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Chelsea Wilkinson; Michelle Leanne Oppert; Mikaela Sian Owen – Australasian Journal of Educational Technology, 2024
ChatGPT, at the forefront of artificial intelligence advancement, has caused excitement and scepticism within academic spheres due to its potential to affect academic processes. Understanding attitudes towards ChatGPT could help manage expectations and concerns for ChatGPT in academia, predict behaviour and inform policy. This study aimed to…
Descriptors: College Faculty, Teacher Attitudes, Artificial Intelligence, Computer Software
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Tangalakis, Kathy; Julien, Brianna L.; Lexis, Louise; Hryciw, Deanne H.; Thomas, Colleen J.; Husaric, Maja; Towstoless, Michelle; MacKinnon, Philip J.; Miao, Yuan; Hayes, Alan – Advances in Physiology Education, 2023
Core concepts in physiology, designed by physiology educators to promote improved learning and teaching, have existed for over a decade. This study aimed to investigate the extent to which a set of 15 core concepts of physiology (developed by Michael and McFarland, U.S.-based educators) are reflected in the learning outcomes (LOs) of units…
Descriptors: Concept Formation, Scientific Concepts, Physiology, Science Instruction
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Ekaterina Tour; Marianne Turner; Anne Keary; Khanh-Linh Tran-Dang – Language and Education, 2024
It has been widely recognised that plurilingual pedagogy offers many benefits both for language learning and learning in general. However, in contexts where the linguistic profile of students is diverse, it can still be challenging for teachers to view working with the language resources of their students as feasible. In this article, we discuss…
Descriptors: Multilingualism, Multiple Literacies, Correlation, Teaching Methods
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Abd-Elaal, El-Sayed; Gamage, Sithara H. P. W.; Mills, Julie E. – European Journal of Engineering Education, 2022
Authentic writing is an important aspect in education and research. Unfortunately, academic misconduct occurs among students and researchers. Consequently, written articles undergo certain detection measures and most teaching and research institutions use a range of software to detect plagiarism. However, state-of-the-art Automatic Article…
Descriptors: College Faculty, Identification, Computational Linguistics, Computer Software
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Luck, Jo-Anne; Chugh, Ritesh; Turnbull, Darren; Rytas Pember, Edward – Higher Education Research and Development, 2022
Increasing incidents of academic dishonesty are a problem for universities globally. The traditional approach to dealing with academic dishonesty has been to detect and punish, which may not be the best solution. This study explored the perceptions of sessional teaching staff (a growing but often neglected workforce) on academic integrity and…
Descriptors: Integrity, Cheating, Universities, Teacher Attitudes
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Cunningham-Nelson, Samuel; Baktashmotlagh, Mahsa; Boles, Wageeh – IEEE Transactions on Education, 2019
Contribution: An automated methodology that provides visualizations of students' free text comments from course satisfaction surveys. Focusing on sentiment, these visualizations reveal learning and teaching aspects of the course that either may require improvement or are performing well. They provide educators with a simple, systematic way to…
Descriptors: Student Attitudes, Visualization, Course Evaluation, Teaching Methods
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Dinneen, Cara – English Australia Journal, 2021
This article considers the challenges heralded by digital technology in relation to the management of academic integrity on high-stakes Direct Entry English Programs in Australia. Firstly, a number of the ways in which students are using digital tools to complete assignment writing are examined. Secondly, findings from a review of academic…
Descriptors: Phrase Structure, Integrity, Barriers, Information Technology
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Kaktinš, Louise – Ethics and Education, 2019
Australian universities are grappling with the challenge of plagiarism among students, particularly international students, with a reliance on software such as Turnitin. Measuring plagiarism in this way has limitations, with consequences for the internalisation of academic integrity by international students. An appraisal of such software…
Descriptors: Computer Software, Computational Linguistics, Writing Evaluation, Cheating
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Conroy, Mark A. – Australasian Journal of Educational Technology, 2010
Many excellent corpus-based language learning resources (e.g., concordancers) have been freely available on the Internet for some time. Google assisted language learning (GALL) is also gaining increasing acceptance. These tools are a potential resource for English as an additional language (EAL) university students who want to independently…
Descriptors: Foreign Countries, Internet, Computer Software, Computer Uses in Education