Paper Info
Title
A Declarative Approach For An Adaptive Framework For Learning In Online Courses
Abstract
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.
Year
DOI
Venue
2019
10.1109/COMPSAC.2019.00039
2019 IEEE 43RD ANNUAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE (COMPSAC), VOL 1
Keywords
DocType
ISSN
Adaptive Learning, Answer Set Programming, Action Language, LPMLN
Conference
0730-3157
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Djananjay Pandit100.34
Ajay Bansal232027.21