A Declarative Approach for an Adaptive Framework for Learning in Online Courses

Online courses have gained popularity and seen a surge in enrollment with a reported 58 million students. Adaptive learning is an educational method that is applicable to online courses. Computers adapt the presentation of educational material according to students' learning needs. One of the major challenges with existing systems is that learners are not able to keep up with the instructions in the course that leads to a very low course completion rate. Personalization of the course materials based on the needs of a student is of great value. We propose an adaptive framework for learning that groups students and charts a course plan with the end goal of helping the learner complete all topics in the course. The system also provides feedback about the learner's strong and weak topics with a view to help them learn better. We present a declarative approach that is quite different from existing approaches and provides the user flexibility to specify the constraints and actions as well as consequence of each action instead of having the user encode how to find the solution.