Analytics and Adaptive Learning Paths

many paths by Meredith James, on Flickr
What class(es) should I take next? Which instructors am I likely to learn more from? Common questions that students face each semester. Every institution has formal and informal channels that get used, whether they are institution sanctioned academic advisors and student opinion surveys or back channel methods, like “underground” surveys, sites like ratemyprofessors and e-mail and casual conversation.

These approaches, however, are either suspect in their depth and accuracy (, surveys) or costly to scale (academic advisors). Two recent mergers, Desire to Learn’s acquisition of Degree Compass and IAC’s (OK Cupid and purchase of, bring interesting possibilities to this space, as the concept of adaptive learning is no longer strictly in the domain of content, but now extends to the instructor and course path that a learner takes as they pursue mastery.

Degree Compass (modeled after Netflix and Pandora) takes your existing transcript information, along with historical data and the transcripts of hundreds of your peers and predicts how well you’ll do in a course.  The developers claim that it is more than just a tool to aid grade inflation, as there are several data points that they use in their algorithm, and several recommendations made to the student, not just expected grade. D2L’s purchase will likely see the addition of this recommendation engine its your LMS. While fantastic at a large institution with substantial course offerings, I wonder how valuable this functionality is when the course offerings are smaller. As a student, I want not only the best statistics class that my institution offers, I want the best statistics class that caters to my strengths and weaknesses as a learner. With the rise of MOOCs, sites like Udemy and Skillshare and efforts of the Mozilla foundation to bring a unifying voice to  micro-credentialing (badges),  students have more learning opportunities, with different teachers, content and approaches, available to them than ever before. As demand grows for education that is designed for the individual learner, large institutions will have a tough time developing highly personalized content.  To this end, I find the IAC and Tutor combination a little more intriguing. Fewer details exist on IAC’s plans for Tutor, but the New York Times suggests that IAC will be bringing their analytics expertise to Tutor, perhaps to aid in instructor selection (identify my ideal instructor match based on my learning profile), perhaps to give tutors/instructors better diagnostic tools (how should I approach teaching this student?), perhaps even extending to a point of taking the learner profile and creating a personalized learning skill tree (What combination of experiences should I employ to allow me to reach a particular level of mastery or understanding?).

Both platforms and their acquisition suggest that adaptable learning paths, and not just content, through deep data analysis will be an interesting space to watch as educational technology continues to evolve. A world where every student has access to not only high quality learning, as the big MOOC players promise, but personalized high quality learning.

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