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Olena Bolgova; Paul Ganguly; Volodymyr Mavrych – Anatomical Sciences Education, 2025
Integrating artificial intelligence, particularly large language models (LLMs), into medical education represents a significant new step in how medical knowledge is accessed, processed, and evaluated. The objective of this study was to conduct a comprehensive analysis comparing the performance of advanced LLM chatbots in different topics of…
Descriptors: Comparative Analysis, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Adam Lockwood; Ryan Farmer; Gagan Shergill; Nicholas Benson; Kacey Gilbert – Journal of Psychoeducational Assessment, 2025
This study examines the effectiveness of artificial intelligence (AI) in psychological report writing by comparing reports generated by human psychologists with those produced by OpenAI's Generative Pre-trained Transformer Version 4 (ChatGPT-4). A total of 249 licensed psychologists evaluated the reports based on overall quality, readability,…
Descriptors: Man Machine Systems, Artificial Intelligence, Psychological Evaluation, Reports
Ibrahim Abba Mohammed; Ahmed Bello; Bala Ayuba – Education and Information Technologies, 2025
In spite of the emergence of studies seeking to integrate chatbot into education, there is a wide literature gap in the Nigerian contexts. While most studies focus on the design and development of chatbots, there exists a very scarce literature on the effect of ChatGPT chatbot on students' achievement. To address this gap, this study checked the…
Descriptors: Natural Language Processing, Artificial Intelligence, Academic Achievement, Computer Science Education
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
Kyle, Kristopher; Crossley, Scott A.; McNamara, Danielle S. – Language Testing, 2016
This study explores the construct validity of speaking tasks included in the TOEFL iBT (e.g., integrated and independent speaking tasks). Specifically, advanced natural language processing (NLP) tools, MANOVA difference statistics, and discriminant function analyses (DFA) are used to assess the degree to which and in what ways responses to these…
Descriptors: Construct Validity, Natural Language Processing, Speech Skills, Speech Acts

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