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ERIC Number: ED615493
Record Type: Non-Journal
Publication Date: 2021
Pages: 7
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Assessing Attendance by Peer Information
Deng, Pan; Zhou, Jianjun; Lyu, Jing; Zhao, Zitong
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (14th, Online, Jun 29-Jul 2, 2021)
Attendance rate is an important indicator of students' study motivation, behavior and Psychological status; however, the heterogeneous nature of student attendance rates due to the course registration difference or the online/offline difference in a blended learning environment makes it challenging to compare attendance rates. In this paper, we propose a novel method called Relative Attendance Index (RAI) to measure attendance rates, which reflects students' efforts on attending courses. While traditional attendance focuses on the record of a single person or course, relative attendance emphasizes peer attendance information of relevant individuals or courses, making the comparisons of attendance more justified. Experimental results on real-life data show that RAI can indeed better reflect student engagement. [For the full proceedings, see ED615472.]
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: https://educationaldatamining.org/conferences/
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: China
Grant or Contract Numbers: N/A