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Teaching Approaches to Ethical Generative Artificial Intelligence Use in Agricultural Economics Classrooms

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Listed:
  • Petersonn-Wilhelm, Bailey
  • Day, Merri E.
  • Sharma, Priyanka
  • Kim, Jiyeon
  • Hobbs, Lonnie Jr.
  • Britton, Logan L.

Abstract

With the introduction of generative artificial intelligence (AI)-powered tools, such as ChatGPT, Google Gemini, Copilot, and others, professionals and students in higher education institutions have altered their approaches to teaching and learning. While varying opinions exist on the implementation of AI in higher education, there is need for both students and educators to understand the ethical dimensions of its use for both students and educators. This article demonstrates a three-module instructional approach for integrating generative AI and its ethical use into undergraduate coursework. The modules include (1) AI introduction, (2) how to use AI, and (3) ethical dimensions. The three-module approach was implemented in a first-year, computer-based course designed to develop skills for agribusiness decision making. Students reported improved understanding of generative AI and its ethical implications after completing the lecture, irrespective of section or class level. This modular framework offers a practical guide for instructors aiming to integrate ethical AI education into agricultural economics curricula.

Suggested Citation

  • Petersonn-Wilhelm, Bailey & Day, Merri E. & Sharma, Priyanka & Kim, Jiyeon & Hobbs, Lonnie Jr. & Britton, Logan L., 2026. "Teaching Approaches to Ethical Generative Artificial Intelligence Use in Agricultural Economics Classrooms," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 8(2).
    • Handle: RePEc:ags:aaeatr:410071
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    File URL: https://ageconsearch.umn.edu/record/410071/files/Article%2010%208%282%29%20AETR_2026_0303%20Proof%20Final.pdf
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    References listed on IDEAS

    as
    1. Monika Hooda & Chhavi Rana & Omdev Dahiya & Ali Rizwan & Md Shamim Hossain & Vijay Kumar, 2022. "Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-19, May.
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