Presentation Schedule


Presenter Registration Banner 5

The Role of Critical-Thinking Self-Efficacy in Creative Problem-Solving: A Generative AI-based Evaluation (107850)

Session Information:

Session: On Demand
Room: Virtual Poster Presentation
Presentation Type:Virtual Poster Presentation

All presentation times are UTC + 1 (Europe/London)

Addressing global challenges such as the United Nations Sustainable Development Goals (SDG) requires individuals to critically evaluate problems and generate viable solutions. However, assessing performance on such open-ended and complex tasks is often time-consuming and methodologically challenging. The rapid development of generative artificial intelligence (GAI), such as ChatGPT, offers a potential solution to this assessment challenge. In addition, critical thinking has been identified as a key factor influencing creative problem-solving. Accordingly, this study examined the role of critical thinking self-efficacy (CTSE) in solving ten online SDG-related problems among 82 college students, with ChatGPT employed as an automated scoring tool. Based on CTSE scores, participants were categorized into high- and low-CTSE groups. A mixed-design analysis of variance revealed a significant main effect of time, F(1, 80) = 20.541, p < .001, ηp² = .204, as well as a significant Time × Group interaction, F(1, 80) = 6.340, p = .014, ηp² = .073. Follow-up simple main effects analyses indicated that students in the high-CTSE group demonstrated significantly greater improvements in GAI-rated CPS performance, F(1, 40) = 22.364, p < .001, ηp² = .359. Notably, repeated trials revealed that ChatGPT was less effective in evaluating complex problem-solving responses involving large volumes of information. Accurate and consistent assessment was achieved only when responses were constrained to smaller, well-structured inputs. Collectively, these findings suggest that CT self-efficacy plays a critical role in creative problem-solving and underscore the importance of cautiously and strategically employing generative AI as an assessment tool for complex, open-ended tasks.

Authors:
Bethany C. Y. Wu, National Chengchi University, Taiwan
Rayen Jui-Yen Chang, National Chengchi University, Taiwan
Yu-Chu Yeh, National Chengchi University, Taiwan
Min-Wen Jao, National Chengchi University, Taiwan


About the Presenter(s)
Rayen Chang is currently a PhD student in Education at National Chengchi University (NCCU) in Taipei, Taiwan.

See this presentation on the full scheduleOn Demand Schedule




Virtual Poster Presentation




Conference Comments & Feedback

Place a comment using your LinkedIn profile

Comments

Share on activity feed

Powered by WP LinkPress

Share this Presentation

Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00