Artificial intelligence and the future of learning and assessment in agricultural and applied economics

Author:

Shear Hannah E.1,Britton Logan L.2ORCID,Aleks Schaefer K.1,Thapa Bhawna1,Bergtold Jason S.2

Affiliation:

1. Department of Agricultural Economics Oklahoma State University Stillwater Oklahoma USA

2. Department of Agricultural Economics Kansas State University Manhattan Kansas USA

Abstract

AbstractUsing a repository of historical student responses to an actual course‐assigned essay prompt and a series of artificial intelligence (AI)‐generated responses to the same prompt, we conduct a single‐blind, randomized experiment to evaluate the performance of AI in agricultural and applied economics education. Further, we assess instructors' ability to detect the use of AI. We find that AI‐generated responses to the essay received statistically significantly higher scores than those of the average student. Instructors who had previous exposure to dialog‐based AI were 13 times more likely to accurately detect AI‐generated essays than instructors without previous exposure to the technology.

Publisher

Wiley

Reference34 articles.

1. Aiyappa Rachith JisunAn HaewoonKwak andYong‐YeolAhn.2023. “Can We Trust the Evaluation on ChatGPT?”arXiv preprint arXiv:2303.12767. [Preprint].https://doi.org/10.48550/arXiv.2303.12767

2. ChatGPT as an Educational Tool: Opportunities, Challenges, and Recommendations for Communication, Business Writing, and Composition Courses;AlAfnan Mohammad Awad;Journal of Artificial Intelligence and Technology,2023

3. Earnings of Kansas State University Agriculture Graduates: 1978–88

4. Agricultural Graduate Earnings: The Impacts of College, Career, and Gender

5. Inferences from logistic regression models in the presence of small samples, rare events, nonlinearity, and multicollinearity with observational data;Bergtold Jason S.;Journal of Applied Statistics,2017

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