User Modeling and Adaptive Support for MOOCSUser Modeling and Adaptive Support for MOOCS

Massive open on-Line courses (MOOCS) have great potential to innovate education, but suffer from one key limitation typical of many on-line learning environments: lack of personalization. Intelligent Tutoring Systems (ITS) is a field that leverages Artificial Intelligence and Machine Learning to devise educational tools that can provide instruction tailored to the needs of individual learners, as good teachers do. In this project, Drs. Conati and Roll aim to apply some of the concepts and technique from ITS research to MOOCS. Specifically, in previous work they have developed a framework to: i) discover from data, students behaviors that can be detrimental for or conducive to learning with specific educational software; ii) use these behaviors to build classifiers that can detect ineffective learners in real time and provide personalized support accordingly. They have already successfully applied this framework to two different on-line educational tools, and now plan to extend it to make existing MOOCS more reactive to specific student needs.