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Andrea Zanellati; Stefano Pio Zingaro; Maurizio Gabbrielli – IEEE Transactions on Learning Technologies, 2024
Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…
Descriptors: Dropouts, Dropout Characteristics, Potential Dropouts, Artificial Intelligence
Holly N. Johnson; Ya-yu Lo; Morgan E. Nichols – Educational Research and Development Journal, 2024
Promoting a high level of student engagement has been a goal for many teachers. Opportunities to respond (OTR) offer a low-cost instructional practice that allows teachers to improve student engagement in the classroom. In this study, we explored the potential effects of a data-driven coaching model on one elementary school teacher's…
Descriptors: Data Use, Decision Making, Coaching (Performance), Learner Engagement

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