that have missed one or more deadline.

    Eerily similar, no? A number of years back, when I pressed Course Signals inventor John Campbell on which factors in the LMS are most highly predictive of student success across different courses, he named exactly these four. The only surprise here is that this isn’t a common analytics feature of every LMS and courseware platform on the market yet. Purdue proved that their value in helping at-risk students is high. I’m glad Blackboard is stepping up.

    The one piece that’s missing is a simple standard where an SIS or other longitudinal data system could pass an at-risk “credit score” to the early warning system to modify its sensitivity. If a student on the honor roll drops off the radar for a week, it’s less of a cause for concern that a student on academic probation (for example). I tried to push this idea for a standard at the IMS a few years back but got nowhere with it at the time. I hope that Blackboard will push for something like it now that they have a system to take the data.