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Direct linkOuyang, Fan; Wu, Mian; Zheng, Luyi; Zhang, Liyin; Jiao, Pengcheng – International Journal of Educational Technology in Higher Education, 2023
As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…
Descriptors: Technology Integration, Artificial Intelligence, Performance, Prediction
Xu, Zhuojia; Yuan, Hua; Liu, Qishan – IEEE Transactions on Education, 2021
Contribution: This article explored blended learning by implementing a student-centered teaching method based on the flipped classroom and small private online course (SPOC). The impact of general online learning behavior on student performance was analyzed. This work is practical and provides enlightenment for learning analysis and individualized…
Descriptors: Academic Achievement, Blended Learning, Prediction, Performance Factors
Devlin, Maura; Bushey, Heather – Change: The Magazine of Higher Learning, 2019
With national graduation rates that range from 32% among open enrollment institutions to 66% among private not-for-profits, higher education institutions have a moral imperative to improve the success of their students. Interventions to support today's students must consider the student holistically, be just-in-time, and come from a…
Descriptors: Data Use, Academic Achievement, Outcomes of Education, Holistic Approach
