MIT EECS — Keel Foundation Undergraduate Research and Innovation Scholar
Increasing Completion Rates of MOOCs
Isaac L. Chuang
Massive Open Online Course (MOOC) Platforms such as edX have the potential to provide immense value but is currently crippled by the low completion rates of its offered courses. In an effort to increase legitimacy of MOOCs – making them more desirable to complete – we will be collecting and analyzing data of student usage to detect signs of cheating. This not only can give us substantial information about what cheating might look like, but also who feels the need to cheat. In addition, we will be increasing the effectiveness of MOOCs to teach and give timely and effective feedback about what you have learned and what you need to review/learn by creating dynamic dependency tree based exams, representing student mastery not on a linear scale but a multidimensional scale.
I’m a senior majoring in Computational Biology and my passion for making quality education accessible and viable for all makes this project ideal for me. I have much experience working with students and adults in an educational setting, am concentrating in education and plan to work on MOOCs and other educational platforms in the future. I have taken MOOCs and have experience with algorithms and data analysis.