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Ouyang, 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
Dipace, Anna; Loperfido, F. Feldia; Scarinci, Alessia – Research on Education and Media, 2018
This article describes Learning Analytics (LA) as a predictive and formative approach that enables the planning of educational scenarios in line with students' needs and languages in order to set a priori and in progress systems of control and inspection of the following: consistency, relevance and effectiveness of training objectives, curriculum…
Descriptors: Learning Analytics, Individualized Instruction, Curriculum Design, Student Centered Learning

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