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Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
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Iva Božovic – Journal of Political Science Education, 2024
This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…
Descriptors: Data Use, Teaching Methods, Data, Information Literacy
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Duschl, Richard; Avraamidou, Lucy; Azevedo, Nathália Helena – Science & Education, 2021
Grounded within current reform recommendations and built upon Giere's views (1986, 1999) on model-based science, we propose an alternative approach to science education which we refer to as the "Evidence-Explanation (EE) Continuum." The approach addresses conceptual, epistemological, and social domains of knowledge, and places emphasis…
Descriptors: Science Education, Epistemology, Data, Observation
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Radinsky, Josh; Tabak, Iris – British Journal of Educational Technology, 2022
How do people reason with data to make sense of the world? What implications might everyday practices hold for data literacy education? We leverage the unique context of the COVID-19 pandemic to shed light on these questions. COVID-19 has engendered a complex, multimodal ecology of information resources, with which people engage in high-stakes…
Descriptors: Information Literacy, Data, COVID-19, Pandemics
Luke Keele; Matthew Lenard; Lindsay Page – Annenberg Institute for School Reform at Brown University, 2021
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Cluster Grouping, Educational Environment, Outcomes of Treatment, Compliance (Psychology)
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Ann Marie Cotman; F. Chris Curran; Katharine Harris-Walls – Education Policy Analysis Archives, 2024
Choices made on data visualizations guide how users make meaning of the information presented. This research investigates design decisions made on 115 state-level dashboards reporting school safety data. Using pre-determined codes drawn from a framework of visualization rhetoric, dashboard characteristics were described and analyzed. Analysis…
Descriptors: School Safety, Data, Visual Aids, State Agencies