Opportunities of artificial intelligence for supporting complex problem-solving: Findings from a scoping review

认知 多样性(控制论) 领域(数学分析) 计算机科学 元认知 心理学 认知科学 认知心理学 管理科学 人工智能 数学 数学分析 经济 神经科学
作者
Srécko Joksimovíc,Dirk Ifenthaler,Rebecca Marrone,Maarten de Laat,George Siemens
出处
期刊:Computers & Education: Artificial Intelligence [Elsevier BV]
卷期号:4: 100138-100138 被引量:134
标识
DOI:10.1016/j.caeai.2023.100138
摘要

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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