Implications of AI-assisted Assignments for Cognitive Engagement and Emerging Ethical Themes in Humanities, Design, and STEM: A Pilot Study Utilizing Bloom’s Taxonomy

Leda Cempellin; Nathan Serfling; Marisa Ten Brink; Matthew Biesecker; Sahand Abbasi; Kwanghee Won; Mostafa Tazarv

doi:10.20343/teachlearninqu.14.42

Authors

Leda Cempellin South Dakota State University https://orcid.org/0000-0002-5328-687X
Nathan Serfling South Dakota State University
Marisa Ten Brink South Dakota State University
Matthew Biesecker South Dakota State University https://orcid.org/0009-0000-6652-3435
Sahand Abbasi South Dakota State University
Kwanghee Won South Dakota State University https://orcid.org/0000-0003-1717-6881
Mostafa Tazarv South Dakota State University

DOI:

https://doi.org/10.20343/teachlearninqu.14.42

Keywords:

AI-assisted learning, Bloom’s Taxonomy, critical thinking, higher education, AI ethics

Abstract

This exploratory mixed-method pilot study investigated students’ experiences with artificial intelligence (AI)-guided assignments across selected humanities, design, and STEM courses in higher education during the academic term beginning in August/September 2024. Using a custom survey tool grounded in Bloom’s taxonomy, the study assessed AI’s perceived effectiveness in enhancing cognitive engagement and explored students’ ethical awareness through open-ended reflections. A literature review, interdisciplinary collaboration, and iterative refinement using Copilot prompting informed survey questions in order to ensure cross-disciplinary applicability. Quantitative data came from Likert scale responses, while the researchers drew qualitative insights from coded action verbs and thematic analysis of open-ended responses. Preliminary findings indicated generally positive perception of AI, with mean scores above three across all six cognitive levels. The results underscore AI’s potential to support critical thinking as a layered cognitive process, rather than a discrete skill. Students often reported having engaged productively and skeptically with AI rather than over relying on it. Reflections highlighted concerns about query refinement, content verification, and responsible use, suggesting a meaningful link between ethical AI engagement and critical thinking development. Due to the small sample size and reliance on self-reported data from students, findings are not broadly generalizable. Future research should incorporate longitudinal and triangulated methods to better capture evolving student behaviors and align perceptions with actual AI use.

Author Biographies

Leda Cempellin, South Dakota State University

Leda Cempellin (United States) is a professor of art history in the School of Design at South Dakota State University. Her interdisciplinary research spans late modern art, museum studies, SoTL, wayfinding, collaborative practices, and artificial intelligence.
Nathan Serfling, South Dakota State University

Nathan Serfling (United States) is an assistant professor and composition coordinator in the School of English and Interdisciplinary Studies at South Dakota State University. His current research interests focus on writing program administration, writing pedagogy, curriculum design, and artificial intelligence.
Marisa Ten Brink, South Dakota State University

Marisa Ten Brink (United States) is an assistant professor of graphic design in the School Design at South Dakota State University. Her teaching and research cover a range of graphic design disciplines, including typography, branding, publication design, and data visualization.
Matthew Biesecker, South Dakota State University

Matt Biesecker (United States) is an associate professor of mathematics in the Department of Mathematics and Statistics at South Dakota State University. His research spans pure and applied mathematics, SoTL, and the use of technology in education.
Sahand Abbasi, South Dakota State University

Sahand Abbasi (United States) is currently an assistant professor of interior design at the Michael Graves College at Kean University. His interdisciplinary research focuses on design for health and well-being as well as the integration of artificial intelligence in design processes.
Kwanghee Won, South Dakota State University

Kwanghee Won (United States) is an associate professor of computer science at South Dakota State University. His research focuses on intelligent systems and cross-domain artificial intelligence applications, including smart infrastructure and agriculture.
Mostafa Tazarv, South Dakota State University

Mostafa Tazarv is currently an associate professor in the department of Civil and Environmental Engineering at the University of Nevada, Reno. Dr. Tazarv has secured more than $10 million research funding in the area of structural engineering.

References

Abrami, Philip C., Robert M. Bernard, Eugene Borokhovski, David I. Waddington, C. Anne Wade, and Tonje Persson. 2015. “Strategies for Teaching Students to Think Critically: A Meta-Analysis.” Review of Educational Research 85 (2): 275–314. https://doi.org/10.3102/0034654314551063. DOI: https://doi.org/10.3102/0034654314551063

Anderson, Lorin W., and David R. Krathwohl, editors. 2001. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. Longman.

Aviles, Christopher B. 2000. Teaching and Testing for Critical Thinking with Bloom’s Taxonomy of Educational Objectives. ERIC. Retrieved from https://files.eric.ed.gov/fulltext/ED446023.pdf.

Bloom, Benjamin S., editor. 1956. Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook I: Cognitive Domain. Longmans, Green and Co. LTD.

Crompton, Helen, and Diane Burke. 2023. “Artificial Intelligence in Higher Education: The State of the Field.” International Journal of Educational Technology in Higher Education 20: 1–22. https://doi.org/10.1186/s41239-023-00392-8. DOI: https://doi.org/10.1186/s41239-023-00392-8

Das, Syaamantak, Shyamal Kumar Das Mandal, and Anupam Basu. 2022. “Classification of Action Verbs of Bloom’s Taxonomy Cognitive Domain: An Empirical Study.” Journal of Education 202 (4): 554–66. https://doi.org/10.1177/00220574211002199. DOI: https://doi.org/10.1177/00220574211002199

De Matas, Jarrel. 2023. “ChatGPT and the Future of Writing about Writing.” Double Helix 11: 1–7. https://doi.org/10.37514/DBH-J.2023.11.1.09. DOI: https://doi.org/10.37514/DBH-J.2023.11.1.09

Duenas, Tom, and Diana Ruiz. 2024. The Risks of Human Overreliance on Large Language Models for Critical Thinking. Research Gate. https://doi.org/10.13140/RG.2.2.26002.06082.

EL YAZIDI, Rachid. 2023. “Strategies for Promoting Critical Thinking in the Classroom.” International Journal of English Literature and Social Sciences 8 (2): 26–40. https://doi.org/10.22161/ijels.82.5. DOI: https://doi.org/10.22161/ijels.82.5

Felten, Peter. 2013. “Principles of Good Practice in SoTL.” Teaching & Learning Inquiry 1 (1): 121–25. https://doi.org/10.2979/teachlearninqu.1.1.121. DOI: https://doi.org/10.20343/teachlearninqu.1.1.121

Lai, Emily R. 2011. Critical Thinking: A Literature Review. Pearson.

Lubbe, Anitia, Elma Marais, and Donnavan Kruger. 2025. “Cultivating Independent Thinkers: The Triad of Artificial Intelligence, Bloom’s Taxonomy and Critical Thinking in Assessment Pedagogy.” Education and Information Technologies 30: 17589–622. https://doi.org/10.1007/s10639-025-13476-x. DOI: https://doi.org/10.1007/s10639-025-13476-x

Rasul, Tareq, Sumesh Nair, Diane Kalendra, Mulyadi Robin, Fernando de Oliveira Santini, Wagner Junior Ladeira, Mingwei Sun, Ingrid Day, Raouf Ahmad Rather, and Liz Heathcote. 2023. “The Role of ChatGPT in Higher Education: Benefits, Challenges, and Future Research Directions.” Journal of Applied Learning & Teaching 6 (1): 41–56. https://doi.org/10.37074/jalt.2023.6.1.29. DOI: https://doi.org/10.37074/jalt.2023.6.1.29

Spector, Jonathan M., and Shanshan Ma. 2019. “Inquiry and Critical Thinking Skills for the Next Generation: From Artificial Intelligence Back to Human Intelligence.” Smart Learning Environments 6, Article 8. https://doi.org/10.1186/s40561-019-0088-z. DOI: https://doi.org/10.1186/s40561-019-0088-z

Stanny, Claudia J. 2016. “Reevaluating Bloom’s Taxonomy: What Measurable Verbs Can and Cannot Say about Student Learning.” Education Sciences 6 (4): 37. https://doi.org/10.3390/educsci6040037. DOI: https://doi.org/10.3390/educsci6040037

Stojanov, Ana, Qian Liu, and Joyce Hwee Ling Koh. 2024. “University Students’ Self-Reported Reliance on ChatGPT for Learning: A Latent Profile Analysis.” Computers and Education: Artificial Intelligence 6: 100243. https://doi.org/10.1016/j.caeai.2024.100243. DOI: https://doi.org/10.1016/j.caeai.2024.100243

Zhai, Chunpeng, Santoso Wibowo, and Lily D. Li. 2024. “The Effects of Over-Reliance on AI Dialogue Systems on Students’ Cognitive Abilities: A Systematic Review.” Smart Learning Environments 11, Article 28. https://doi.org/10.1186/s40561-024-00316-7. DOI: https://doi.org/10.1186/s40561-024-00316-7