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Nancy Montes; Fernanda Luna – UNESCO International Institute for Educational Planning, 2024
This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…
Descriptors: Data Collection, Data Use, At Risk Students, Foreign Countries
Arnold, Pip; Pfannkuch, Maxine – set: Research Information for Teachers, 2020
Statistical investigations, a thread within the statistics strand of the mathematics and statistics learning area (Ministry of Education, 2007), are underpinned by the statistical enquiry cycle. As teachers introduce their students to the statistical enquiry cycle, they are supporting their students to become data detectives, posing and answering…
Descriptors: Novices, Statistics, Active Learning, Inquiry
Yang, Zongkai; Yang, Juan; Rice, Kerry; Hung, Jui-Long; Du, Xu – IEEE Transactions on Learning Technologies, 2020
This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify…
Descriptors: Distance Education, At Risk Students, Artificial Intelligence, Man Machine Systems
Amanda Katherine Riske – ProQuest LLC, 2022
This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…
Descriptors: Teaching Methods, Data Use, Decision Making, Educational Practices
Piety, Philip J. – Review of Research in Education, 2019
This chapter reviews actionable data use--both as an umbrella term and as a specific concept--developed in three different traditions that data/information can inform and guide P-20 educational practice toward better outcomes. The literatures reviewed are known as data-driven decision making (DDDM), education data mining (EDM), and learning…
Descriptors: Educational Practices, Data Use, Outcomes of Education, Learning Analytics

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