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Meina Zhu – Journal of Computer Assisted Learning, 2025
Background: Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning. Objectives: This study aims to examine the sentiments and primary topics discussed in YouTube comments…
Descriptors: Computer Science Education, Programming, Social Media, Video Technology
Dana Kube; Sebastian Gombert; Brigitte Suter; Joshua Weidlich; Karel Kreijns; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Gender stereotypes about women and men are prevalent in computer science (CS). The study's goal was to investigate the role of gender bias in computer-supported collaborative learning (CSCL) in a CS context by elaborating on gendered experiences in the perception of individual and team performance in mixed-gender teams in a hackathon.…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Gender Issues, Learning Activities
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
Yang Jiang; Beata Beigman Klebanov; Jiangang Hao; Paul Deane; Oren E. Livne – Journal of Computer Assisted Learning, 2025
Background: Writing is integral to educational success at all levels and to success in the workplace. However, low literacy is a global challenge, and many students lack sufficient skills to be good writers. With the rapid advance of technology, computer-based tools that provide automated feedback are being increasingly developed. However, mixed…
Descriptors: Feedback (Response), Writing Evaluation, Middle School Students, High School Students
Jia Zhang; Zhuo Zhang – Journal of Computer Assisted Learning, 2024
Background: AI can positively influence teaching by offering support for classroom management, creating inclusive learning environments, enhancing digital skills, personalizing teaching methods, and strengthening teacher-student relationships. Objectives: This quantitative research study investigates the opportunities, difficulties, and…
Descriptors: Inclusion, Teaching Methods, Computer Assisted Instruction, Barriers
Maertens, Rien; Van Petegem, Charlotte; Strijbol, Niko; Baeyens, Toon; Jacobs, Arne Carla; Dawyndt, Peter; Mesuere, Bart – Journal of Computer Assisted Learning, 2022
Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…
Descriptors: Plagiarism, Benchmarking, Coding, Computer Science Education
Araos, Andrés; Damsa, Crina; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: The surge of online platforms has generated interest in how specialized platforms support formal and informal learning in various disciplinary domains. Knowledge is still limited regarding how undergraduate students navigate and use platforms to learn. Objectives: This study explores computer and software engineering students' learning…
Descriptors: Computer Science Education, Computer Software, Learning Activities, Undergraduate Students
Esmaeil Jafari – Journal of Computer Assisted Learning, 2024
Background: Artificial intelligence (AI) has created new opportunities, challenges, and potentials in teaching; however, issues related to the philosophy of using AI technology in learners' learning have not been addressed and have caused some issues and concerns. This issue is due to the research gap in addressing issues related to ethical and…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, College Faculty
Duncan, Alex; Joyner, David – Journal of Computer Assisted Learning, 2022
Background: It is important for institutions of higher education to maintain academic integrity, both for students and the institutions themselves. Proctoring is one way of accomplishing this, and with the increasing popularity of online courses--along with the sudden shift to online education sparked by the COVID-19 pandemic--digital proctoring…
Descriptors: Computer Assisted Testing, Supervision, Integrity, COVID-19
Tong Bao – Journal of Computer Assisted Learning, 2025
Background: Given the limited availability of effective tools for Korean language learning among students with autism spectrum disorder (ASD), there is a need to explore innovative educational technologies to support the development of reading skills in Korean language education for this population. Objectives: The purpose of this study is to…
Descriptors: Korean, Autism Spectrum Disorders, Scores, Reading Comprehension
Surahman, Ence; Wang, Tzu-Hua – Journal of Computer Assisted Learning, 2022
Background: Academic dishonesty (AD) and trustworthy assessment (TA) are fundamental issues in the context of an online assessment. However, little systematic work currently exists on how researchers have explored AD and TA issues in online assessment practice. Objectives: Hence, this research aimed at investigating the latest findings regarding…
Descriptors: Ethics, Trust (Psychology), Computer Assisted Testing, Educational Technology
Katai, Zoltan; Osztian, Erika – Journal of Computer Assisted Learning, 2023
Background: This study is the first to address the topic of schematic versus realistic dynamic visualization with particular focus on the human movement effect (HME) when the content to be learned takes the form of a computer algorithm. An AlgoRythmics dance choreography illustration (HM-realistic) was compared with an abstract computer animation…
Descriptors: Computer Software, Algorithms, Visualization, Animation
Allan Mesa Canonigo – Journal of Computer Assisted Learning, 2024
Motivation: This research investigates the transformative impact of integrating AI into mathematics education, aiming to enhance students' conceptual understanding and self-efficacy. It addresses the crucial need for innovative teaching methods in response to contemporary challenges in education and aims to fill gaps in understanding the potential…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Mathematics Instruction, Problem Solving
Li, Yuhao; Chang, Mengyi; Zhao, Hanxuan; Jiang, Caihong; Xu, Sihua – Journal of Computer Assisted Learning, 2023
Background: Mobile devices facilitate learning activities in a self-paced way. However, the current understanding of learning participation and its consequence are minimal when learners take advantage of opportunities provided by mobile technologies worldwide. Aims: The primary purpose of this study is to examine the effectiveness of environmental…
Descriptors: Anxiety, Computer Software, Computer Assisted Instruction, Learning Processes
Gao, Ming; Zhang, Jingjing; Lu, Yu; Kahn, Ken; Winters, Niall – Journal of Computer Assisted Learning, 2023
Background: As a non-cognitive trait, grit plays an important role in human learning. Although students higher in grit are more likely to perform well on tests, how they learn in the process has been underexamined. Objectives: This study attempted to explore how students with different levels of grit behave and learn in an exploratory learning…
Descriptors: Resilience (Psychology), Academic Persistence, Personality Traits, Usability

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