Research
Individualization
One of the major pain points in online learning today is the scale-efficacy tradeoff of learning. The best example of this is perhaps Massive Open Online Courses (MOOCs), which have showcased orders of magnitude larger student bodies than traditional classrooms but with completion rates that hover in the single digits. The problem is that in settings where the teacher to student ratios are so small, a one-size-fits-all (OSFA) course structure cannot effectively cater to the widespread learning desires and needs of the student body.
We believe that individualized learning – where the course content can be different for each student, adjusted based on her desires and needs – is the solution to this problem. To this end, we have designed a system that we call MIIC: the Mobile Integrated and Individualized Course. MIIC is a platform for personalized course delivery which integrates four modalities of learning – lecture videos, text, assessments, and social learning – into a single mobile app, and collects fine-granular behavioral measurements about each student as they interact with the course material. The current individualization framework in MIIC incorporates both assessment results and video-watching behavior for user modeling.
Recruiting a set of students from MOOC, we have carried out two user trials with MIIC, in which we made a number of interesting results. For example, we found that 70% of students preferred MIIC overall to a standard, OSFA presentation of the same material, and that those using MIIC had a higher level of engagement by an estimated 22% relative to the maximum of any student.
We are currently exploring a number of next steps on this in conjunction with the learning technology company Zoomi Inc (www.zoomiinc.com). In particular, we are deploying and capturing data from courses in professional training and private tutoring learning scenarios.
For more information, feel free to email Christopher Brinton at "cbrinton [at] princeton [dot] edu".