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Kam Hong Shum; Samuel Kai Wah Chu; Cheuk Yu Yeung – Interactive Learning Environments, 2023
This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…
Descriptors: Student Behavior, Online Courses, Cooperative Learning, Computer Software
Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Poole, Frederick J.; Clarke-Midura, Jody – Language Learning & Technology, 2023
Research involving digital games and language learning is rapidly growing. One advantage of using digital games to support language learning is the ability to collect data on students learning in real time. In this study, we use educational data mining methods to explore the relationship between in-game data and elementary students' Chinese…
Descriptors: Computer Games, Second Language Learning, Second Language Instruction, Data Analysis

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