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Wu Xu; Zhang Wei; Peng Yan – European Journal of Education, 2025
This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…
Descriptors: Artificial Intelligence, Natural Language Processing, Engineering Education, Majors (Students)
Valentine Joseph Owan; Ibrahim Abba Mohammed; Ahmed Bello; Tajudeen Ahmed Shittu – Contemporary Educational Technology, 2025
Despite the increasing interest in artificial intelligence technologies in education, there is a gap in understanding the factors influencing the adoption of ChatGPT among Nigerian higher education students. Research has not comprehensively explored these factors in the Nigerian context, leaving a significant gap in understanding technology…
Descriptors: Student Behavior, Foreign Countries, Artificial Intelligence, Natural Language Processing
Abdulrahman M. Al-Zahrani – SAGE Open, 2025
This study examines the impact of Artificial Intelligence (AI) chatbots on the loss of human connection and emotional support among higher education students. To do so, a quantitative research design is employed. An online survey questionnaire is distributed to a sample of 819 higher education students, assessing concerns about human connection,…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, College Students
Shamola Pramjeeth; Priya Ramgovind – New Directions for Teaching and Learning, 2025
While AI has the potential to streamline assessment development in higher education, there are concerns about its reliability, fairness, and potential to perpetuate bias. This study sought to understand the perceptions of academics and teaching and learning (T&L) specialists on the use of AI tools and large language models on assessment…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Educational Assessment
Qinghao Guan; Yangxi Han – Innovations in Education and Teaching International, 2025
As generative AI (GenAI) continues to permeate academia, distinguishing between student-authored essays and those by Large Language Models (LLMs) becomes crucial for maintaining academic integrity. This study conducted a survey on the ethical awareness of using generative AI tools among a group of STEM students (n=156). Also, we empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Intelligent Tutoring Systems
Yuan Chih Fu; Jin Hua Chen; Kai Chieh Cheng; Xuan Fen Yuan – Higher Education: The International Journal of Higher Education Research, 2024
Using data from approximately 342,000 course-taking records collected from 4406 college students enrolled at Taipei Tech during the 2009-2012 academic years, we examine the impact of multidisciplinarity on students' academic performance. Our study contributes to the literature in three ways. First, by applying natural language processing (NLP), we…
Descriptors: College Students, Interdisciplinary Approach, Academic Achievement, Natural Language Processing
Reima Al-Jarf – Online Submission, 2024
This study explores Arab university faculty's views on fully AI-generated assignments and research papers submitted by students, what reasons they give for their stance and how they react in this case. Surveys with a sample of 45 Arab instructors revealed that 98% do not accept AI-generated assignments and research papers from students at all.…
Descriptors: Assignments, Research Papers (Students), Foreign Countries, College Faculty
Nisar Ahmed Dahri; Noraffandy Yahaya; Waleed Mugahed Al-Rahmi – Education and Information Technologies, 2025
Enhancing student academic success and career readiness is important in the rapidly evolving educational field. This study investigates the influence of ChatGPT, an AI tool, on these outcomes using the Stimulus-Organism-Response (SOR) theory and constructs from the Technology Acceptance Model (TAM). The aim is to explore how ChatGPT impacts…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Career Readiness
Muhammad Farrukh Shahzad; Shuo Xu; Hira Zahid – Education and Information Technologies, 2025
Artificial Intelligence (AI) technologies have rapidly transformed the education sector and affect student learning performance, particularly in China, a burgeoning educational landscape. The development of generative artificial intelligence (AI) based technologies, such as chatbots and large language models (LLMs) like ChatGPT, has completely…
Descriptors: Artificial Intelligence, Technology Uses in Education, Academic Achievement, Self Efficacy
Navreet Kaur Rana – Higher Education for the Future, 2025
The article is an exploratory study assessing the stance selected higher education institutes (HEIs) have adopted regarding the usage of generative artificial intelligence (AI) applications in academic research. The HEIs are selected based on purposive sampling in order to showcase different stances they have adopted to curb plagiarism and uphold…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Plagiarism
Muna Barakat; Nesreen A. Salim; Malik Sallam – Open Praxis, 2025
Integration of ChatGPT into higher education requires assessing university educators' perspectives regarding this novel technology. This study aimed to validate a survey instrument specifically tailored to assess ChatGPT usability and acceptability among university educators based on the Technology Acceptance Model (TAM). The survey instrument…
Descriptors: College Faculty, Teacher Attitudes, Artificial Intelligence, Man Machine Systems
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
University Teachers at the Crossroads: Unpacking Their Intentions toward ChatGPT's Instructional Use
Muhammad Jaffar; Nazir Ahmed Jogezai; Abdul Rais Abdul Latiff; Fozia Ahmed Baloch; Gulab Khan Khilji – Journal of Applied Research in Higher Education, 2025
Purpose: The objective of this study was to elucidate the intentions of university teachers regarding the utilization of ChatGPT for instructional purposes. Design/methodology/approach: In this cross-sectional quantitative research, data were collected through an online survey tool from 493 university teachers across Pakistan. Findings: The…
Descriptors: College Faculty, Teacher Attitudes, Artificial Intelligence, Man Machine Systems
Maria Eleftheriou; Muhammad Ahmer; Daniel Fredrick – Contemporary Educational Technology, 2025
Like many student writing centers, the American University of Sharjah Writing Center is seeing a rise in student reliance upon generative AI (GenAI) tools, which are artificial intelligence systems capable of generating human-like text. Peer tutors frequently seek guidance on how to approach student papers involving GenAI tools such as ChatGPT,…
Descriptors: Laboratories, Writing (Composition), Artificial Intelligence, Man Machine Systems
Ahmet Yusuf Cevher; Serkan Yildirim – Turkish Online Journal of Distance Education, 2025
This study investigates the impact and role of an instructional chatbot, ARUChatbot, in a distance education setting. Using a sequential explanatory mixed-methods design, the research involved 130 students from Ardahan University's Basic Information Technologies course. Participants were selected through purposive sampling. Quantitative data were…
Descriptors: Distance Education, Artificial Intelligence, Man Machine Systems, Natural Language Processing

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