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Abdullahi Yusuf; Amiru Yusuf Muhammad – Journal of Educational Computing Research, 2024
The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch…
Descriptors: Novices, Programming, Anxiety, Coding
Chun-Hsiung Tseng; Hao-Chiang Koong Lin; Andrew Chih-Wei Huang; Jia-Rou Lin – Cogent Education, 2023
This study explores the use of machine learning and physiological signals to enhance learning performance based on students' personality traits. Traditional personality assessment methods often yield unreliable responses, prompting the need for a novel approach utilizing objective data collection through physiological signals. Participants from a…
Descriptors: Artificial Intelligence, Personality Traits, Foreign Countries, Engineering Education
Hajar Darif; Mohammed Amine Lafraxo – Educational Process: International Journal, 2025
Background/purpose: The emergence of educational technologies has profoundly transformed teaching and learning methods in health sciences. This bibliometric study aims to identify the most widely used educational practices in this field between 2014 and 2024, exploring their applications within a constantly evolving technological context.…
Descriptors: Programming Languages, Bibliometrics, Research Reports, Educational Technology
Bertrand Schneider; Tonya Bryant – Cognition and Instruction, 2024
The goal of this paper is to bring new insights to the study of social learning processes by designing measures of collaboration using high-frequency sensor data. More specifically, we are interested in understanding the interplay between moments of collaboration and cooperation, which is an understudied area of research. We collected a multimodal…
Descriptors: Eye Movements, Socialization, Attention Control, Correlation
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michalis – Journal of Learning Analytics, 2020
Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…
Descriptors: Learning Analytics, Data Collection, Instructional Design, Learning Modalities
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis