The DOI matches its Crossref record; 34 of the 35 references it cites were found in a registry or an index, and 1 are not checked yet.
ChatGPT has Aced the Test of Understanding in College Economics: Now What?
Open accessAbstract
The Test of Understanding in College Economics (TUCE) is a standardized test of economics knowledge performed in the United States which primarily targets principles-level understanding. We asked ChatGPT to complete the TUCE. ChatGPT ranked in the 91st percentile for Microeconomics and the 99th percentile for Macroeconomics when compared to students who take the TUCE exam at the end of their principles course. The results show that ChatGPT is capable of providing answers that exceed the mean responses of students across all institutions. The emergence of artificial intelligence presents a significant challenge to traditional assessment methods in higher education. An important implication of this finding is that educators will likely need to redesign their curriculum in at least one of the following three ways: reintroduce proctored, in-person assessments; augment learning with chatbots; and/or increase the prevalence of experiential learning projects that artificial intelligence struggles to replicate well.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Generative AI, such as OpenAI’s ChatGPT, has rapidly emerged as a disruptive technology capable of achieving human-level performance on a broad range of tasks (1–5).”
From Generative AI without guardrails can harm learning: Evidence from high school mathematics (2025) · cites this paper as [4]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In economics education, Geerling et al. (2023) demonstrate that ChatGPT scores in the 90th percentile on standardized exams, showing how easily it can produce high-quality academic work without genuine student engagement.”
From Generative AI-Enhanced Oral Exams in Economics Education (2026) · cites this paper as Geerling et al. (2023)
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“An alternative to using GenAI in education, beyond exams and assignment writing, is building supportive and engaging learning environments that complement traditional pedagogical methods. This proposition can provide a dynamic and interactive platform to foster knowledge acquisition and acknowledge the existing concerns on plagiarism and academic integrity [8,16].”
From Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment (2024) · cites this paper as [8]
The cited source says what the claim attributes to it.
In the citing paper
“Some recent research results show that ChatGPT can provide answers in exams that exceed the mean responses of students, which poses a significant challenge to traditional assessment methods in HE [8].”
From Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment (2024) · cites this paper as [8]
In the citing paper
“Related research shows that ChatGPT performs well in exams in disciplines such as engineering (Uhlig et al., 2023), economics (Geerling et al., 2023), medicine (Currie et al., 2023), and geography (Stutz et al., 2023), indicating that the issue of academic integrity in higher education is facing unprecedented challenges.”
From A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education (2024) · cites this paper as Geerling et al., 2023
In the citing paper
“Moreover, ChatGPT offers opportunities for authentic assessment by challenging students’ beliefs and critical thinking (Crawford et al., 2023; Currie et al., 2023; Geerling et al., 2023).”
From A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education (2024) · cites this paper as Geerling et al., 2023
In the citing paper
“as traditional examinations and assignments may become obsolete due to AI-generated content (Geerling et al., 2023; Gorichanaz, 2023).”
From A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education (2024) · cites this paper as Geerling et al., 2023
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023) · JMIR Medical Education · doi:10.2196/45312 · Cited by 2,078
Hill, J., Randolph Ford, W., & Farreras, I. G. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.02.026 · Cited by 856
Huang, W., Hew, K. F., & Fryer, L. K. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12610 · Cited by 830
The design and implementation of Xiaoice, an empathetic social chatbot
Zhou, L., Gao, J., Li, D., & Shum, H.-Y. (2020) · Computational Linguistics · doi:10.1162/coli_a_00368 · Cited by 777
Chatbots for learning: A review of educational chatbots for the Facebook Messenger
Smutny, P., & Schreiberova, P. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103862 · Cited by 770
ChatGPT Goes to Law SchoolPreprint
Choi, J. H., Hickman, K. E., Monahan, A., & Schwarcz, D. B. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4335905 · Cited by 565
Are We There Yet? - A Systematic Literature Review on Chatbots in Education
Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler, H. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.654924 · Cited by 557 · cited 1×
“Because of its scalability and adaptability, it offers unique possibilities as a communication and information tool for digital learning (Wollny et al., 2021).”
BackgroundA review of opportunities and challenges of chatbots in education
Hwang, G.-J., & Chang, C.-Y. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.1952615 · Cited by 530
Chatbots and the new world of HCI
Følstad, A., & Brandtzæg, P. B. (2017) · interactions · doi:10.1145/3085558 · Cited by 520
Education and technology: Key issues and debates
Teräs, M. (2022) · International Review of Education · doi:10.1007/s11159-022-09971-9 · Cited by 235
Advantages and constraints of a hybrid model K–12 e-learning assistant chatbot
Wu, E. H.-K., Lin, C.-H., Ou, Y.-Y., Liu, C.-Z., Wang, W.-K., & Chao, C.-Y. (2020) · IEEE Access · doi:10.1109/access.2020.2988252 · Cited by 205
Emerson, T. L. N., & Taylor, B. A. (2004) · Southern Economic Journal · doi:10.2307/4135338 · Cited by 198
Multimedia-Assisted Language Learning
(2020) · Multimedia-Assisted Language Learning · doi:10.15702/mall · Cited by 193
New Modes of Learning Enabled by AI Chatbots: Three Methods and Assignments
Mollick, E. R., & Mollick, L. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4300783 · Cited by 176 · cited 1×
“…challenges in learning, including improving transfer of knowledge, dispelling misconceptions, and promoting critical thinking skills among students (Mollick & Mollick, 2022), and can be utilized as an effective teaching assistant in online learning environments by helping to enhance students ’…”
BackgroundGoel, A. K., & Polepeddi, L. (2018) · Routledge eBooks · doi:10.4324/9781351186193-7 · Cited by 146
Integrating Selectional Constraints and Subcategorization Frames in a Dependency Parser
(2016) · HAL · doi:10.1162/coli · Cited by 135
Contract cheating & the market in essays
Rigby, D., Burton, M. P., Balcombe, K., Bateman, I. J., & Mulatu, A. (2014) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2014.12.019 · Cited by 128
How Do High School Students Justify Internet Plagiarism?
Sisti, D. A. (2007) · Ethics & Behavior · doi:10.1080/10508420701519163 · Cited by 117
Plagiarism: Why is it such a big issue for medical writers?
Das, N., & Panjabi, M. (2011) · Perspectives in Clinical Research · doi:10.4103/2229-3485.80370 · Cited by 99
TECHNOLOGY CHALLENGES AND OPPORTUNITIES FACING MARKETING EDUCATION
Ferrell, O. C., & Ferrell, L. K. (2020) · Marketing Education Review · doi:10.1080/10528008.2020.1718510 · Cited by 87
AI and the FCI: Can ChatGPT Project an Understanding of Introductory Physics?Preprint
West, C. G. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2303.01067 · Cited by 85
The economics instructor’s toolbox
Picault, J. (2019) · International Review of Economics Education · doi:10.1016/j.iree.2019.01.001 · Cited by 75
The Test of Understanding of College Economics
Walstad, W. B., & Rebeck, K. (2008) · American Economic Review · doi:10.1257/aer.98.2.547 · Cited by 71
Schmulian, A., & Coetzee, S. A. (2018) · British Journal of Educational Technology · doi:10.1111/bjet.12723 · Cited by 48
Modern Cheating Techniques, Their Adverse Effects on Engineering Education and Preventions
Srikanth, M., & Asmatulu, R. (2014) · International Journal of Mechanical Engineering Education · doi:10.7227/ijmee.0005 · Cited by 46
How to Learn and Teach Economics with Large Language Models, Including GPT
Cowen, T., & Tabarrok, A. T. (2023) · doi:10.2139/ssrn.4391863 · Cited by 35
Is Interactive/Active Learning Superior to Traditional Lecturing in Economics Courses?
Dorestani, A. (2005) · International Journal of Ethics and Systems · doi:10.1108/eb018897 · Cited by 29
Boyle, A., & Goffe, W. L. (2018) · AEA Papers and Proceedings · doi:10.1257/pandp.20181052 · Cited by 25
Academic Integrity in the Technology-Driven Education Era
Cojocariu, V.-M., & Mareș, G. (2021) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-981-16-1951-9_1 · Cited by 20
Best, L. M., & Shelley, D. J. (2018) · International Journal of Information and Communication Technology Education · doi:10.4018/ijicte.2018070101 · Cited by 16
Looking for innovative pedagogy? An online economics instructor’s toolbox
Picault, J. (2021) · The Journal of Economic Education · doi:10.1080/00220485.2021.1887024 · Cited by 15
Smith, B. O., & Wagner, J. (2018) · The Journal of Economic Education · doi:10.1080/00220485.2018.1500959 · Cited by 14
Artificial Intelligence in Teaching and Learning: An Introduction
Stubbs, M., & Piddock, P. (1985) · PLET Programmed Learning & Educational Technology · doi:10.1080/1355800850220207 · Cited by 12
Music Then and Now: Using Technology to Build a Lyric Animation Module
Geerling, W., Mateer, G. D., & O’Roark, B. (2019) · The American Economist · doi:10.1177/0569434519889063 · Cited by 12
Self-citationAn exploration of Robert Frank's ‘The Economic Naturalist’ in the classroom
Geerling, W. (2013) · International Review of Economics Education · doi:10.1016/j.iree.2013.04.008 · Cited by 5
Self-citation
Research works printed but not linked: 9
- Al-Bahrani A., 2016, Journal of Economics and Finance Education, 15, 1
- Batane T., 2010, Journal of Educational Technology and Society, 13, 1
- Gecker J., 2023, Some educators embrace ChatGPT as a new teaching tool
- Lancaster T., 2007, Higher Education Academy for Information and Computer Sciences, 1
- Leswing K., 2023, March 26). OpenAI announces GPT-4, claims it can beat 90% of humans on the SAT
- McMutrie B., 2023, February 8). AI and the future of undergraduate writing
- Schulten K., 2023, Lesson plan: Teaching and learning in the era of ChatGPT. The New York times
- Surovell E., 2023, ChatGPT has everyone freaking out about cheating. It’s not the first time
- Walstad W., 2006, Examiner’s manual
Cited by
Sorted by citations
Dell'Acqua, F., McFowland III, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4573321 · Cited by 794
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784
A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00468-z · Cited by 493
Large language models empowered agent-based modeling and simulation: a survey and perspectives
Gao, C., Lan, X., Li, N., Yuan, Y., Ding, J., Zhou, Z., Xu, F., & Li, Y. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03611-3 · Cited by 294
ChatGPT in education: Methods, potentials, and limitations
Memarian, B., & Doleck, T. (2023) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2023.100022 · Cited by 266
Metadata
- Authors
- Geerling, W., Mateer, G. D., Wooten, J., & Damodaran, N.
- Affiliations
- The University of Texas at Austin (US)
- Virginia Tech (US)
- O. P. Jindal Global University (IN)
- Corresponding author
- Geerling, Wayne
- Venue
- The American Economist
- Publisher
- SAGE Publications
- Published
- 2023-04-08
- Volume
- 68
- Issue
- 2
- Pages
- 233-245
- ISSN
- 0569-4345 (ISSN-L)
- 2328-1235
- OpenAlex
- W4362723020
- Cited by
- 119
- References
- 34
- Citations by year
- 2026: 15 · 2025: 38 · 2024: 38 · 2023: 28
- FWCI
- 27.93
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- The American Economist (publishedVersion, cc-by)
- VTechWorks (Virginia Tech) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- ChatGPT, economics education, artificial intelligence in education, automated assessment, microeconomics, macroeconomics, economic principles, chatbots, experiential learning, curriculum redesign
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review