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Mike Perkins; Jasper Roe; Binh H. Vu; Darius Postma; Don Hickerson; James McGaughran; Huy Q. Khuat – International Journal of Educational Technology in Higher Education, 2024
This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content modified to evade detection (n = 805). We compare these detectors to assess their reliability in identifying AI-generated text in educational settings, where they are increasingly used to address academic integrity…
Descriptors: Artificial Intelligence, Inclusion, Computer Software, Word Processing
Abdullahi Yusuf; Nasrin Pervin; Marcos Román-González – International Journal of Educational Technology in Higher Education, 2024
In recent years, higher education (HE) globally has witnessed extensive adoption of technology, particularly in teaching and research. The emergence of generative Artificial Intelligence (GenAI) further accelerates this trend. However, the increasing sophistication of GenAI tools has raised concerns about their potential to automate teaching and…
Descriptors: Artificial Intelligence, Educational Trends, Futures (of Society), Higher Education
Zhou, Wenyi; Simpson, Elizabeth; Domizi, Denise Pinette – International Journal of Teaching and Learning in Higher Education, 2012
Google Docs, an online word processing application, is a promising tool for collaborative learning. However, many college instructors and students lack knowledge to effectively use Google Docs to enhance teaching and learning. Goals of this study include (1) assessing the effectiveness of using Google Docs in an out-of-class collaborative writing…
Descriptors: Assignments, Word Processing, Collaborative Writing, Undergraduate Students