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Direct linkAbdullahi 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
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
Download full textMangaroska, 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
Uysal, Murat Pasa – Turkish Online Journal of Distance Education, 2013
Teaching object-oriented programming (OOP) is a difficult task, especially to the beginners. First-time learners also find it difficult to understand. Although there is a considerable amount of study on the cognitive dimension, a few study points out its physiological meaning. Moreover, it has been suggested that neuroscientific studies and…
Descriptors: Cognitive Measurement, Cognitive Processes, Difficulty Level, Programming
Bartocci, Ezio; Singh, Rupinder; von Stein, Frederick B.; Amedome, Avessie; Caceres, Alan Joseph J.; Castillo, Juan; Closser, Evan; Deards, Gabriel; Goltsev, Andriy; Ines, Roumwelle Sta.; Isbilir, Cem; Marc, Joan K.; Moore, Diquan; Pardi, Dana; Sadhu, Sandeep; Sanchez, Samuel; Sharma, Pooja; Singh, Anoopa; Rogers, Joshua; Wolinetz, Aron; Grosso-Applewhite, Terri; Zhao, Kai; Filipski, Andrew B.; Gilmour, Robert F., Jr.; Grosu, Radu; Glimm, James; Smolka, Scott A.; Cherry, Elizabeth M.; Clarke, Edmund M.; Griffeth, Nancy; Fenton, Flavio H. – Advances in Physiology Education, 2011
As part of a 3-wk intersession workshop funded by a National Science Foundation Expeditions in Computing award, 15 undergraduate students from the City University of New York collaborated on a study aimed at characterizing the voltage dynamics and arrhythmogenic behavior of cardiac cells for a broad range of physiologically relevant conditions…
Descriptors: Undergraduate Students, Mathematical Models, Student Interests, Laboratories
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
