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Amal Abdullah Alibrahim – South African Journal of Education, 2024
After ChatGPT was released late in 2022, many arguments about its accuracy and use in education arose. In this article, I seek to provide evidence of the accuracy and validity of ChatGPT's responses to users' queries in education by applying a systematic review methodology to analyse publications in specific databases following PRISMA guidelines…
Descriptors: Artificial Intelligence, Technology Uses in Education, Reliability, Natural Language Processing
Adam B. Lockwood; Joshua Castleberry – Contemporary School Psychology, 2025
Technological Advances in Artificial Intelligence (AI) have Brought forth the Potential for Models to Assist in Academic Writing. However, Concerns Regarding the Accuracy, Reliability, and Impact of AI in Academic Writing have been Raised. This Study Examined the Capabilities of GPT-4, a state-of-the-art AI Language Model, in Writing an American…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Writing (Composition)
Ferdiye Çobanogullari – The EUROCALL Review, 2024
This literature review delves into the applications and implications of ChatGPT, an artificial intelligence-driven chatbot, in educational settings. As technology continues to permeate the field of education, ongoing debates persist regarding the potential impact on learners' critical thinking skills and the evolving role of educators. Instead of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Educational Strategies
Blanka Klimova; Victor Paiva Luz de Campos – Cogent Education, 2024
At present, ChatGPT is penetrating all spheres of human activities, and especially education is no exception. The purpose of this exploratory study is to examine the potentials and pitfalls of using ChatGPT for academic purposes among university students, as well as provide relevant pedagogical implications for its use in academia. The methodology…
Descriptors: Undergraduate Students, Undergraduate Study, Student Attitudes, Artificial Intelligence
Crossley, Scott A.; Kyle, Kristopher; McNamara, Danielle S. – Grantee Submission, 2015
This study investigates the relative efficacy of using linguistic micro-features, the aggregation of such features, and a combination of micro-features and aggregated features in developing automatic essay scoring (AES) models. Although the use of aggregated features is widespread in AES systems (e.g., e-rater; Intellimetric), very little…
Descriptors: Essays, Scoring, Feedback (Response), Writing Evaluation
Cook, Anne E.; O'Brien, Edward J. – Discourse Processes: A Multidisciplinary Journal, 2014
Previous text comprehension studies using the contradiction paradigm primarily tested assumptions of the activation mechanism involved in reading. However, the nature of the contradiction in such studies relied on validation of information in readers' general world knowledge. We directly tested this validation process by varying the strength of…
Descriptors: Reading Comprehension, Validity, Reliability, Undergraduate Students