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Joshua Weidlich; Aron Fink; Ioana Jivet; Jane Yau; Tornike Giorgashvili; Hendrik Drachsler; Andreas Frey – Journal of Computer Assisted Learning, 2024
Background: Developments in educational technology and learning analytics make it possible to automatically formulate and deploy personalized formative feedback to learners at scale. However, to be effective, the motivational and emotional impacts of such automated and personalized feedback need to be considered. The literature on feedback…
Descriptors: Emotional Response, Student Motivation, Feedback (Response), Automation
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Yi-Fan Li; Jue-Qi Guan; Xiao-Feng Wang; Qu Chen; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: Self-regulated learning (SRL) is a predictive variable in students' academic performance, especially in virtual reality (VR) environments, which lack monitoring and control. However, current research on VR encounters challenges in effective interventions of cognitive and affective regulation, and visualising the SRL processes using…
Descriptors: Electronic Learning, Individualized Instruction, Learning Processes, Performance
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Burin, Debora I.; González, Federico M.; Martínez, Magali; Marrujo, Jonathan G. – Journal of Computer Assisted Learning, 2021
Most of the studies establishing factors affecting digital text and multimedia comprehension have been conducted in controlled conditions. The present study sought to test and extend the modality and seductive details effects, and the role of verbal ability and working memory capacity, to a remote, self-paced, E-learning scenario. Two hundred and…
Descriptors: Electronic Learning, Multimedia Materials, Comprehension, College Freshmen
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de Mooij, Susanne M. M.; Raijmakers, Maartje E. J.; Dumontheil, Iroise; Kirkham, Natasha Z.; van de Maas, Han L. J. – Journal of Computer Assisted Learning, 2021
While response time and accuracy indicate overall performance, their value in uncovering cognitive processes, underlying learning, is limited. A promising online measure, designed to track decision-making, is computer mouse tracking, where mouse attraction towards different locations may reflect the consideration of alternative response options.…
Descriptors: Error Patterns, Identification, Computer Peripherals, Computer Uses in Education
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Jopling, M. – Journal of Computer Assisted Learning, 2012
This paper outlines the findings of a review that examined the literature around current practice in one-to-one online tuition in schools and higher education. It summarizes the purposes, contexts, scope, and methods of 17 core studies identified through a systematic literature search. It then uses a conceptual framework focusing on pedagogical…
Descriptors: Electronic Learning, Online Courses, Web Based Instruction, Literature Reviews
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Hsiao, I.-H.; Sosnovsky, S.; Brusilovsky, P. – Journal of Computer Assisted Learning, 2010
Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a…
Descriptors: Electronic Learning, Guidance, Individualized Instruction, Computer Software
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Popescu, E. – Journal of Computer Assisted Learning, 2010
Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization criterion called learning style-based adaptive educational systems. The paper presents an innovative approach based on an integrative set of learning preferences that alleviates…
Descriptors: Electronic Learning, Undergraduate Students, Cognitive Style, Individualized Instruction