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Jamal Kay B. Rogers; Tamara Cher R. Mercado; Ronald S. Decano – Journal of Education and Learning (EduLearn), 2025
Poor academic performance remains among the most concerning educational issues, especially in higher education and online learning. To address the concern, institutions like the University of Southeastern Philippines (USeP) leverage educational data mining (EDM) techniques to generate relevant information from learning management systems (LMS)…
Descriptors: Foreign Countries, Learning Management Systems, Academic Achievement, Data Analysis
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Hadis Anahideh; Nazanin Nezami; Abolfazl Asudeh – Grantee Submission, 2025
It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…
Descriptors: Correlation, Measurement Techniques, Guidelines, Semantics
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Seiyon M. Lee; Sami Baral; Hongming Chip Li; Li Cheng; Shan Zhang; Carly S. Thorp; Jennifer St. John; Tamisha Thompson; Neil Heffernan; Anthony F. Botelho – Journal of Educational Data Mining, 2025
Teachers often use open-ended questions to promote students' deeper understanding of the content. These questions are particularly useful in K-12 mathematics education, as they provide richer insights into students' problem-solving processes compared to closed-ended questions. However, they are also challenging to implement in educational…
Descriptors: Feedback (Response), Taxonomy, Data Analysis, Middle School Mathematics
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Paul A. Jewsbury; Matthew S. Johnson – Large-scale Assessments in Education, 2025
The standard methodology for many large-scale assessments in education involves regressing latent variables on numerous contextual variables to estimate proficiency distributions. To reduce the number of contextual variables used in the regression and improve estimation, we propose and evaluate principal component analysis on the covariance matrix…
Descriptors: Factor Analysis, Matrices, Regression (Statistics), Educational Assessment
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Steven Glazerman; Larissa Campuzano; Nancy Murray – Evaluation Review, 2025
Randomized experiments involving education interventions are typically implemented as cluster randomized trials, with schools serving as clusters. To design such a study, it is critical to understand the degree to which learning outcomes vary between versus within clusters (schools), specifically the intraclass correlation coefficient. It is also…
Descriptors: Educational Experiments, Foreign Countries, Educational Assessment, Research Design
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Pornpisut Duangngern; Wanwisa Wannapipat; Sanit Srikoon; Parama Kwangmuang – Educational Process: International Journal, 2025
Background/purpose: The ongoing digital transformation in education has identified important areas for development in pre-service teachers' preparation to facilitate critical and creative thinking within technology-enhanced learning environments. This study investigated the readiness and implementation of creative and critical thinking skills…
Descriptors: Critical Thinking, Creative Thinking, Preservice Teacher Education, Preservice Teachers
Joao M. Souto-Maior; Kenneth A. Shores; Rachel E. Fish – Annenberg Institute for School Reform at Brown University, 2025
Whether selection processes contribute to group-level disparities or merely reflect pre-existing inequalities is an important societal question. In the context of observational data, researchers, concerned about omitted-variable bias, assess selection-contributing inequality via a kitchen-sink approach, comparing selection outcomes of…
Descriptors: Control Groups, Predictor Variables, Correlation, Selection Criteria