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Julius Moritz Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Journal of Computer Assisted Learning, 2024
Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can…
Descriptors: Video Technology, Models, Cues, Problem Solving
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Slof, Bert; van Leeuwen, Anouschka; Janssen, Jeroen; Kirschner, Paul A. – Journal of Computer Assisted Learning, 2021
In computer-supported collaborative learning research, studies examining the combined effects of individual level, group level and within-group differences level measures on individual achievement are scarce. The current study addressed this by examining whether individual, group and within-group differences regarding engagement and prior…
Descriptors: Cooperative Learning, Prior Learning, Secondary School Students, Academic Achievement
Richter, Juliane; Lachner, Andreas; Jacob, Leonie; Bilgenroth, Friederike; Scheiter, Katharina – Journal of Computer Assisted Learning, 2022
Background: Engaging students in computer-assisted guided inquiry learning has great potential to scaffold their scientific understanding: Students are expected to improve their scientific problem-solving skills, and at the same time gain a deep conceptual understanding of the subject-matter. Additional generative activities such as creating video…
Descriptors: Self Concept, Problem Solving, Video Technology, Computer Assisted Instruction
Gyllen, J.; Stahovich, T.; Mayer, R. – Journal of Computer Assisted Learning, 2018
Time on task has been recognized as an important variable in academic learning, but self-report measures of study time are problematic. Therefore, this study employs an automated system for recording time spent reading a course textbook. College students in an introductory engineering course accessed their textbook online. The book contained pages…
Descriptors: Undergraduate Students, Engineering Education, Electronic Learning, Electronic Publishing
Hooshyar, D.; Ahmad, R. B.; Yousefi, M.; Yusop, F. D.; Horng, S.-J. – Journal of Computer Assisted Learning, 2015
Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem-solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one-to-one personalized and…
Descriptors: Flow Charts, Intelligent Tutoring Systems, Educational Technology, Teaching Methods