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Maria M. Swanepoel; Gary W. Collins – International Journal of Education and Development using Information and Communication Technology, 2025
Despite the widespread use of electronic accounting systems in professional practice, South African accounting education often lags, with teachers frequently prioritising manual accounting skills over the integration of Computer-Aided Learning (CAL). This reliance on traditional methods, potentially shaped by a complex combination of internal and…
Descriptors: Foreign Countries, Accounting, Private School Teachers, Teacher Attitudes
Shilpi Taneja; Siddhartha Sankar Biswas; Bhavya Alankar; Harleen Kaur – Electronic Journal of e-Learning, 2025
This paper presents the design of a personalized learning agent powered by the Agentic RAG technique. The agent can interpret learners' queries and autonomously decide which tools should be used to generate the most suitable response. When the learner shares an Open Educational Resource (OER) they wish to learn from, the agent first breaks the…
Descriptors: Artificial Intelligence, Natural Language Processing, Open Educational Resources, Individualized Instruction
Chih-Chung Lin; Tzu-Hsuan Lin; Chi-Kay Tang – Journal of Computer Assisted Learning, 2025
Background: The integration of generative artificial intelligence (Gen-AI) into second language (L2) education has opened new possibilities for personalized and adaptive instruction. While Gen-AI has shown promise in supporting language production skills, its application in reading, particularly in pre-reading scaffolding, remains underexplored.…
Descriptors: Reading Comprehension, English (Second Language), Second Language Learning, College Freshmen
Xian Shang – European Journal of Education, 2025
Artificial intelligence (AI) technologies have been increasingly recognised for their transformative potential in education. However, limited research has examined the emotional and behavioural impacts of AI-powered robots on students. To bridge this gap, the present study explored whether instruction supported by AI-powered robots enhances…
Descriptors: Artificial Intelligence, Technology Uses in Education, Robotics, Learner Engagement
Ngo Thi Huyen Trang; Phuoc Tai Nguyen – Educational Process: International Journal, 2025
Background/purpose: The research was conducted to explore how digital transformation can enhance LLCT teaching quality by integrating advanced technologies, improving interactivity, and fostering critical thinking among cadres. The main purpose is to analyze the necessity, current status, challenges, and solutions for digital transformation in…
Descriptors: Foreign Countries, Technology Uses in Education, Technology Integration, Educational Technology
Zheng, Lanqin; Niu, Jiayu; Long, Miaolang; Fan, Yunchao – British Journal of Educational Technology, 2023
Computer-supported collaborative learning (CSCL) has been an effective pedagogy in the field of education. However, productive collaborative learning often does not occur spontaneously, and learners often have difficulties with collaborative knowledge building and socially shared regulation. To address this research gap, this study proposes an…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Graphs, College Students
Havard, Byron; Podsiad, Megan; Valaitis, Karen – TechTrends: Linking Research and Practice to Improve Learning, 2023
The Peer Assessment Collaboration Evaluation (PACE) Tool is an original peer assessment tool designed and developed by the authors to address the prevalence of social loafing in group projects in online learning environments. Online group projects offer students collaborative opportunities to engage in critical thinking and problem-solving.…
Descriptors: Peer Evaluation, Student Behavior, Computer Assisted Instruction, Cooperative Learning
Alwafi, Enas Mohammad – Educational Technology Research and Development, 2023
This study investigated the impact of designing an online learning environment based on cognitive apprenticeship on students' critical thinking and interaction in CSCL. The one group pretest-posttest quasi-experimental design was used in this study. A questionnaire was used to measure students' critical thinking and social network analysis (SNA)…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Instructional Design, Electronic Learning
Siegle, Robert F.; Schroeder, Noah L.; Lane, H. Chad; Craig, Scotty D. – TechTrends: Linking Research and Practice to Improve Learning, 2023
Pedagogical agents are on-screen characters that help facilitate learning in a virtual or mixed-reality setting. The research on pedagogical agents has shifted focus since their creation, from understanding their underlying principles, identifying their potential roles and usage, and recently finetuning their design for applied practice. This…
Descriptors: Teaching Methods, Artificial Intelligence, Technology Uses in Education, Barriers
Eglington, Luke G.; Pavlik, Philip I., Jr. – International Journal of Artificial Intelligence in Education, 2023
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Manegre, Marni; Gutiérrez-Colón, Mar – Interactive Learning Environments, 2023
Knowledge building occurs when students work together and participate in idea-centred discussions where they share information and create knowledge collectively. This research explores whether knowledge building in knowledge forums using English as the "lingua franca" can facilitate in foreign language learning. An analysis was done on…
Descriptors: Second Language Learning, Collaborative Writing, Computer Assisted Instruction, Computer Mediated Communication
Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
Liu, Sannyuya; Kang, Lingyun; Liu, Zhi; Fang, Jing; Yang, Zongkai; Sun, Jianwen; Wang, Meiyi; Hu, Mengwei – Interactive Learning Environments, 2023
Computer-supported collaborative concept mapping (CSCCM) integrates technology and concept mapping to support students' knowledge understanding, and much research on the behavioral patterns involved in CSCCM activities has been conducted. However, there is limited understanding of the differences in knowledge understanding and behavioral patterns…
Descriptors: Computer Assisted Instruction, Concept Mapping, Student Attitudes, College Students
Bembenutty, Héfer – New Directions for Teaching and Learning, 2023
Along with the increased interest in self-regulated learning research, there has been a high engrossment in computer-based learning environments that facilitate instruction and promote learning. These two crucial pedagogical approaches have been identified as being valuable to educators and learners. They merit refreshed considerations in light of…
Descriptors: Metacognition, Computer Assisted Instruction, Teaching Methods, Learning Processes
Lili Mutiary; Christina Ratnam-Lim – International Journal of Technology in Education, 2023
Online courses for the professional development of workers in service is ever pervasive and continually growing. However, studies of teaching with technology are mostly conducted in K-12, pre-service, or higher education settings resulting in a lack of attention given to the professional development context. In addition, most studies tend to…
Descriptors: Professional Development, Computer Assisted Instruction, Internet, Selection

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