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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
Varank, Ilhan; Erkoç, M. Fatih; Büyükimdat, Meryem Köskeroglu; Aktas, Mehmet; Yeni, Sabiha; Adigüzel, Tufan; Cömert, Zafer; Esgin, Esad – EURASIA Journal of Mathematics, Science & Technology Education, 2014
The purpose of this study was to investigate the effectiveness of an online automated evaluation and feedback system that assessed students' word processing assignments prepared with Microsoft Office Word. The participants of the study were 119 undergraduate teacher education students, 86 of whom were female and 32 were male, enrolled in different…
Descriptors: Computer Literacy, Introductory Courses, Student Evaluation, Feedback (Response)
Mogey, Nora; Paterson, Jessie; Burk, John; Purcell, Michael – ALT-J: Research in Learning Technology, 2010
Students at the University of Edinburgh do almost all their work on computers, but at the end of the semester they are examined by handwritten essays. Intuitively it would be appealing to allow students the choice of handwriting or typing, but this raises a concern that perhaps this might not be "fair"--that the choice a student makes,…
Descriptors: Handwriting, Essay Tests, Interrater Reliability, Grading