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Sasha Nikolic; Isabelle Wentworth; Lynn Sheridan; Simon Moss; Elisabeth Duursma; Rachel A. Jones; Montserrat Ros; Rebekkah Middleton – Australasian Journal of Educational Technology, 2024
The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators and institutions have embraced AI and generative AI (GenAI), other individuals remain cautious. This systematic literature review explored teaching…
Descriptors: College Faculty, Teacher Attitudes, Intention, Teacher Behavior
Yun Dai; Sichen Lai; Cher Ping Lim; Ang Liu – Australasian Journal of Educational Technology, 2023
As artificial intelligence (AI) continues to evolve, its impact on academic environments, especially in postgraduate research supervision, becomes increasingly significant. This study explored the impact of ChatGPT, an advanced AI conversational model, on five dimensions of research supervision: functional, enculturation, critical thinking,…
Descriptors: Artificial Intelligence, Supervision, Graduate Students, Student Attitudes
Michael Cowling; Joseph Crawford; Kelly-Ann Allen; Michael Wehmeyer – Australasian Journal of Educational Technology, 2023
ChatGPT and other artificial intelligence (AI) and large language models (LLMs) have hit higher education by storm. Much of the research focuses on how this -- and similar -- tools can be leveraged for effective education of undergraduate coursework students. In this study, we explore the emerging benefits and limitations of ChatGPT and LLMs in…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
Bünyami Kayali; Mehmet Yavuz; Sener Balat; Mücahit Çalisan – Australasian Journal of Educational Technology, 2023
The purpose of this study was to determine university students' experiences with the use of ChatGPT in online courses. The sample consisted of 84 associate degree students from a state university in Turkey. A multi-method approach was used in the study. Although quantitative data were collected using the Chatbot Usability Scale, qualitative data…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Electronic Learning
Thanh Pham; Binh Nguyen; Son Ha; Thanh Nguyen Ngoc – Australasian Journal of Educational Technology, 2023
This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that…
Descriptors: Artificial Intelligence, Engineering Education, Universities, Foreign Countries
Xiaojing Weng; Qi Xia; Mingyue Gu; Kumaran Rajaram; Thomas K. F. Chiu – Australasian Journal of Educational Technology, 2024
Generative artificial intelligence (GenAI) impacts higher education assessment and learning outcomes, which are closely related and intertwined. Literature suggests that educators and researchers have many varied concerns regarding student assessment in the higher education GenAI context, such as how to assess students' learning and the new…
Descriptors: Evaluation Methods, Outcomes of Education, Artificial Intelligence, Natural Language Processing
Hai-Feng Li – Australasian Journal of Educational Technology, 2023
In recent decades, flipped learning has been adopted by teachers to improve learning achievement. However, it is challenging to provide all students with instant personalised guidance at the same time. To address this gap, based on Chat Generative Pre-trained Transformer (ChatGPT) and the learning scaffolding theory, I developed a ChatGPT-based…
Descriptors: Flipped Classroom, Artificial Intelligence, Instructional Effectiveness, Technology Uses in Education
Christopher Dann; Petrea Redmond; Melissa Fanshawe; Alice Brown; Seyum Getenet; Thanveer Shaik; Xiaohui Tao; Linda Galligan; Yan Li – Australasian Journal of Educational Technology, 2024
Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…
Descriptors: Artificial Intelligence, Learner Engagement, Feedback (Response), Decision Making