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Jennifer Kahn; Shiyan Jiang – Information and Learning Sciences, 2024
Purpose: While designing personally meaningful activities with data technologies can support the development of data literacies, this paper aims to focuses on the overlooked aspect of how learners navigate tensions between personal experiences and data trends. Design/methodology/approach: The authors report on an analysis of three student cases…
Descriptors: Visual Aids, Trend Analysis, Data Science, Secondary School Students
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Cui, 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