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Zong, Zheng; Schunn, Christian D. – International Journal of Computer-Supported Collaborative Learning, 2023
Online peer feedback has proven to be practically useful for instructors and to be useful for learning, especially for the feedback provider. Because students can vary widely in skill level, some research has explored matching reviewer and author by performance level. However, past research on the impacts of reviewer matching has found little…
Descriptors: Computer Mediated Communication, Feedback (Response), Peer Evaluation, Biology
Sonsoles Lopez-Pernas; Kamila Misiejuk; Rogers Kaliisa; Mohammed Saqr – IEEE Transactions on Learning Technologies, 2025
Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…
Descriptors: Students, Artificial Intelligence, Man Machine Systems, Interaction
Ilja Cornelisz; Chris van Klaveren – npj Science of Learning, 2022
Longitudinal randomized controlled trials generally assign individuals randomly to interventions at baseline and then evaluate how differential average treatment effects evolve over time. This study shows that longitudinal settings could benefit from "Recurrent Individual Treatment Assignment" ("RITA") instead, particularly in…
Descriptors: Longitudinal Studies, Randomized Controlled Trials, Intervention, Assignments
Ellie Lovellette; Dennis J. Bouvier; John Matta – ACM Transactions on Computing Education, 2024
In recent years, computing education researchers have investigated the impact of problem context on students' learning and programming performance. This work continues the investigation motivated, in part, by cognitive load theory and educational research in computer science and other disciplines. The results of this study could help inform…
Descriptors: Computer Science Education, Student Evaluation, Context Effect, Problem Solving
Imhof, Christof; Comsa, Ioan-Sorin; Hlosta, Martin; Parsaeifard, Behnam; Moser, Ivan; Bergamin, Per – IEEE Transactions on Learning Technologies, 2023
Procrastination, the irrational delay of tasks, is a common occurrence in online learning. Potential negative consequences include a higher risk of drop-outs, increased stress, and reduced mood. Due to the rise of learning management systems (LMS) and learning analytics (LA), indicators of such behavior can be detected, enabling predictions of…
Descriptors: Prediction, Time Management, Electronic Learning, Artificial Intelligence
David B. Nelson; Anaelle Emma Gackiere; Samantha Elizabeth LeGrand; Daniel A. Guberman – Thresholds in Education, 2025
In response to the significant disruption posed by emergent AI technology, we propose a four part framework for teaching and learning practice and development. Rather than focus on the specific technologies of the moment, this framework provides actionable suggestions for individuals with varying views of AI and its positive and negative…
Descriptors: Teaching Methods, Learning Processes, Algorithms, Artificial Intelligence
Oberman, Paul S. – JCSE Online, 2001
Describes an assignment for an introductory computer science class that requires the student to write a software program that simulates an automated teller machine. Highlights include an algorithm for the assignment; sample file contents; language features used; assignment variations; and discussion points. (LRW)
Descriptors: Algorithms, Assignments, Computer Science Education, Computer Simulation