Metacognition and Critical Thinking: Using ChatGPT-Generated Responses as Prompts for Critique in a Problem-Solving Workshop (SMARTCHEMPer)
Abstract
Successful problem solving is a complex process that requires content knowledge, process skills, developed critical thinking, metacognitive awareness, and deep conceptual reasoning. Teaching approaches to support students developing problem-solving skills include worked examples, metacognitive and instructional scaffolding, and variations of these techniques. In this report, we describe a classroom activity, which involves a combination of metacognitive scaffolding, problem-solving practice, and critiquing of ChatGPT-generated solutions. It was demonstrated that students engaged with the idea of metacognition as part of the problem-solving toolbox and showed appreciation for the collaborative nature of problem solving. They were also able to identify mistakes and flaws in the provided erroneous solutions, albeit to varying degrees. The results also revealed that incoming university students likely require scaffolding to develop sophisticated critical-thinking skills.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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 unpredictability of cGPT outputs, while initially a technical challenge, became pedagogically valuable as students learned to analyse them critically, reflecting an essential skill required in working with generative AI.
“For example, the unpredictability of cGPT outputs, while initially a technical challenge, became pedagogically valuable as students learned to analyse them critically, reflecting an essential skill required in working with generative AI that has previously been reported (Exintaris et al., 2023; Yuriev et al., 2025).”
From Co-creating custom GPTs: an autoethnographic study of undergraduate students as partners in generative AI innovation (2026) · cites this paper as Exintaris et al., 2023
A significant number of studies employed rubrics and performance-based assessments to evaluate CT in students' outputs, including essays, chatbot interactions, and project submissions.
“A significant number of studies employed rubrics and performance-based assessments to evaluate CT in students' outputs, including essays, chatbot interactions, and project submissions [75,76,78,87,88].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [76]
AI agents assumed roles such as peer reviewer, expert stakeholder, regulator, or devil's advocate to challenge students' reasoning and surface underlying assumptions.
“In these designs, AI agents assumed roles such as peer reviewer, expert stake holder, regulator, or devil's advocate to challenge students' reasoning and surface underlying assumptions [56,76,93].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [76]
Tools providing explicit reflective questions or ethical simulations were particularly effective in engaging students deeply, promoting sustained metacognitive awareness.
“Tools providing explicit reflective questions or ethical simulations were particularly effective in engaging students deeply, promoting sustained metacognitive awareness [76].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [76]
The range of benefits in our study suggests personalized learning, promotion of critical thinking, encouragement of exploration and creativity, support for inquiry and problem-solving, and enhancement of students' understanding of real-world connections.
“The range of benefits in our study suggest personalized learning, promotion of critical thinking, encouragement of exploration and creativity, support for inquiry and problem-solving, and the enhancement of students' understanding of real-world connections (Exintaris et al., 2023;Limo et al., 2023;Morath et al., 2023).”
From Widen the debate: What is the academic community’s perception on ChatGPT? (2024) · cites this paper as Exintaris et al., 2023
Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414 · see citing works
Cognitive Load During Problem Solving: Effects on Learning
Sweller, J. (1988) · Cognitive Science · doi:10.1016/0364-0213(88)90023-7 · Cited by 11,048 · see citing works
One size fits all? What counts as quality practice in (reflexive) thematic analysis?
Braun, V., & Clarke, V. (2021) · Qualitative Research in Psychology · doi:10.1080/14780887.2020.1769238 · Cited by 9,727 · see citing works
THE ROLE OF TUTORING IN PROBLEM SOLVING <sup>*</sup>
Wood, D., Bruner, J. S., & Ross, G. (1976) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.1976.tb00381.x · Cited by 8,851 · see citing works
Bang, Y., Cahyawijaya, S., Lee, N., Dai, W., Su, D., Wilie, B., Lovenia, H., Ji, Z., Yu, T., Chung, W., et al. (2023) · arXiv · doi:10.48550/arxiv.2302.04023 · Cited by 337 · see citing works
Learning gain differences between ChatGPT and human tutor generated algebra hints
Pardos, Z. A., & Bhandari, S. (2023) · arXiv · doi:10.48550/arxiv.2302.06871 · Cited by 70 · see citing works
Belland, B. R. (2011) · Educational Psychology Review · doi:10.1007/s10648-011-9176-5 · Cited by 64 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Leveraging ChatGPT for Enhancing Critical Thinking Skills
Guo, Y., & Lee, D. (2023) · Journal of Chemical Education · doi:10.1021/acs.jchemed.3c00505 · Cited by 250 · see citing works
Schei, O. M., Møgelvang, A., & Ludvigsen, K. (2024) · Education Sciences · doi:10.3390/educsci14080922 · Cited by 166 · see citing works
Implementing generative AI (GenAI) in higher education: A systematic review of case studies
Belkina, M., Daniel, S., Nikolic, S., Haque, R., Lyden, S., Neal, P., Grundy, S., & Hassan, G. M. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100407 · Cited by 183 · see citing works
Chen, A., Xiang, M., Zhou, J., Jia, J., Shang, J., Li, X., Gašević, D., & Fan, Y. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105198 · Cited by 115 · see citing works
West, J. K., Franz, J. L., Hein, S. M., Leverentz-Culp, H. R., Mauser, J. F., Ruff, E. F., & Zemke, J. M. (2023) · Journal of Chemical Education · doi:10.1021/acs.jchemed.3c00581 · Cited by 79 · see citing works
(2023) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets45212 · Cited by 74 · see citing works
Youssef, E., Medhat, M., Abdellatif, S., & Al Malek, M. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100316 · Cited by 65 · see citing works
Hwang, G.-J., Cheng, P.-Y., & Chang, C.-Y. (2025) · Nurse Education in Practice · doi:10.1016/j.nepr.2025.104266 · Cited by 44 · see citing works
Young, J. D., Dawood, L., & Lewis, S. E. (2024) · Journal of Chemical Education · doi:10.1021/acs.jchemed.4c00154 · Cited by 35 · see citing works
Yuriev, E., Burton, M. G., Knott, D., Terrill, A. E., Jackson, N. R. C., & Chen, S. (2025) · Journal of Chemical Education · doi:10.1021/acs.jchemed.4c01499 · Cited by 26 · see citing works
Self-citationWiden the debate: What is the academic community’s perception on ChatGPT?
Jiang, Y., Xie, L., Lin, G., & Mo, F. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12677-0 · Cited by 21 · see citing works
Zhang, Y., Lai, X., Yi, S., & Lu, Y. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13190-0 · Cited by 18 · see citing works
Balart, T., Díaz, B., & Shryock, K. (2026) · Algorithms · doi:10.3390/a19030179 · Cited by 15 · see citing works
“A significant number of studies employed rubrics and performance-based assessments to evaluate CT in students’ outputs, including essays, chatbot interactions, and project submissions [75,76,78,87,88].”
InfluentialLeveraging generative AI to foster metacognition and self-directed learning
Lowry, B., McGrath, S., Eitel, C., Hall, H., & Clapp, T. R. (2026) · Journal of Microbiology & Biology Education · doi:10.1128/jmbe.00153-25 · Cited by 7 · see citing works
Lo, S., Lea, T., Mavromoustakos, A., Joseph, B., Yii, M., Exintaris, B., Karunaratne, N., Pearson, D. L., Ritchie, T., Yuriev, E., et al. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1818781
Self-citation
- Authors
- Exintaris, B., Karunaratne, N., & Yuriev, E.
- Affiliations
- Monash University (AU)
- Corresponding author
- Yuriev, Elizabeth
- Venue
- Journal of Chemical Education
- Publisher
- American Chemical Society (ACS)
- Published
- 2023-07-24
- Volume
- 100
- Issue
- 8
- Pages
- 2972-2980
- ISSN
- 0021-9584 (ISSN-L)
- 1938-1328
- OpenAlex
- W4385198957
- Cited by
- 123
- References
- 7
- Citations by year
- 2026: 30 · 2025: 39 · 2024: 45 · 2023: 9
- FWCI
- 59.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Chemical Education (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Education and Critical Thinking Development
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- metacognition, critical thinking, problem solving, metacognitive scaffolding, chemistry education, collaborative problem solving, university students
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