Figure-Based Approach in Creating ChatGPT-4o-Resistant Multiple-Choice Questions for Introductory Biology Courses: An Instructional Guide

Kyeng Gea Lee, Mark J Lee, Soo Jung Lee
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Abstract


Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, text-based questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of online assessments. In particular, it has been reported that large language models, like ChatGPT-4o, show high performance on text-based questions. In comparison, ChatGPT-4o exhibited significantly reduced performance on figure-based questions in our study. In an effort to counter the recent encroachment of ChatGPT-4o into online assessment, we propose a step-by-step instructional guide for a method in creating figure-based multiple-choice questions that are resistant to ChatGPT-4o. This involves generation of a ChatGPT-4o-resistant figure, writing the question text based on it, and evaluating the final question on ChatGPT-4o. If successfully created, ChatGPT-4o response could be subject to random guessing. Our results showcase four representative examples for introductory biology courses and illustrate a systematic approach to compose questions based on qualitative analysis of ChatGPT-4o responses. In combination with other assessment methods, our method aims to serve as a tool to alleviate the current challenge that educators face for online assessments.

Keywords


ChatGPT-4o, Figure-based, Multiple-choice, Online assessment, Biology education

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References


Lee, K.G., Lee, M.J., & Lee, S.J. (2024). Figure-based approach in creating ChatGPT-4o-resistant multiple-choice questions for introductory biology courses: An instructional guide. International Journal of Technology in Education and Science (IJTES), 8(4), 689-709. https://doi.org/10.46328/ijtes.589




DOI: https://doi.org/10.46328/ijtes.589

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International Journal of Technology in Education & Science (IJTES)-ISSN: 2651-5369


 
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.