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Showing 1 to 15 of 52 results Save | Export
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Rustam Shadiev; Xuan Chen; Fahriye Altinay – Journal of Computer Assisted Learning, 2024
Background: Our study analysed 46 articles on computer-aided translation (CAT) and its educational uses. We explored two main areas: CAT technologies in learning and teaching, and the research methodologies of these studies. Objectives: Our review covered the types of CAT technologies used, their applications in different learning settings,…
Descriptors: Translation, College Students, Computer Assisted Instruction, Computer Software Evaluation
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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
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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
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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
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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
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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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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
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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
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Elif Sari; Turgay Han – Journal of Computer Assisted Learning, 2024
Background: With the growing trend of integrating technology into teaching environments, using Automated Writing Evaluation (AWE) in writing instruction has been extensively studied over the last two decades. The studies on AWE mostly investigated its impact on students' writing proficiencies and revealed conflicting results. However, very few…
Descriptors: Writing Evaluation, Second Language Learning, Second Language Instruction, English (Second Language)
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Krouska, Akrivi; Troussas, Christos; Virvou, Maria – Journal of Computer Assisted Learning, 2019
Social networks have intruded in human life by providing new technological innovations in a range of fields, including the education. The use of social networks in education has the potential to extend e-learning and to introduce new forms of tutoring, communication, and collaboration between students and instructors. Thus, e-learning is the…
Descriptors: Social Networks, Guidelines, Electronic Learning, Teacher Student Relationship
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Porter, J. – Journal of Computer Assisted Learning, 2018
Tablets have much to offer children with learning difficulties, but evidence of their effectiveness to teach academic skills is limited and cannot be easily separated from the quality of the software. This paper analyses data from 3 iterative cycles of designing an app for children with Down syndrome to support their awareness of quantity through…
Descriptors: Down Syndrome, Computer Software, Learning Problems, Handheld Devices
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Cornelisz, Ilja; Klaveren, Chris – Journal of Computer Assisted Learning, 2018
A prerequisite for low-stakes activities to improve learning is to keep students engaged when confronted with challenging material. Comparing a personalized and non-personalized version of computerized practising, this study experimentally evaluates the relationships between student effort and ability across different dimensions of task…
Descriptors: Learner Engagement, Computer Assisted Instruction, Correlation, Summative Evaluation
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Ghysels, J.; Haelermans, C. – Journal of Computer Assisted Learning, 2018
This paper provides new evidence on the effect of computerized individualized practice and instruction on language skills, more specifically on spelling. An individually randomized experiment among 7th grade students in the Netherlands is developed to study the effect of an adaptive digital homework tool on spelling performance. Using an…
Descriptors: Teaching Methods, Computer Assisted Instruction, Grade 7, Language Skills
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Kolpashnikova, Kamila; Bartolic, Silvia – Journal of Computer Assisted Learning, 2019
Computer-assisted instruction can change the way introductory statistics and quantitative methods courses are taught. Using a two-group pretest-posttest design, we conducted an experiment using an undergraduate social science student sample to investigate whether the introduction of statistical software to teaching quantitative methods would…
Descriptors: Computer Assisted Instruction, Student Attitudes, Pretests Posttests, Teaching Methods
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Schneider, J.; Börner, D.; van Rosmalen, P.; Specht, M. – Journal of Computer Assisted Learning, 2017
The ability to present effectively is essential for professionals; therefore, oral communication courses have become part of the curricula for higher education studies. However, speaking in public is still a challenge for many graduates. To tackle this problem, driven by the recent advances in computer vision techniques and prosody analysis,…
Descriptors: Nonverbal Communication, Feedback (Response), Semi Structured Interviews, Public Speaking
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