Prompting for creative problem-solving: A process-mining study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081740%3A_____%2F25%3A00635530" target="_blank" >RIV/68081740:_____/25:00635530 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11210/25:10498707 RIV/00216208:11240/25:10498707 RIV/00216208:11320/25:10498707

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0959475225000805" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0959475225000805</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.learninstruc.2025.102156" target="_blank" >10.1016/j.learninstruc.2025.102156</a>

Result language

angličtina

Original language name

Prompting for creative problem-solving: A process-mining study

Original language description

Background: Although generative-AI systems are increasingly used to solve non-routine problems, effective prompting strategies remain largely underexplored. Aims: The present study investigates how university students prompt ChatGPT to solve complex ill-defined problems, specifically examining which prompts are associated with higher or lower problem-solving performance. Sample: Seventy-seven university students (53 women, Mage = 22.4 years) participated in the study. Methods: To identify various prompt types employed by students, the study utilized qualitative analysis of interactions with ChatGPT 3.5 during the resolution of the creative problem-solving task. Participants’ performance was measured by the quality, elaboration, and originality of their ideas. Subsequently, two-step clustering was employed to identify groups of low- and high-performing students. Finally, process-mining techniques (heuristics miner) were used to analyze the interactions of low- and high-performing students. Results: The findings suggest that including clear evaluation criteria when prompting ChatGPT to generate ideas (rs = .38), providing ChatGPT with an elaborated context for idea generation (rs = .47), and offering specific feedback (rs = .45), enhances the quality, elaboration, and originality of the solutions. Successful problemsolving involves iterative human-AI regulation, with high performers using an overall larger number of prompts (d = .82). High performers interacted with ChatGPT through dialogue, where they monitored and regulated the generation of ideas, while low performers used ChatGPT as an information resource. Conclusions: These results emphasize the importance of active and iterative engagement for creative problemsolving and suggest that educational practices should foster metacognitive monitoring and regulation to maximize the benefits of human-AI collaboration.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50101 - Psychology (including human - machine relations)

Project

<a href="/en/project/GA24-11515S" target="_blank" >GA24-11515S: Learning with ChatGPT: why and how students employ ChatGPT in their school assignments</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Learning and Instruction

ISSN

0959-4752

e-ISSN

1873-3263

Volume of the periodical

99

Issue of the periodical within the volume

říjen

Country of publishing house

GB - UNITED KINGDOM

Number of pages

11

Pages from-to

102156

UT code for WoS article

001500163700001

EID of the result in the Scopus database

2-s2.0-105005601069