Cited by 219Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationAcademic integrity and plagiarism

Student perceptions of ChatGPT use in a college essay assignment: Implications for learning, grading, and trust in artificial intelligence

Open access
Tossell, Chad C., Tenhundfeld, Nathan L., Momen, Ali, Cooley, Katrina, de Visser, Ewart J.·2024·IEEE Transactions on Learning Technologies

Abstract

This study examined student experiences before and after an essay writing assignment that required the use of ChatGPT within an undergraduate engineering course. Utilizing a pre-post study design, we gathered data from 24 participants to evaluate ChatGPT's support for both completing and grading an essay assignment, exploring its educational value and impact on the learning process. Our quantitative and thematic analyses uncovered that ChatGPT did not simplify the writing process. Instead, the tool transformed the student learning experience yielding mixed responses. Participants reported finding ChatGPT valuable for learning, and their comfort with its ethical and benevolent aspects increased post-use. Concerns with ChatGPT included poor accuracy and limited feedback on the confidence of its output. Students preferred instructors to use ChatGPT to help grade their assignments, with appropriate oversight. They did not trust ChatGPT to grade by itself. Student views of ChatGPT evolved from a perceived “cheating tool” to a collaborative resource that requires human oversight and calibrated trust. Implications for writing, education, and trust in AI are discussed.

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Registry

Crossref · 10.1109/tlt.2024.3355015

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84 of 84 references verified0 citation errors · 0 not checkable

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  • Student-centred AI feedback mechanisms involve tasks like reflection prompts, AI-use reports, or annotated submissions, encouraging students to critically evaluate how and why they used generative AI tools.

    “Student-centred AI feedback mechanisms involve tasks like reflection prompts, AI-use reports, or annotated submissions, encouraging students to critically evaluate how and why they used generative AI tools (Rawas, 2024; Tossell et al., 2024).”

    From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Tossell et al., 2024

    The Assignment section (page unavailable) describes drafts that identify ChatGPT-generated content and require students to highlight and address AI errors. The Open-Response Questions section asks students about their experience, and Limitations suggests annotating where ChatGPT assisted. These support examples of documented and critical AI use, but the paper does not describe a general set of reflection prompts or AI-use reports aimed at evaluating both how and why students used AI. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • Perceived trustworthiness of ChatGPT predicted students' intent to rely upon it for future educational purposes.

    “For example, Tossell et al. (2024) found perceived trustworthiness of ChatGPT predicted students' intent to rely upon it for future educational purposes.”
  • Students use ChatGPT to complete their homework assignments.

    “students are using ChatGPT to complete their homework assignments [3]”
  • University students value ChatGPT for its utility in completing academic tasks, such as writing assistance, research, and learning new concepts.

    “This finding suggests that university students, in particular, value ChatGPT for its utility in completing academic tasks, such as writing assistance, research, and learning new concepts [1,7,20,65].”

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Research works printed but not linked: 3

  1. C. Teddlie and A. Tashakkori, "Major issues and controversies in the use of mixed methods in the social and behavioural sciences," in Handbook of Mixed Methods in Social and Behavioural Research, Sage, 2003, pp. 3-50.
  2. A. Bartoszko, S. Czerwinski, and A. Bereznowska, (Jun. 2019). Single-item self-report measure of learning engagement: What does it measure? Presented at Interdisciplinary Scientific International Conference for PhD Students and Assistants. [Paper]. Available: https://www.researchgate.net/publication/334974047_Single- item_self- report_measure_of_learning_engagement_What_does_it_measu re
  3. T. V. McGovern, "Process/pedagogy," in The teaching of psychology: Essays in honors of Wilbert J. McKeachie and Charles L. Brewer, Mahwah, NJ, Lawrence Erlbaum Associates Inc, 2002, pp. 81-90.

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Authors
Tossell, C. C., Tenhundfeld, N. L., Momen, A., Cooley, K., & de Visser, E. J.
Affiliations
  • United States Air Force Academy (US)
  • University of Alabama in Huntsville (US)
  • Department of Behavioral Sciences and Leadership, United States Air Force Academy, Colorado Springs, CO, USA
Venue
IEEE Transactions on Learning Technologies
Published
2024
Volume
17
Pages
1069-1081
ISSN
  • 1939-1382 (ISSN-L)
  • 2372-0050
OpenAlex
W4390921168
Cited by
218
References
79
Citations by year
2026: 80 · 2025: 90 · 2024: 48
FWCI
81.97
Type
journal article
Language
en
Open access
Locations
IEEE Transactions on Learning Technologies (publishedVersion, cc-by)
Funders
  • Air Force Office of Scientific Research (21USCOR004)
  • Defense Advanced Research Projects Agency (FA8650-23-C-7318)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Safety Research › Academic integrity and plagiarism
Keywords
ChatGPT, student perceptions, AI-assisted grading, trust in AI, academic integrity, human oversight of AI, engineering education, student learning experience

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