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Direct linkCui, Ying; Chen, Fu; Shiri, Ali – Information and Learning Sciences, 2020
Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…
Descriptors: Foreign Countries, Identification, At Risk Students, Prediction
Cui, Ying; Guo, Qi; Leighton, Jacqueline P.; Chu, Man-Wai – International Journal of Testing, 2020
This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…
Descriptors: Inferences, Artificial Intelligence, Data Analysis, Computer Assisted Testing
