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Fostering AI Literacy in Elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) Education in the Age of Generative AI

doi: 10.3390/su151813595
The advancement of generative AI technologies underscores the need for AI literacy, particularly in Southeast Asia’s elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) education. This study explores the development of AI literacy principles for elementary students. Utilizing existing AI literacy models, a three-session classroom intervention was implemented in an Indonesian school, grounded in constructivist, constructionist, and transformative learning theories. Through design-based research (DBR) and network analysis of reflection papers (n = 77), the intervention was evaluated and redesigned. Findings revealed clusters of interdependent elements of learner experiences, categorized into successes, struggles, and alignments with learning theories. These were translated into design moves for future intervention iterations, forming design principles for AI literacy development. The study contributes insights into optimizing the positive effects and minimizing the negative impacts of AI in education.
- University of Alabama at Birmingham United States
- Satya Wacana Christian University Indonesia
- Universitas Krisnadwipayana Indonesia
- Education University of Hong Kong China (People's Republic of)
- University of Alabama at Birmingham United States
Environmental effects of industries and plants, STEAM education, AI literacy, TJ807-830, TD194-195, Renewable energy sources, design-based research, Environmental sciences, generative AI, elementary school, GE1-350, network analysis
Environmental effects of industries and plants, STEAM education, AI literacy, TJ807-830, TD194-195, Renewable energy sources, design-based research, Environmental sciences, generative AI, elementary school, GE1-350, network analysis
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).36 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
