Facebook, the most popular social networking site, has recently been applied in a wide variety of fields for educational purposes. The social network site provides some social features such as communication methods, individual profiles, and personal posts that are shared with friends. Although learners can obtain lots of knowledge and improve their learning performance through discussions with friends in a social networking site, a learning group may not enhance learning performance in learning activities for specific courses. This study proposes an adaptive group composition system on Facebook to support adaptive group learning based on the background knowledge of individuals in a computer science project for college students. The system collects learner profile data automatically using Facebook and analyzes main course topics and professional abilities. This system utilizes an artificial bee colony algorithm to optimize group composing of students. Experimental results indicate that the proposed method improves the grouping process and enables students to achieve better performance.
All Science Journal Classification (ASJC) codes
- Numerical Analysis
- Computer Science Applications
- Computational Theory and Mathematics
- Applied Mathematics