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Showing 1 to 15 of 56 results Save | Export
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Miao Chao; Weiyi Sun; Jie Liu; Jiahui Ding; Ye Zhu – Journal of Computer Assisted Learning, 2025
Background: The use of social media among students has become debatable concern due to both positive and negative effects on academic performance. Yet, understanding of the diverse patterns of social media use and their influence on actual and perceived academic performance remains limited. Objectives: This study distinguishes between academic and…
Descriptors: Social Media, Performance, Influence of Technology, Predictor Variables
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Blaženka Divjak; Barbi Svetec; Damir Horvat – Journal of Computer Assisted Learning, 2024
Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic…
Descriptors: Automation, Formative Evaluation, Test Validity, Test Reliability
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Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
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Gulnur Tyulepberdinova; Madina Mansurova; Talshyn Sarsembayeva; Sulu Issabayeva; Darazha Issabayeva – Journal of Computer Assisted Learning, 2024
Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…
Descriptors: Artificial Intelligence, Algorithms, Predictor Variables, Physical Health
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Lihui Sun; Danhua Zhou – Journal of Computer Assisted Learning, 2024
Background: Integrating programming in K-12 curriculum has become a global consensus. Teachers are central figures in programming instruction. But the majority of current research focuses on teachers' external teaching behaviours and less on teachers' attitudes towards programming. Objectives: The purpose of this study is to validate the K-12…
Descriptors: Foreign Countries, Elementary School Teachers, Secondary School Teachers, Teacher Attitudes
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Spitzer, Markus Wolfgang Hermann; Moeller, Korbinian – Journal of Computer Assisted Learning, 2022
Background: Mastering fractions seems among the most critical mathematical skills for students to acquire in school as fraction understanding significantly predicts later mathematic achievements, but also broader academic and vocational prospects. As such, identifying longitudinal predictors of fraction understanding (e.g., mastery of numbers and…
Descriptors: Fractions, Mathematics Instruction, Mathematics Skills, Predictor Variables
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Okan Bulut; Guher Gorgun; Seyma Nur Yildirim-Erbasli – Journal of Computer Assisted Learning, 2025
Background: Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress.…
Descriptors: Formative Evaluation, Academic Achievement, Student Participation, Learning Processes
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Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
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Alam, Sabrina Shajeen; Dubé, Adam Kenneth – Journal of Computer Assisted Learning, 2023
Background: A strong knowledge of mathematics, beginning at the elementary level, is critical for participation in today's complex world. The home may be one way to facilitate individualized mathematics instruction, given that children spend more time at home than in an academic institution. Therefore, researchers are interested to see whether the…
Descriptors: Foreign Countries, Elementary School Students, Numeracy, Family Environment
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Chen, Yi-Ching; Chang, Yu-Shan; Chuang, Meng-Jung – Journal of Computer Assisted Learning, 2022
Virtual reality (VR) can promote design performance, and may generate a high cognitive load and affect creative design thinking as well. In order to examine the effect of VR application on cognitive load and engineering design creativity, this study recruited 81 eighth-grade students as participants and employed a non-equivalent-groups…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Creative Thinking
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Daniels, Lia M.; Bulut, Okan – Journal of Computer Assisted Learning, 2020
In computer-based testing (CBT) environments instructors can provide students with feedback immediately. Commonly, instructors give students their percentage correct without additional descriptive feedback. Our objectives were (a) to compare students' perceived usefulness of a percentage-only score report vs. a descriptive feedback report in a CBT…
Descriptors: Computer Assisted Testing, Feedback (Response), Value Judgment, Student Attitudes
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Niu, Liwei; Wang, Xinghua; Wallace, Matthew P.; Pang, Hui; Xu, Yanping – Journal of Computer Assisted Learning, 2022
Background: In view of the widespread use of digital technologies in English as a foreign language (EFL) learning and the importance of students' approaches to learning (SAL) and digital competence, as well as the threats of technostress in digital settings, digital EFL learning requires a critical examination. Objectives: This study sought to…
Descriptors: English (Second Language), Educational Technology, Electronic Learning, Second Language Learning
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Edwards, Ordene V. – Journal of Computer Assisted Learning, 2021
This study examines the influence of perceived social presence on online graduate students' value and expectancy beliefs. Forty-nine participants enrolled in an online teacher leadership graduate program completed questionnaires that measured perceived social presence and value and expectancy beliefs. A series of simple linear regression analyses…
Descriptors: Context Effect, Social Environment, Value Judgment, Expectation
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Ding, Yan; Zhao, Ting – Journal of Computer Assisted Learning, 2020
Emotions are critical to learning. However, the function of emotions in the emerging context of massive open online courses (MOOCs) has been under-researched. The present study complemented this line of research by modelling the relation between learner emotions, engagement with videos, engagement with assignments, and self-perceived achievement…
Descriptors: Psychological Patterns, Online Courses, Learner Engagement, Educational Technology
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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