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Chandan Kumar Tiwari; Mohd. Abass Bhat; Shagufta Tariq Khan; Rajaswaminathan Subramaniam; Mohammad Atif Irshad Khan – Interactive Technology and Smart Education, 2024
Purpose: The purpose of this paper is to identify the factors determining students' attitude toward using newly emerged artificial intelligence (AI) tool, Chat Generative Pre-Trained Transformer (ChatGPT), for educational and learning purpose based on technology acceptance model. Design/methodology/approach: The recommended model was empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Student Attitudes
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Yizhou Fan; Luzhen Tang; Huixiao Le; Kejie Shen; Shufang Tan; Yueying Zhao; Yuan Shen; Xinyu Li; Dragan Gaševic – British Journal of Educational Technology, 2025
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of supports from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. In particular, there has been a surge of academic interest in human-AI collaboration and…
Descriptors: College Students, Writing Achievement, Writing Exercises, Artificial Intelligence
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Chang, Hui-Tzu; Lin, Chia-Yu; Jheng, Wei-Bin; Chen, Shih-Hsu; Wu, Hsien-Hua; Tseng, Fang-Ching; Wang, Li-Chun – Educational Technology & Society, 2023
The objective of this research is based on human-centered AI in education to develop a personalized hybrid course recommendation system (PHCRS) to assist students with course selection decisions from different departments. The system integrates three recommendation methods, item-based, user-based and content-based filtering, and then optimizes the…
Descriptors: Artificial Intelligence, Course Selection (Students), Blended Learning, Accuracy
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Yong Jik Lee; Robert O. Davis – Contemporary Educational Technology, 2024
This research investigated the effects of generative AI on affective factors (motivation, interest, and confidence) of English as a foreign language (EFL) learners enrolled in Korean university-level general English courses. During the Spring 2024 semester, this study involved 89 participants exposed to a generative AI-based instruction model.…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Artificial Intelligence
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Sultan Hammad Alshammari; Mohammed Habib Alshammari – International Journal of Information and Communication Technology Education, 2024
The current study aims at assessing the factors which could affect students' use of ChatGPT. The study proposed a theoretical model that included five factors. Data were collected from 136 students using a questionnaire. The data were analyzed using two steps: CFA for measuring the model and SEM for analyzing the relationships and testing…
Descriptors: Influences, Technology Uses in Education, Artificial Intelligence, Natural Language Processing
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John R. Haughery – IEEE Transactions on Education, 2024
Contribution: This study qualitatively uncovered meaning for why and what was motivating to undergraduates participating in an educational human-robot interaction (HRI) experience. A data corpus of four documents (groups) was evaluated from a quasi-experimental, nonequivalent control (n = 23) and treatment (n = 61) research design revealing three…
Descriptors: Undergraduate Students, Engineering Education, Man Machine Systems, Robotics
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Orji, Fidelia A.; Vassileva, Julita – Journal of Educational Technology Systems, 2023
This research presents a proposed approach that could be applied in modeling students' study strategies and performance in higher education. The research used key learning attributes, including intrinsic motivation, extrinsic motivation, autonomy, relatedness, competence, and self-esteem in the modeling. Five machine learning models were…
Descriptors: Student Motivation, Learner Engagement, Undergraduate Students, Learning Strategies
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Saman Ebadi; Asieh Amini – Interactive Learning Environments, 2024
Artificial Intelligence (AI) technology in the educational context, particularly chatbotics, has made significant changes in learning English. This mixed-methods study is intended to explore university students' attitudes toward the potential role of artificial intelligence (AI)-assisted mobile applications. Meanwhile, the role of social presence…
Descriptors: Artificial Intelligence, Educational Technology, English (Second Language), Second Language Learning
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Saw Fen Tan – Asian Association of Open Universities Journal, 2024
Purpose: This study aims to explore students' perceptions of the use of an artificial intelligence-generated content avatar (AIGC avatar) within a learning management system (LMS). Design/methodology/approach: This qualitative research involved seven postgraduate students. Data were collected through individual, in-depth interviews. The videos of…
Descriptors: Student Attitudes, Artificial Intelligence, Computer Simulation, Self Concept
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Luis Alberto Laurens-Arredondo – Education and Information Technologies, 2024
The use of technologies in the classroom has become one of the main allies for university teachers in pedagogical innovation, especially during, and after the pandemic. Therefore, the main objective of this article is to investigate how different types of innovative technologies are most effective in increasing motivation among university…
Descriptors: Educational Technology, Student Motivation, Technology Uses in Education, College Students
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Chen-Chen Liu; Hai-Jie Wang; Dan Wang; Yun-Fang Tu; Gwo-Jen Hwang; Youmei Wang – Interactive Learning Environments, 2024
Teachers' instructional design skills influence their teaching practices and student learning performances. However, researchers have found that the traditional one-to-many model of preservice teacher education prevents preservice teachers from receiving timely and individualized feedback, making it difficult to fill in theoretical knowledge gaps…
Descriptors: Preservice Teachers, Instructional Design, Teaching Skills, Knowledge Level
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Salah Zogheib; Bashar Zogheib – Journal of Information Technology Education: Research, 2024
Aim/Purpose: The aim of this study is to explore the factors that influence higher education students' adoption of ChatGPT by incorporating constructs from the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT) with trust, social influence, and personal innovativeness. Background: Even though the use of ChatGPT has become more…
Descriptors: College Students, Student Behavior, Natural Language Processing, Public Colleges
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Yu-Yin Wang – Education and Information Technologies, 2025
Considering the proliferation of artificial intelligence (AI) technologies, it has become crucial to integrate AI-related knowledge and skills education into business management curricula. This is a significant concern for both academics and practitioners. However, in the context of university business management education, few studies have…
Descriptors: Individual Differences, Intention, Artificial Intelligence, Technology Uses in Education
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Hanwei Wu; Yunsong Wang; Yongliang Wang – International Review of Research in Open and Distributed Learning, 2024
Artificial intelligence (AI) offers new possibilities for English as a foreign language (EFL) learners to enhance their learning outcomes, provided that they have access to AI applications. However, little is written about the factors that influence their intention to use AI in distributed EFL learning contexts. This mixed-methods study, based on…
Descriptors: College Students, Artificial Intelligence, English (Second Language), Second Language Learning
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Wei-Sheng Wang; Margus Pedaste; Chia-Ju Lin; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Interactive Learning Environments, 2024
Virtual reality (VR) provides a unique platform for interactive learning experiences, enhancing learning, particularly in hands-on courses. However, the visual load of VR and the lack of guidance and interaction from physical teachers or peers can pose challenges for learners in self-regulated learning (SRL) and learning motivation. This study…
Descriptors: Feedback (Response), Self Management, Student Motivation, Computer Simulation
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