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Md Akib Zabed Khan; Agoritsa Polyzou – Journal of Educational Data Mining, 2024
In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…
Descriptors: Academic Advising, Courses, Data Use, Artificial Intelligence
WenHua Cui; Yiming Fang; Yan Ma – International Journal of Web-Based Learning and Teaching Technologies, 2024
A framework was proposed to identify the at-risk factors of college courses in blended mode, offering suggestions for continuous improvement. An indicator system concerning teaching quality characteristics was constructed based on context, input, process, and product (CIPP) model. Subsequently, the group Analytic Hierarchy Process (AHP) algorithm…
Descriptors: Higher Education, Blended Learning, Risk Assessment, Risk
David Van Nguyen; Shayan Doroudi; Daniel A. Epstein – Community College Journal of Research and Practice, 2025
Our preliminary experiment examined a potential pain point with ASSIST, California's database of articulation agreements. That pain point is cross-referencing multiple articulation agreements to manually develop an "optimal" academic plan. Optimal is defined as the minimal set of community college courses that satisfy all transfer…
Descriptors: Articulation (Education), Human Factors Engineering, Algorithms, Educational Planning

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