ERIC Number: ED649065
Record Type: Non-Journal
Publication Date: 2024
Pages: 81
Abstractor: As Provided
ISBN: 979-8-3817-4500-9
ISSN: N/A
EISSN: N/A
Early Identification of Students at Academic Risk Based on Learning Management System Log Data
Roger Sheng So
ProQuest LLC, Ed.D. Dissertation, St. John's University (New York)
Understanding student engagement with the institution from the first day of classes to the end of the semester would help inform the institution of the potential risk that a student will drop out of a class or of the school. Learning Management Systems (LMS) record student interactions with the system and might be able to be used to identify students who are at academic risk. The scope of this study is to retrospectively analyze first-year student activity for the Spring 2022 semester for early warning signs worthy of intervention. A student risk assessment will be determined by reviewing student LMS activity, compared with peers, during the semester. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]
Descriptors: Learning Management Systems, Data Use, At Risk Students, Learner Engagement, Interaction, Identification, Academic Achievement, College Freshmen, Dropout Prevention, Intervention
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A