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Showing 1 to 15 of 135 results Save | Export
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Yu Gao; Linjing Wu; Xiaotong Lv; Xinqian Ma; Qingtang Liu – Journal of Computer Assisted Learning, 2024
Background: Both socially regulated learning and cognitive quality are important factors affecting collaborative knowledge building, but the current research lacks a joint quantified evaluation method that combines these two aspects. Objectives: Based on the existing framework, we proposed a joint evaluation method for regulated learning and…
Descriptors: Self Management, Cooperative Learning, Learning Strategies, Evaluation Methods
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Radovan Šikl; Karla Brücknerová; Hana Švedová; Filip Dechterenko; Pavel Ugwitz; Jirí Chmelík; Hana Pokorná; Vojtech Jurík – Journal of Computer Assisted Learning, 2024
Introduction: Media comparison studies examining the effectiveness of immersive virtual reality in education have yielded inconclusive findings, leaving the question of its impact on learning compared to conventional media unanswered. To address this issue, our study employs a novel approach that combines media comparison with an investigation on…
Descriptors: Computer Simulation, Educational Technology, Secondary School Students, Topography
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Yuko Suzuki; Fridolin Wild; Eileen Scanlon – Journal of Computer Assisted Learning, 2024
Background: Cognitive load during AR use has been measured conventionally by performance tests and subjective rating. With the growing interest in physiological measurement using non-invasive biometric sensors, unbiased real-time detection of cognitive load in AR is expected. However, a range of sensors and parameters are used in various subject…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Physiology
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Buchner, Josef; Buntins, Katja; Kerres, Michael – Journal of Computer Assisted Learning, 2022
Background: Previous studies on augmented reality-enriched learning and training indicated conflicting results regarding the cognitive load involved: some authors report that AR can reduce cognitive load, others have shown that AR is perceived as cognitively demanding and can lead to poorer performance. Objectives: The aim of this study is to…
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Difficulty Level
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Lai, Jennifer W. M.; Bower, Matt; De Nobile, John; Breyer, Yvonne – Journal of Computer Assisted Learning, 2022
Background: There is a lack of critical or empirical work interrogating the nature and purpose of evaluating technology use in education. Objectives: In this study, we examine the values underpinning the evaluation of technology use in education through field specialist perceptions. The study also poses critical reflections about the rigour of…
Descriptors: Technology Uses in Education, Educational Technology, Program Evaluation, Content Validity
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Valentina Nachtigall; Selina Yek; Nikol Rummel – Journal of Computer Assisted Learning, 2024
Background: With the increasing availability of immersive technologies such as 360° videos for educational purposes, research needs to shift from media comparison studies to value-added studies in order to identify conditions for effective learning with such technologies. For the educational use of history-related virtual reality media, which are…
Descriptors: Computer Simulation, Video Technology, Technology Uses in Education, Educational Technology
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Yadviga Radzitskaya; Artem Islamov – Journal of Computer Assisted Learning, 2024
Nanolearning represents an educational methodology rooted in personalisation and the individualisation of the educational process, leveraging contemporary information technologies. Nanolearning, closely intertwined with self-regulated learning, entails an individual's capacity to plan, monitor and regulate their learning process, objectives and…
Descriptors: Microcredentials, Teaching Methods, Information Technology, Learning Processes
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Bissonnette, Steve; Boyer, Christian – Journal of Computer Assisted Learning, 2022
Tingir et al. (2017) concluded from their meta-analysis that the subject areas taught through mobile devices had significantly higher achievement scores (d = 0.48) than the ones taught with traditional teaching methods. Given the relatively high positive effect of mobile devices on student achievement, we carefully analysed the selected research…
Descriptors: Meta Analysis, Electronic Learning, Handheld Devices, Academic Achievement
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Hilliger, Isabel; Ruipérez-Valiente, José A.; Alexandron, Giora; Gaševic, Dragan – Journal of Computer Assisted Learning, 2022
Background: Online learning has grown significantly during the past two decades, and COVID-19 pandemic has expedited this process. However, previous research has shown how academic dishonesty is more prevalent under these modalities. Therefore, there is the challenge of performing trustworthy remote assessments, in order to obtain valid and…
Descriptors: Online Courses, Ethics, Student Evaluation, Evaluation Methods
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Porter, Jill – Journal of Computer Assisted Learning, 2022
Background: Despite the interest and potential of multi touch devices, there are limited published studies researching their effectiveness and usability specifically with children with Down syndrome, one of the most common groups of children with an intellectual disability. This is particularly true for mathematical learning, an area in which many…
Descriptors: Educational Technology, Down Syndrome, Students with Disabilities, Mathematics Instruction
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Charlotte H. Müller; Markus Reiher; Manu Kapur – Journal of Computer Assisted Learning, 2024
Background: Haptic feedback has been shown to be an effective facilitator of the learning of scientific concepts in a series of studies. However, little is known about the underlying salient learning mechanisms, which are activated when learning from haptic feedback. Objectives: We investigate the learning mechanism in a higher chemistry education…
Descriptors: Quantum Mechanics, Chemistry, Feedback (Response), Cognitive Processes
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Shan Li; Xiaoshan Huang; Gaoxia Zhu; Hanxiang Du; Tianlong Zhong; Chenyu Hou; Juan Zheng – Journal of Computer Assisted Learning, 2024
Background: Social annotation has emerged as a promising educational technology that fosters collaborative reading and discussion of digital resources among learners. While the positive impact of social annotation on students' learning process and performance is widely acknowledged, students' behavioural patterns in social annotation are…
Descriptors: Undergraduate Students, Cooperative Learning, Reading Strategies, Group Activities
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Weipeng Yang; Xinyun Hu; Ibrahim H. Yeter; Jiahong Su; Yuqin Yang; John Chi-Kin Lee – Journal of Computer Assisted Learning, 2024
Background: Artificial Intelligence (AI) literacy is a crucial part of digital literacy that all individuals should possess in today's technologically advanced world. Despite the potential benefits that AI education offers, little research has been done on how to teach AI literacy to children. Objectives: This study aimed to fill that gap by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Digital Literacy
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Wang, Jingxian; Tigelaar, Dineke E. H.; Zhou, Tian; Admiraal, Wilfried – Journal of Computer Assisted Learning, 2023
Background: The impact of mobile technology usage on student learning in various educational stages has been the subject of ongoing empirical and review research. The most recent meta-analyses on various types of mobile technology use for potential benefits of learning covered the empirical studies up to about nine years ago. Since then, the use…
Descriptors: Educational Technology, Telecommunications, Handheld Devices, Elementary Secondary Education
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Tomoko Yabukoshi; Atsushi Mizumoto – Journal of Computer Assisted Learning, 2024
Background: While self-regulated learning (SRL) strategy-based writing instruction has been proposed in English as a foreign language (EFL) classrooms, there is insufficient evidence with Japanese EFL learners and little discussion on incorporating online resources into SRL strategy-based writing instruction, despite the availability of various…
Descriptors: Writing (Composition), Educational Technology, Self Management, Learning Strategies
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