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Jessica M. Lammert; Angela C. Roberts; Ken McRae; Laura J. Batterink; Blake E. Butler – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification…
Descriptors: Identification, Natural Language Processing, Artificial Intelligence, Barriers
Maira Klyshbekova; Pamela Abbott – Electronic Journal of e-Learning, 2024
There is a current debate about the extent to which ChatGPT, a natural language AI chatbot, can disrupt processes in higher education settings. The chatbot is capable of not only answering queries in a human-like way within seconds but can also provide long tracts of texts which can be in the form of essays, emails, and coding. In this study, in…
Descriptors: Artificial Intelligence, Higher Education, Technology Uses in Education, Evaluation Methods
Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
Mohammadreza Farrokhnia; Seyyed Kazem Banihashem; Omid Noroozi; Arjen Wals – Innovations in Education and Teaching International, 2024
ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT's strengths and weaknesses and to discuss its opportunities for and threats to education. The strengths include using a sophisticated natural language model to generate plausible answers,…
Descriptors: Artificial Intelligence, Synchronous Communication, Computer Software, Technology Uses in Education
Ibrahim Adeshola; Adeola Praise Adepoju – Interactive Learning Environments, 2024
The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…
Descriptors: Opportunities, Barriers, Artificial Intelligence, Natural Language Processing
Matthew Landers – Higher Education for the Future, 2025
This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…
Descriptors: Ethics, Cheating, Plagiarism, Artificial Intelligence
Jacob Holster – Music Educators Journal, 2024
ChatGPT is emerging as a formidable asset for music educators, poised to enhance student engagement, refine assessment methods, and automate repetitive tasks related to music teaching. The core of this perspective revolves around the use of custom prompt templates that support individualized and reflexive teaching practices. The broader…
Descriptors: Music Education, Artificial Intelligence, Natural Language Processing, Man Machine Systems
Edmund De Leon Evangelista – Contemporary Educational Technology, 2025
The rapid advancement of artificial intelligence (AI) technologies, particularly OpenAI's ChatGPT, has significantly impacted higher education institutions (HEIs), offering opportunities and challenges. While these tools enhance personalized learning and content generation, they threaten academic integrity, especially in assessment environments.…
Descriptors: Artificial Intelligence, Integrity, Educational Strategies, Natural Language Processing
Mayer, Christian W. F.; Ludwig, Sabrina; Brandt, Steffen – Journal of Research on Technology in Education, 2023
This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…
Descriptors: Prompting, Classification, Artificial Intelligence, Natural Language Processing
Shalva Kikalishvili – Interactive Learning Environments, 2024
Presented study seeks to examine the potential applications of the OpenAI language model, GPT-3, within the realm of education. Specifically, the inquiry focuses on the feasibility of utilizing GPT-3 to generate essays based on customized prompts. To this end, the experimentation involved providing GPT-3 with tailored prompts derived from diverse…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Opportunities
Jacob Whitehill; Jennifer LoCasale-Crouch – Journal of Educational Data Mining, 2024
With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate "Instructional Support" domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning…
Descriptors: Artificial Intelligence, Teacher Evaluation, Models, Transcripts (Written Records)
Jae Q. J. Liu; Kelvin T. K. Hui; Fadi Al Zoubi; Zing Z. X. Zhou; Dino Samartzis; Curtis C. H. Yu; Jeremy R. Chang; Arnold Y. L. Wong – International Journal for Educational Integrity, 2024
The application of artificial intelligence (AI) in academic writing has raised concerns regarding accuracy, ethics, and scientific rigour. Some AI content detectors may not accurately identify AI-generated texts, especially those that have undergone paraphrasing. Therefore, there is a pressing need for efficacious approaches or guidelines to…
Descriptors: Artificial Intelligence, Investigations, Identification, Human Factors Engineering
Morgan J. Clark; Micke Reynders; Thomas A. Holme – Journal of Chemical Education, 2024
In the field of education, ChatGPT has become a topic of debate for its usefulness as a learning tool. This article focuses on non-science majors' (n = 29) perceptions of a ChatGPT enabled final exam, where, prior to the exam, students wrote papers on science and sustainability and, during the final exam, students were asked to compare their paper…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Tests
Hanbing Xue; Weishan Liu – SAGE Open, 2025
The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge…
Descriptors: Bibliometrics, Natural Language Processing, Technology Uses in Education, Educational Trends
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
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