Abstract
Using videos as a learning resource has received a lot of attention as an effective learning tool. Knowledge Tracing is intended to track students’ knowledge acquisition when they answer a serie of problems. In this paper, we describe an experiment to model students’ knowledge acquisition in educational video courses. For this purpose, Deep Knowledge tracing is used to classify and predict learners’ performance as they interact with an educational video course in the subject of ”C programming language”. Learners’ responses in previous quizzes were analyzed in order to forecast their next responses. The implementation of DKT in our dataset, led to an AUC (Area Under the Receiver Operating Characteristic Curve) of 0.73 which is a notable performance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
