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.]
Descriptors: Attendance Patterns, Peer Influence, Online Courses, Blended Learning, College Students, Student Interests, Student Motivation, Correlation, Grades (Scholastic), Grade Point Average, Conventional Instruction, Student Behavior, Foreign Countries, Courses
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