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Showing 1 to 15 of 26 results Save | Export
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Minkai Wang; Jingdong Zhu; Gwo-Jen Hwang; Shao-Chen Chang; Qi-Fan Yang; Di Zhang – Journal of Computer Assisted Learning, 2025
Background: STEM education aims to develop innovation and problem-solving skills through interdisciplinary learning, yet struggles to foster student engagement and interdisciplinary thinking. Whilst alternate reality games (ARGs) can boost motivation via game-based problem-solving, integrating large language models (LLMs) remains underexplored.…
Descriptors: Learner Engagement, STEM Education, Natural Language Processing, Artificial Intelligence
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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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Veerbeek, Jochanan; Vogelaar, Bart; Verhaegh, Janneke; Resing, Wilma C. M. – Journal of Computer Assisted Learning, 2019
Task solving processes and changes in these processes have long been expected to provide valuable information about children's performance in school. This article used electronic tangibles (concrete materials that can be physically manipulated) and a dynamic testing format (pretest, training, and posttest) to investigate children's task solving…
Descriptors: Young Children, Pretests Posttests, Problem Solving, Outcomes of Education
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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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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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Sun, Lihui; Hu, Linlin; Yang, Weipeng; Zhou, Danhua; Wang, Xiaoqian – Journal of Computer Assisted Learning, 2021
Computational thinking (CT) plays a vital role in the fields of science, technology, engineering and mathematics (STEM). However, whether students' learning attitude towards STEM is related to their CT skills remains unknown. Two studies were conducted to address this knowledge gap. In Study 1, we validated a newly developed STEM learning attitude…
Descriptors: STEM Education, Predictor Variables, Computer Science, Thinking Skills
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Chen, Chen; Sonnert, Gerhard; Sadler, Philip M.; Malan, David J. – Journal of Computer Assisted Learning, 2020
Massive open online course (MOOC) studies have shown that precourse skills (such as precomputational thinking) and course engagement measures (such as making multiple submission attempts with assignments when the initial submission is incorrect) predict students' grade performance, yet little is known about whether these factors predict students'…
Descriptors: Computation, Thinking Skills, Assignments, Predictor Variables
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Zhu, Jinxin; Mok, Magdalena M. C. – Journal of Computer Assisted Learning, 2020
In recent years, it has become common to use the internet or computer tutoring with a programme or application for additional instruction (ICTPAAI), in addition to the mandatory school schedule. This study aimed to understand students' participation in ICTPAAI and its relation to academic achievement. Multilevel structural equation modelling was…
Descriptors: Predictor Variables, Student Participation, Internet, Computer Assisted Instruction
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Joksimovic, S.; Gaševic, D.; Kovanovic, V.; Riecke, B. E.; Hatala, M. – Journal of Computer Assisted Learning, 2015
With the steady development of online education and online learning environments, possibilities to support social interactions between students have advanced significantly. This study examined the relationship between indicators of social presence and academic performance. Social presence is defined as students' ability to engage socially with an…
Descriptors: Computer Mediated Communication, Online Courses, Correlation, Interpersonal Relationship
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Spikol, Daniel; Ruffaldi, Emanuele; Dabisias, Giacomo; Cukurova, Mutlu – Journal of Computer Assisted Learning, 2018
Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates the use of diverse sensors, including computer vision, user-generated content, and data from the learning objects (physical computing components),…
Descriptors: Student Projects, Active Learning, Teaching Methods, Group Dynamics
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Jo, I.; Park, Y.; Lee, H. – Journal of Computer Assisted Learning, 2017
An asynchronous online discussion (AOD) is one format of instructional methods that facilitate student-centered learning. In the wealth of AOD research, this study evaluated how students' behavior on AOD influences their academic outcomes. This case study compared the differential analytic methods including web log mining, social network analysis…
Descriptors: Computer Mediated Communication, Interaction Process Analysis, Undergraduate Students, Predictor Variables
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Bressler, D. M.; Bodzin, A. M. – Journal of Computer Assisted Learning, 2013
Current studies have reported that secondary students are highly engaged while playing mobile augmented reality (AR) learning games. Some researchers have posited that players' engagement may indicate a flow experience, but no research results have confirmed this hypothesis with vision-based AR learning games. This study investigated factors…
Descriptors: Psychological Patterns, Affective Behavior, Learner Engagement, Secondary School Students
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Levy, S. T.; Lahav, O. – Journal of Computer Assisted Learning, 2012
This paper addresses a central need among people who are blind, access to inquiry-based science learning materials, which are addressed by few other learning environments that use assistive technologies. In this study, we investigated ways in which learning environments based on sound mediation can support science learning by blind people. We used…
Descriptors: Assistive Technology, Pretests Posttests, Acoustics, Auditory Stimuli
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