Towards Reduction in MOOCs Dropouts: An Agent-Based Model for Social Network Based Collaborative Learning
- Resource Type
- Conference
- Authors
- Prakash, Lakshmi Sunil; Zia, Kashif; Khalil, Ismail
- Source
- 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2019 10th IEEE International Conference on. 2:814-819 Sep, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
collaborative learning
MOOCs
dropouts
social networks dynamics
Agent Based Modelling
- Language
Universities, hosting Massive Open Online Courses (MOOC) are facing a major challenge of immature dropout of a student. Major research considerations to address this challenge are only able to, identify a student at the verge of a dropout using learning and learner analytics based on different sources of data (MOOCs data, social networking data). There is no significant research done on how to avert this particular state of the learner. An agent-based model is proposed to recreate different scenarios of learners' interactions and social network evolution. The purpose of this study is to identify important phenomena and structures of social networking using a simulated MOOC setting so that the social network interaction can be channeled to avert the possibility of dropout.