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Saleem Malik; K. Jothimani – Education and Information Technologies, 2024
Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…
Descriptors: Algorithms, Decision Making, At Risk Students, Learning Management Systems
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Prinsloo, Paul; Kaliisa, Rogers – Journal of Learning Analytics, 2022
While learning analytics (LA) has been highlighted as a field aiming to address systemic equity and quality issues within educational systems between and within regions, to date, its adoption is predominantly in the Global North. Since the Society for Learning Analytics Research (SoLAR) aspires to be international in reach and relevance, and to…
Descriptors: Learning Analytics, Equal Education, Educational Quality, Diversity
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Grimaldi, Phillip; Weatherholtz, Kodi; Hill, Kelli Millwood – International Educational Data Mining Society, 2022
As educational technology platforms become more and more commonplace in education, it is critical that these systems work well across a diverse range of student sub-groups. In this study, we estimated the effectiveness of MAP Accelerator; a large-scale, personalized, web-based, mathematics mastery learning platform. Our analysis placed a…
Descriptors: Educational Technology, Mastery Learning, Learning Management Systems, Middle School Students
US Department of Education, 2020
The U.S. Department of Education's (Department) mission is to promote student achievement and preparation for global competitiveness by fostering educational excellence and ensuring equal access. The Department pursues its mission by establishing policies and distributing corresponding funds, focusing national attention on key educational issues,…
Descriptors: Public Agencies, Institutional Mission, Academic Achievement, Educational Policy