NotesFAQContact Us
Collection
Advanced
Search Tips
Source
Journal of Computer Assisted…113
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 113 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Xu Fang; Yutong Cai – Journal of Computer Assisted Learning, 2025
Background: The application of generative artificial intelligence (GenAI) in education has been deepening. However, at the same time, behaviours that jeopardise academic health, such as learners' over-reliance on generative AI and massive plagiarism of generated content of generative AI in essay writing, have begun to emerge, and the issue of…
Descriptors: Ethics, College Students, Artificial Intelligence, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Shang Shanshan; Geng Sen – Journal of Computer Assisted Learning, 2024
Background: Artificial intelligence-generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic. Objectives: This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Programming
Peer reviewed Peer reviewed
Direct linkDirect link
Héctor Galindo-Domínguez; Nahia Delgado; María-Victoria Urruzola; Jose-María Etxabe; Lucía Campo – Journal of Computer Assisted Learning, 2025
Background: With the integration of artificial intelligence into educational processes, its impact remains to be discovered. Objective: The aim of the present study was to determine whether, after a 7-month intervention in which a subject of artificial intelligence was taught, students improved their psychological needs for competence, autonomy…
Descriptors: Artificial Intelligence, Adolescents, Student Motivation, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Chengliang Wang; Xiaojiao Chen; Zhebing Hu; Sheng Jin; Xiaoqing Gu – Journal of Computer Assisted Learning, 2025
Background: ChatGPT, as a cutting-edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated content (AIGC) technology, highlighting the need…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Computer Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Mohamed Ali Nagy Elmaadaway; Mohamed Elsayed El-Naggar; Mohamed Radwan Ibrahim Abouhashesh – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) made substantial progress with language recognition. Proficiency in spoken English reading is a prerequisite for fluency in written English. However, research on its use, especially for non-native speakers, is lacking despite increased usage. Objectives: This study aimed to enhance the oral reading fluency…
Descriptors: Artificial Intelligence, Reading Fluency, Elementary School Students, Oral Reading
Peer reviewed Peer reviewed
Direct linkDirect link
Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Yerin Seung; James D. Basham; Taehyun Kim; Jennifer Lohoefener – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) can support more personalised learning in K-12 education, reshaping the educational experience for all students. However, little is known about how AI is being designed and implemented to support accessible and equitable learning experiences for all students, including those with disabilities and academic…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Secondary Education, Student Diversity
Peer reviewed Peer reviewed
Direct linkDirect link
Seyma Çaglar-Özhan; Perihan Tekeli; Selay Arkün-Kocadere – Journal of Computer Assisted Learning, 2025
Background: Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Role, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Sivakorn Malakul – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) tools have been increasingly utilised in the production of educational media, including animated educational videos (AEVs) incorporating pedagogical agents (PAs). These tools support the efficient creation of multimedia content and reduce teachers' technical workload. Objectives: This study investigates the…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Teacher Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
Xue Zhou; Peter Wolstencroft; Lilian N. Schofield; Lei Fang – Journal of Computer Assisted Learning, 2025
Background: The digital literacy landscape has undergone significant changes over the last 5 years, from the impact of the COVID-19 pandemic to the emergence of Artificial Intelligence (AI) technologies. The COVID-19 pandemic hastened the necessity for advanced digital skills for remote work and online collaboration, while the current AI era…
Descriptors: College Graduates, Alumni, Employer Attitudes, Digital Literacy
Peer reviewed Peer reviewed
Direct linkDirect link
Bryan Abendschein; Xialing Lin; Chad Edwards; Autumn Edwards; Varun Rijhwani – Journal of Computer Assisted Learning, 2024
Background: Education is often the primary arena for exploring and integrating new technologies. AI and human-machine communication (HMC) are prevalent in the classroom, yet we are still learning how student perceptions of these tools will impact education. Objectives: We sought to understand student perceptions of credibility related to written…
Descriptors: Students, Student Attitudes, Feedback (Response), Writing (Composition)
Peer reviewed Peer reviewed
Direct linkDirect link
Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
Peer reviewed Peer reviewed
Direct linkDirect link
Weipeng Shen; Xiao-Fan Lin; Jiachun Liu; Xinxian Liang; Ruiqing Chen; Xiaoyun Lai; Xinwen Zheng – Journal of Computer Assisted Learning, 2025
Background: Generative artificial intelligence (GenAI) chatbots extend transformative impact in higher education. Current research requires more comprehensive evaluations of the collaborative learning fostered by students and GenAI chatbots. However, existing articles have rarely explored the dynamic process of student--AI collaboration in higher…
Descriptors: Undergraduate Students, Artificial Intelligence, Technology Uses in Education, Computer Mediated Communication
Peer reviewed Peer reviewed
Direct linkDirect link
Fan Xu; Ana-Paula Correia – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) is an essential skill for preparing the younger generation to succeed in an AI-driven world, with pair programming emerging as a widely used approach to foster these skills. However, the role of individual factors and mutual engagement in shaping CT skills within pair programming remains underexplored,…
Descriptors: Computation, Thinking Skills, Learner Engagement, Middle School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Michelle Cheong – Journal of Computer Assisted Learning, 2025
Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…
Descriptors: Artificial Intelligence, Performance Based Assessment, Spreadsheets, Models
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8