Educational Technology

January 6, 2013

Students’ Online and Offline Social Networks Can Predict Course Grades

Filed under: Educational Technology — admin @ 12:30 am

by Science Daily

Ben-Gurion University of the Negev’s (BGU) Social Networks Security Research Group in its Department of Information Systems Engineering has developed a novel method to predict how well or badly a student will perform in an academic course. The information can be used to determine which students need the most help, as well as which ones excel and might be guided to further study or careers in that subject area. The paper, “Predicting Student Exam Scores by Analyzing Social Network Data,” was presented earlier this month at the Advanced Media Technology Conference in Macau, Hong Kong. The researchers analyzed data from a BGU course that included assignments submitted online and Web site logs (containing 10,759 entries) to construct social networks of explicit and implicit cooperation among the students. The implicit connections are used to model all the social interactions that happened “offline” among the students: e-mails with questions, conversations in the lab while preparing the assignments and even course forums.

http://www.sciencedaily.com/releases/2012/12/121227142957.htm

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