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Guido Lang; Tamilla Triantoro; Jason H. Sharp – Journal of Information Systems Education, 2024
This study explores the potential of large language models (LLMs), specifically GPT-4 and Gemini, in generating teaching cases for information systems courses. A unique prompt for writing three different types of teaching cases such as a descriptive case, a normative case, and a project-based case on the same IS topic (i.e., the introduction of…
Descriptors: Computational Linguistics, Computer Software, Artificial Intelligence, Readability Formulas
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Nahatame, Shingo – Language Learning, 2021
Although text readability has traditionally been measured based on simple linguistic features, recent studies have employed natural language processing techniques to develop new readability formulas that better represent theoretical accounts of reading processes. This study evaluated the construct validity of different readability formulas,…
Descriptors: Readability, Natural Language Processing, Readability Formulas, Reading Processes
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Anna E. Mason; Jason L. G. Braasch; Daphne Greenberg; Erica D. Kessler; Laura K. Allen; Danielle S. McNamara – Reading Psychology, 2023
This study examined the extent to which prior beliefs and reading instructions impacted elements of a reader's mental representation of multiple texts. College students' beliefs about childhood vaccinations were assessed before reading two anti-vaccine and two pro-vaccine texts. Participants in the experimental condition read for the purpose of…
Descriptors: Immunization Programs, Misconceptions, Beliefs, Accuracy
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Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2018
While hierarchical machine learning approaches have been used to classify texts into different content areas, this approach has, to our knowledge, not been used in the automated assessment of text difficulty. This study compared the accuracy of four classification machine learning approaches (flat, one-vs-one, one-vs-all, and hierarchical) using…
Descriptors: Artificial Intelligence, Classification, Comparative Analysis, Prediction