Prompt Aloud!: Incorporating image-generative AI into STEAM class with learning analytics using prompt data

The rapid advancements in artificial intelligence (AI) have transformed various domains, including education. Generative AI models have garnered significant attention for their potential in educational settings, but image-generative AI models need to be more utilized. This study explores the potenti...

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Vydáno v:Education and information technologies Ročník 29; číslo 8; s. 9575 - 9605
Hlavní autoři: Lee, Unggi, Han, Ariel, Lee, Jeongjin, Lee, Eunseo, Kim, Jiwon, Kim, Hyeoncheol, Lim, Cheolil
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.06.2024
Springer
Springer Nature B.V
Témata:
Analysis
Artificial intelligence
Cognitive Processes
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computers and Education
Convergent Thinking
Creative Thinking
Diaries
Education
Educational Technology
Gender Differences
Generative artificial intelligence
Information Systems Applications (incl.Internet)
Learning Activities
Learning Analytics
Learning strategies
STEM Education
Student Attitudes
Students
Thinking Skills
User Interfaces and Human Computer Interaction
South Korea
Image-generative AI
Art-focused STEAM education
Prompt
ISSN:1360-2357, 1573-7608
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Shrnutí:The rapid advancements in artificial intelligence (AI) have transformed various domains, including education. Generative AI models have garnered significant attention for their potential in educational settings, but image-generative AI models need to be more utilized. This study explores the potential of integrating generative AI, specifically Stable Diffusion, into art-focused STEAM classes. To this end, we combined STEAM education with image-generative AI. We designed and implemented a learning activity in which students used image-generative AI to generate creative images and wrote imaginative diaries inspired by AI-generated pictures. Using a mixed-methods approach, we collected and analyzed data from surveys, interviews, and prompt datasets to gain insights into students' perceptions, motivations, and behaviors concerning the integration of generative AI in art education. Our study found that incorporating generative AI into art-focused STEAM classes may reduce the gap between male and female students' interest in art practices. We also found that the number of subjects in students' prompt datasets is linked to their divergent and convergent thinking. Finally, we discovered a meaningful correlation between the number of unique words in students' diaries and the image scores that researchers assessed. Our findings shed light on the relationship between students' divergent and convergent behaviors, offering valuable insights into their creative thinking processes. This study underscores the potential of integrating image-generative AI models in STEAM education.
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ISSN:1360-2357
1573-7608
DOI:10.1007/s10639-023-12150-4