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Orji, Fidelia A.; Vassileva, Julita – Journal of Educational Computing Research, 2023
There is a dearth of knowledge on how persuasiveness of influence strategies affects students' behaviours when using online educational systems. Persuasiveness is a term used in describing a system's capability to motivate desired behaviour. Most existing approaches for assessing the persuasiveness of a system are based on subjective measures…
Descriptors: Influences, Student Behavior, Artificial Intelligence, Electronic Learning
Hung Manh Nguyen; Daisaku Goto – Education and Information Technologies, 2024
The proliferation of artificial intelligence (AI) technology has brought both innovative opportunities and unprecedented challenges to the education sector. Although AI makes education more accessible and efficient, the intentional misuse of AI chatbots in facilitating academic cheating has become a growing concern. By using the indirect…
Descriptors: Academic Achievement, Cheating, Student Behavior, Artificial Intelligence
Samsudeen Sabraz Nawaz; Mohamed Buhary Fathima Sanjeetha; Ghadah Al Murshidi; Mohamed Ismail Mohamed Riyath; Fadhilah Bt Mat Yamin; Rusith Mohamed – Interactive Technology and Smart Education, 2024
Purpose: This study aims to investigate Sri Lankan Government university students' acceptance of Chat Generative Pretrained Transformer (ChatGPT) for educational purposes. Using the unified theory of acceptance and use of technology 2 (UTAUT2) model as the primary theoretical lens, this study incorporated personal innovativeness as both a…
Descriptors: Foreign Countries, Undergraduate Students, Artificial Intelligence, Computer Software
Priya Saha; Md. Shakhawat Hossain; Nirmal Chandra Roy; Abdullah Al Masud; Ruhul Amin – On the Horizon, 2025
Purpose: This study aims to evaluate students' intention and actual use (AU) of artificial intelligence (AI) tools' to discover how the power of AI influences learning and academic success. Design/methodology/approach: This paper used the unified theory of acceptance and use of technology (UTAUT) to develop a structural equation model (SEM) and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Student Behavior
Guiqin Liang; Chunsong Jiang; Qiuzhe Ping; Xinyi Jiang – Interactive Learning Environments, 2024
With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students…
Descriptors: Academic Achievement, Prediction, Engineering Education, Online Courses
Ruby S. Chanda; Vanishree Pabalkar; Sarika Sharma – Journal of Applied Research in Higher Education, 2024
Purpose: This study aims to understand and analyze the aspects influencing students' attitudes and behavior toward the use of metaverse in education. The metaverse is currently viewed as technology with immense prospects. However, the practice of the metaverse for educational motives is rarely deliberated. Design/methodology/approach: To assess…
Descriptors: Undergraduate Students, Graduate Students, Artificial Intelligence, Computer Simulation
Josef Šedlbauer; Jan Cincera; Martin Slavík; Adéla Hartlová – Journal of Computer Assisted Learning, 2024
Background: The emergence of Generative Artificial Intelligence has brought a number of ethical and practical issues to higher education. Solid experimental evidence is yet inadequate to set the functional rules for the new technology. Objectives: The objective of this study is to analyse the experience of undergraduate students' interaction with…
Descriptors: Artificial Intelligence, Higher Education, Undergraduate Students, Interaction
M. P. R. I. R. Silva; R. A. H. M. Rupasingha; B. T. G. S. Kumara – Technology, Pedagogy and Education, 2024
Today, in every academic institution as well as the university system assessing students' performance, identifying the uniqueness of each student and finding solutions to performance problems have become challenging issues. The main purpose of the study is to predict how student performance changes as a result of their behaviours, hobbies,…
Descriptors: Artificial Intelligence, Student Evaluation, Prediction, Recreational Activities
Dongmin Ma; Huma Akram; I-Hua Chen – International Review of Research in Open and Distributed Learning, 2024
Artificial intelligence (AI) has undergone considerable advancement in the contemporary period and represents an emerging technology in higher education. Cultural contexts significantly shape individuals' perceptions, attitudes, and behaviors, particularly in the realm of technology acceptance. By adopting a cross-cultural lens, this research…
Descriptors: Artificial Intelligence, Student Behavior, Intention, Student Attitudes
Hur, Paul; Lee, HaeJin; Bhat, Suma; Bosch, Nigel – International Educational Data Mining Society, 2022
Machine learning is a powerful method for predicting the outcomes of interactions with educational software, such as the grade a student is likely to receive. However, a predicted outcome alone provides little insight regarding how a student's experience should be personalized based on that outcome. In this paper, we explore a generalizable…
Descriptors: Artificial Intelligence, Individualized Instruction, College Mathematics, Statistics
Selin Urhan; Oguzhan Gençaslan; Senol Dost – Interactive Learning Environments, 2024
ChatGPT, an artificial intelligence-supported chatbot, has become a resource in the field of education for students across various disciplines. The conversation that unfolds based on the user-generated questions and ChatGPT's responses implies the emergence of an argumentation between the student and ChatGPT. In this study, the argumentation…
Descriptors: Persuasive Discourse, Calculus, Mathematical Concepts, Artificial Intelligence
Shuai He; Yu Lu – Interactive Learning Environments, 2024
Currently, generative AI has undergone rapid development. Numerous studies have attested to the benefits of Gen AI in programming, mathematics and other disciplines. However, since Gen AI mostly uses English as the intrinsic training parameter, it is more effective in facilitating the teaching of courses that use international common notation, but…
Descriptors: Instructional Effectiveness, Technology Uses in Education, Artificial Intelligence, Humanities Instruction
Cong Doanh Duong – Journal of Research in Innovative Teaching & Learning, 2024
Purpose: Although previous research has acknowledged the significance of comprehending the initial acceptance and adoption of ChatGPT in educational contexts, there has been relatively little focus on the user's intention to continue using ChatGPT or its continued usage. Therefore, the current study aims to investigate the students' continuance…
Descriptors: Intention, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Yang, Qi-Fan; Lian, Li-Wen; Zhao, Jia-Hua – International Journal of Educational Technology in Higher Education, 2023
According to previous studies, traditional laboratory safety courses are delivered in a classroom setting where the instructor teaches and the students listen and read the course materials passively. The course content is also uninspiring and dull. Additionally, the teaching period is spread out, which adds to the instructor's workload. As a…
Descriptors: Undergraduate Students, Gamification, Artificial Intelligence, Robotics
Vic Benuyenah; Senika Dewnarain – International Journal of Distance Education Technologies, 2024
This initial qualitative study used in-depth interview data from students to examine their perceptions of ChatGPT and intentions regarding using artificial intelligence (AI) in higher education. The students were sampled across business programmes at both the undergraduate and postgraduate levels at an International University in the UAE. As of…
Descriptors: Student Attitudes, Intention, Artificial Intelligence, Technology Uses in Education
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