Adaptive Learning at a Small Liberal Arts College: Failure to Launch

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Adaptive learning platforms are the next evolution of online courseware that promises learners a tailored and individualized learning experience. Adaptive learning is not necessarily new: It has been around for some time, often developed around a specific text or course and often by textbook publishers. As a result, the adaptive learning materials offer learners an individualized experience, but confine teachers to a standardized teaching experience.

Developed over the last several years, new adaptive learning platforms allow instructors to author their own adaptive materials. On platforms like Smart Sparrow, instructors have the ability to author both the content presented to the learners and the adaptivity built into the delivery. This flexibility presents an exceptional opportunity for personalized learning and led me to identify Smart Sparrow as a platform that might be useful to the faculty at Grinnell College. As a digital liberal arts specialist one of my responsibilities is to identify emerging technologies that offer potential benefits for teaching and learning and to partner with faculty to explore their use.

I decided to seek a faculty partner who would be interested in piloting the use of adaptive materials in their course. I fired off a scattershot of e-mails to around two dozen faculty, people who I knew had already developed or were interested in developing online materials to hybridize their face-to-face classes. I offered a brief explanation of adaptive learning and Smart Sparrow and invited them to try it in an upcoming course.

Failure to Launch

In the end no materials were developed, and the platform has not been used in any of their courses. Why? Well, there are a number of contributing factors, some of which are all too familiar. Response from the faculty I contacted was lukewarm, but a few faculty did express interest. In almost every case, this expression of interest was accompanied by an opposing concern about how much time would be required to develop adaptive materials. While I tried to allay their concerns by reassuring them that I would be available to assist with the implementation of any design they came up with, their concerns were not unfounded. Customization is often costly, particularly in terms of time — a scarce resource among faculty.

The basic feature of adaptive learning is that the platform can adjust what is presented to the learner based on their input or performance. The platform self-directs students to the content they need to make progress.1 This is accomplished by introducing a number of conditional statements throughout the content delivery, sometimes referred to as trap points, where, given certain conditions, a specified action is taken. Instructor-authored platforms allow instructors to build the content to be delivered and make decisions about what conditions will be checked and what actions will be taken. They offer unequaled customizability, giving the instructor a blank canvas and all the tools to author a perfectly tailored and effective instructional module. The challenge is that it often takes a substantial amount of time, effort, and training to turn a blank canvas into something beautiful.

Face-to-Face vs. Computer-Mediated Instruction

Keeping in mind that adaptive learning is computer-mediated, situate that blank canvas on a small liberal arts college campus where nearly all classes are conducted face-to-face. Close, personal interaction with students is highly valued. The online or computer-mediated instruction that occurs is in place to maximize and extract every last ounce of value from the face-to-face class time. At my institution, face-to-face is central and will remain so for the foreseeable future. Everything computer-mediated is de facto decentered. This decentering influences the evaluation of effort vs. payoff and is a dampener on the impact that a new computer-mediated platform can have.

The impact of adaptive learning is further dampened when it is used for standalone or discrete modules rather than as the delivery for a full course. The advantage of adaptive learning is being able to redirect learners to the most appropriate pieces of content. When the scope is narrowed and there are fewer pieces of content, the ability to redirect learners has less effect.

While instructor-authored adaptive learning platforms offer great potential, when used to create small modules to support face-to-face learning, their advantages are minimized and the effort to create something from nothing is amplified.

Unfulfilled Potential

In thinking through the potential applications of this tool, I identified a few specific areas where it might be applied to good effect in our environment. One would have involved creating virtual lab activities that would enable students to complete lab exercises without the need for animal testing. This application didn’t get off the ground, I believe, because of the limited scope and the fact that we already have an LMS that can accommodate this need (albeit not as elegantly). While Grinnell doesn’t offer any fully online courses, we do have courses that could be described as flipped. In these courses a significant portion of the course content is delivered online and may well benefit from being delivered on an adaptive learning platform. There is also potential for a limited number of primarily online courses in our less commonly taught languages program and in cases of interinstitutional collaboration. In these instances, the ability to create self-paced materials might be a strong selling point, especially for collaborations where calendars don’t align perfectly. But until those opportunities come about, I don’t expect adaptive learning to have much of an impact on the learning technologies landscape at our institution.


  1. Tyton Partners, Learning to Adapt: Understanding the Adaptive Learning Supplier Landscape, April 15, 2013.

Mike Conner is a digital liberal arts specialist at Grinnell College.

© 2016 Michael S. Conner. The text of this EDUCAUSE Review blog is licensed under the Creative Commons BY-NC-ND 4.0 license.