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Cecilia Ka Yuk Chan – Education and Information Technologies, 2025
This novel study explores "AI-giarism," an emergent form of academic dishonesty involving AI and plagiarism, within the higher education context. The objective of this study is to investigate students' perception of adopting generative AI for research and study purposes, and their understanding of traditional plagiarism and their…
Descriptors: Higher Education, College Students, Artificial Intelligence, Plagiarism
Reginald Lucien; Sanghoon Park – TechTrends: Linking Research and Practice to Improve Learning, 2024
The purpose of this study was to share the design and development case of Advising Virtual Assistant (AVA), a chatbot created to provide support in academic advising in higher education. By analyzing participants' usage data and chatbot performance, we attempted to understand how students engage with AVA to fulfill their advising needs. AVA…
Descriptors: Artificial Intelligence, Academic Advising, College Students, Program Effectiveness
Yiteng Zhang; Songyu Jiang – African Educational Research Journal, 2025
As artificial intelligence (AI) continues to be widely integrated into global economic, social, and environmental governance, its role in promoting sustainable entrepreneurship has garnered increasing scholarly attention. This research aims to uncover the predictors affecting students' pro-environmental personal norms (EPNs) and subjective norms…
Descriptors: Artificial Intelligence, Entrepreneurship, Sustainability, College Students
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
Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
Sourajit Ghosh; Md. Sarwar Kamal; Linkon Chowdhury; Biswarup Neogi; Nilanjan Dey; Robert Simon Sherratt – Education and Information Technologies, 2024
Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic…
Descriptors: Engineering Education, Artificial Intelligence, College Students, Student Interests
Shunan Zhang; Xiangying Zhao; Tong Zhou; Jang Hyun Kim – International Journal of Educational Technology in Higher Education, 2024
Although previous studies have highlighted the problematic artificial intelligence (AI) usage behaviors in educational contexts, such as overreliance on AI, no study has explored the antecedents and potential consequences that contribute to this problem. Therefore, this study investigates the causes and consequences of AI dependency using ChatGPT…
Descriptors: Artificial Intelligence, Self Efficacy, Anxiety, Expectation
Hakan Güldal; Emrah Oguzhan Dinçer – Education and Information Technologies, 2025
The purpose of this study was to investigate student perceptions and acceptance of a rule-based educational chatbot in higher education, employing the TAM (Technology Acceptance Model) framework. The researchers developed a rule-based chatbot for this purpose and examined the students' technology acceptance using qualitative research methods.…
Descriptors: Foreign Countries, Artificial Intelligence, College Students, Simulation
Susan Gardner Archambault – Information and Learning Sciences, 2024
Purpose: Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts' insights and perceptions of the…
Descriptors: Algorithms, Literacy, Artificial Intelligence, Mathematics Instruction
Lanqin Zheng; Yunchao Fan; Bodong Chen; Zichen Huang; LeiGao; Miaolang Long – Education and Information Technologies, 2024
Online collaborative learning has been broadly applied in higher education. However, learners face many challenges in collaborating with one another and coregulating their learning, leading to low group performance. To address the gaps, this study proposed an artificial intelligence (AI)-enabled feedback and feedforward approach that not only…
Descriptors: Artificial Intelligence, Feedback (Response), Electronic Learning, Cooperative Learning
Eyüp Yurt; Ismail Kasarci – International Journal of Technology in Education, 2024
This study introduces the Questionnaire of AI Use Motives (QAIUM), an instrument designed to measure motivation levels in individuals using artificial intelligence (AI) applications. Building on a theoretical framework that emphasizes motivation over dispositions and defines motivation as expectancy/value, the QAIUM aims to fill a research gap in…
Descriptors: Artificial Intelligence, Foreign Countries, College Students, Student Attitudes
Hacer Güner; Erkan Er; Gökhan Akçapinar; Mohammad Khalil – Educational Technology & Society, 2024
The revolutionary breakthrough of ChatGPT has significantly impacted various fields, including education. To produce maximum benefit in education from this innovative technology, it should be properly integrated into educational settings to create effective ways for learning while paying attention to ethical considerations. Understanding students'…
Descriptors: Artificial Intelligence, Technology Integration, Student Attitudes, College Students
Yibei Yin – International Journal of Web-Based Learning and Teaching Technologies, 2023
In order to study the big data of college students' employment, this paper takes the big data of college students' employment as the premise, analyzes the current employment data by establishing a DBN model, and puts forward relevant management measures, aiming to provide scientific basis for the management of graduates' employment data. The…
Descriptors: College Students, Student Employment, Data Analysis, Artificial Intelligence
Lihui Sun; Liang Zhou – Journal of Educational Computing Research, 2024
The use of generative artificial intelligence (Gen-AI) to assist college students in their studies has become a trend. However, there is no academic consensus on whether Gen-AI can enhance the academic achievement of college students. Using a meta-analytic approach, this study aims to investigate the effectiveness of Gen-AI in improving the…
Descriptors: Artificial Intelligence, Academic Achievement, College Students, Technology Uses in Education
Wali Khan Monib; Atika Qazi; Malissa Maria Mahmud – Education and Information Technologies, 2025
ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…
Descriptors: Student Attitudes, Student Experience, Artificial Intelligence, Natural Language Processing