Adaptive Learning
Karun Thankachan · 2017 International Conference on Inventive Computing and Informatics (ICICI) · 2017
This paper discusses the design for an intelligent and adaptive tutoring system offering pedagogical support that deviates from the traditional chalk and talk form of teaching for online courses. The design proposed utilizes the information in the MOOC database with user-system interaction logs to create a model which enables the system to adapt according to user needs. There also exists room for manual intervention by the course administrators in case of at-risk participants. Educational data mining and learning analytics techniques have been applied to pinpoint the best instructional methods and pedagogical support for each student over time. The design proposed allows the system to personalize the learning experience and supports the instructor in administering the course to a huge number of participants.