Opportunities of artificial intelligence for supporting complex problem-solving: Findings from a scoping review
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The research objective of this paper is to advance knowledge about the role of artificial intelligence (AI) in complex problem-solving. A problem is complex due to the large number of highly inter-connected variables affecting the problem state. Complex problem-solving situations often change decremental or worsen, forcing a problem solver to act immediately, under considerable time pressure. While research findings support the assumption that (1) affective, (2) (meta-)cognitive, and (3) social processes support complex problem-solving, opportunities of AI for supporting complex problem-solving need to be further investigated. This article presents a scoping review of relevant literature from the last five years. The study included, N = 38 studies for coding and analysis. Our findings show that in addition to the increased number of publications, the current trend suggests increased quality of published work. Human-AI collaboration in complex problem-solving has been explored across a broad variety of AI application domains. However, the four dimensions of complex problem – namely, cognitive, metacognitive, social and affective - have been augmented by AI to a different extent. Although most of the work has been done in the cognitive domain, it is encouraging to see progress across social and affective dimensions as well. Implications for future research and practice are being discussed.
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Generative AI tools can potentially enhance problem-based learning by supporting brainstorming and solution refinement.
“Generative AI tools can potentially enhance problem- based learning (PBL) by supporting brainstorming and solution refinement.”
From The role of critical thinking on undergraduates' reliance behaviours on generative <scp>AI</scp> in problem‐solving (2025) · cites this paper as Joksimovic et al., 2023
Generative AI can aid the problem-solving process by acting as a tool for knowledge generation, idea exploration, and feedback.
“Generative AI can aid the problem-solving process by acting as a tool for knowledge generation, idea exploration, and feedback (Joksimovic et al., 2023).”
From Measuring undergraduate students’ reliance on generative AI during problem-solving: Scale development and validation. (2025) · cites this paper as Joksimovic et al., 2023
Generative AI can facilitate collaborative learning by acting as a learning partner, helping students engage in meaningful dialogues, share diverse perspectives, and improve collective knowledge.
“Generative AI can facilitate this by acting as a learning partner, helping students to engage in meaningful dialogues, share diverse perspectives, and improve the collective knowledge of the group (Joksimovic et al., 2023).”
From Measuring undergraduate students’ reliance on generative AI during problem-solving: Scale development and validation. (2025) · cites this paper as Joksimovic et al., 2023
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- Authors
- Joksimovic, S., Ifenthaler, D., Marrone, R., De Laat, M., & Siemens, G.
- Affiliations
- University of Mannheim (DE)
- University of South Australia (AU)
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2023
- Volume
- 4
- Pages
- 100138
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4367626887
- Cited by
- 152
- References
- 7
- Citations by year
- 2026: 32 · 2025: 61 · 2024: 52 · 2023: 7
- FWCI
- 35.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- UniSA Research Outputs Repository (University of South Australia) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- artificial intelligence, complex problem solving, human-AI collaboration, metacognition, emotional processing, social processes, cognitive processes, time pressure
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