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Student Perceptions of ChatGPT Use in a College Essay Assignment: Implications for Learning, Grading, and Trust in Artificial Intelligence
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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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![Fig. 4 Adapted from Hayes' (2012) model of writing [75]. ChatGPT as a 'Collaborator' helps 'propose' by generating ideas, 'translate' by converting concepts to text, 'evaluate' by providing feedback, and 'transcribe' by drafting content. This new process likely impacts traditional human writing schemas.](/paper-figures/a5df31459f4a4a259b16384fc2f8e57d/student-perceptions-of-chatgpt-use-in-a-college-essay-assignment-implications-figure-4.png)
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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 (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
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“For example, Tossell et al. (2024) found perceived trustworthiness of ChatGPT predicted students' intent to rely upon it for future educational purposes.”
From College students’ literacy, ChatGPT activities, educational outcomes, and trust from a digital divide perspective (2026) · cites this paper as Tossell et al., 2024
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“students are using ChatGPT to complete their homework assignments [3]”
From Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integrity (2024) · cites this paper as [3]
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“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].”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [20]
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Metadata
- 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
- hybrid
- doi.org
- 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
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › 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
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 ›
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