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Direct linkJi-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Liu, Min; Li, Chenglu; Pan, Zilong; Pan, Xin – Interactive Learning Environments, 2023
More research is needed on how to best use analytics to support educational decisions and design effective learning environments. This study was to explore and mine the data captured by a digital educational game designed for middle school science to understand learners' behavioral patterns in using the game, and to use evidence-based findings to…
Descriptors: Computer Games, Educational Games, Instructional Design, Instructional Effectiveness
Hershkovitz, Arnon; Sitman, Raquel; Israel-Fishelson, Rotem; Eguíluz, Andoni; Garaizar, Pablo; Guenaga, Mariluz – Interactive Learning Environments, 2019
Many worldwide initiatives consider both creativity and computational thinking as crucial skills for future citizens, making them a priority for today's learners. We studied the associations between these two constructs among middle school students (N = 57), considering two types of creativity: a general creative thinking, and a specific…
Descriptors: Creativity, Creative Thinking, Computation, Computer Assisted Instruction
