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Gary D. Fisk – Teaching of Psychology, 2025
Introduction: Recent innovations in generative artificial intelligence (AI) technologies have led to an educational environment in which human authorship cannot be assumed, thereby posing a significant challenge to upholding academic integrity. Statement of the problem: Both humans and AI detection technologies have difficulty distinguishing…
Descriptors: Technology Uses in Education, Writing (Composition), Plagiarism, Identification
Chukwuemeka Ihekweazu; Bing Zhou; Elizabeth Adepeju Adelowo – Information Systems Education Journal, 2024
This study delves into the opportunities and challenges associated with the deployment of AI tools in the education sector. It systematically explores the potential benefits and risks inherent in utilizing these tools while specifically addressing the complexities of identifying and preventing academic dishonesty. Recognizing the ethical…
Descriptors: Ethics, Artificial Intelligence, Responsibility, Technology Uses in Education
Margaret A.L. Blackie – Teaching in Higher Education, 2024
Large language models such as ChatGPT can be seen as a major threat to reliable assessment in higher education. In this point of departure, I argue that these tools are a major game changer for society at large. Many of the jobs we now consider highly skilled are based on pattern recognition that can much more reliably be carried by fine-tuned…
Descriptors: Artificial Intelligence, Synchronous Communication, Science and Society, Evaluation
David W. Brown; Dean Jensen – International Society for Technology, Education, and Science, 2023
The growth of Artificial Intelligence (AI) chatbots has created a great deal of discussion in the education community. While many have gravitated towards the ability of these bots to make learning more interactive, others have grave concerns that student created essays, long used as a means of assessing the subject comprehension of students, may…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Software, Writing (Composition)
Heather Johnston; Rebecca F. Wells; Elizabeth M. Shanks; Timothy Boey; Bryony N. Parsons – International Journal for Educational Integrity, 2024
The aim of this project was to understand student perspectives on generative artificial intelligence (GAI) technologies such as Chat generative Pre-Trained Transformer (ChatGPT), in order to inform changes to the University of Liverpool Academic Integrity code of practice. The survey for this study was created by a library student team and vetted…
Descriptors: Artificial Intelligence, Higher Education, Student Attitudes, Universities
Sinclair, Jeanne; Jang, Eunice Eunhee; Rudzicz, Frank – Journal of Educational Psychology, 2021
Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…
Descriptors: Prediction, Reading Comprehension, Natural Language Processing, Speech Communication
Zhang, H.; Magooda, A.; Litman, D.; Correnti, R.; Wang, E.; Matsumura, L. C.; Howe, E.; Quintana, R. – Grantee Submission, 2019
Writing a good essay typically involves students revising an initial paper draft after receiving feedback. We present eRevise, a web-based writing and revising environment that uses natural language processing features generated for rubric-based essay scoring to trigger formative feedback messages regarding students' use of evidence in…
Descriptors: Formative Evaluation, Essays, Writing (Composition), Revision (Written Composition)
Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel – Computer Assisted Language Learning, 2016
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Descriptors: Discourse Analysis, Feedback (Response), Undergraduate Students, Accuracy
White, Elizabeth K. – ProQuest LLC, 2010
As the number of publications in the biomedical field continues its exponential increase, techniques for automatically summarizing information from this body of literature have become more diverse. In addition, the targets of summarization have become more subtle; initial work focused on extracting the factual assertions from full-text papers,…
Descriptors: Cues, Persuasive Discourse, Figurative Language, Natural Language Processing
Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine – CALICO Journal, 2009
We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary…
Descriptors: Feedback (Response), Sentences, Grammar, Writing Processes

Pasero, Robert; Sabatier, Paul – Computer Assisted Language Learning, 1998
Describes principles underlying ILLICO, a generic natural-language software tool for building larger applications for performing specific linguistic tasks such as analysis, synthesis, and guided composition. Shows to what extent this approach is relevant to the development of computer-assisted language-learning systems. (Author/VWL)
Descriptors: Computer Assisted Instruction, Computer Software, Natural Language Processing, Second Language Instruction