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Jufrida Jufrida; Wawan Kurniawan; M. Furqon; Khairul Anwar; Hebat Shidow Falah; Cicyn Riantoni – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: This study aims to explore the innovative integration of machine learning techniques into project-based learning rooted in Malay ethnoscience in Jambi, Indonesia. The research introduces a novel framework that utilizes educational data mining to personalize culturally responsive STEM education in under-resourced public schools.…
Descriptors: Physics, Science Instruction, Learning Analytics, Algorithms
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Harmer, Nicholas J.; Hill, Alison M. – Journal of Chemical Education, 2021
The COVID-19 pandemic necessitated the move to online teaching and assessment. This has created challenges in teaching laboratory skills and producing assessments that are robust and fair. Our solution was to use bespoke laboratory videos to provide laboratory training and to generate unique data sets for each student in coursework and exams. For…
Descriptors: Pandemics, COVID-19, Science Instruction, Teaching Methods
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Hong, Jeehye; Kim, Hyunjung; Hong, Hun-Gi – Asia-Pacific Science Education, 2022
This study explored science-related variables that have an impact on the prediction of science achievement groups by applying the educational data mining (EDM) method of the random forest analysis to extract factors associated with students categorized in three different achievement groups (high, moderate, and low) in the Korean data from the 2015…
Descriptors: Science Achievement, Prediction, Teaching Methods, Science Teachers