Adaptive Management Model for the Development of AI-Based Science Learning Media and IoT in The Society 5.0 Era: A Literature Study
DOI:
10.29303/jppipa.v11i12.13819Published:
2025-12-31Downloads
Abstract
The transition from Industry 4.0 to Society 5.0 has transformed educational paradigms, particularly in science education, necessitating adaptive management approaches to integrating advanced technologies. This literature study examines the adaptive management model for developing AI and IoT-based science learning media in the Society 5.0 era. Through systematic analysis of 10 peer-reviewed articles from 2020–2025 sourced from Google Scholar, Scopus, and ERIC databases, this research identifies critical components, challenges, and opportunities in technology-integrated science education. Findings reveal that AI enables personalized science learning through adaptive algorithms and data analytics, while IoT facilitates real-time experiential learning through connected laboratory equipment and environmental sensors. The proposed adaptive management model integrates technological infrastructure, teacher competency development, curriculum alignment, and ethical considerations to create responsive science learning ecosystems. Key challenges include digital divides, infrastructure limitations, and balancing technology with humanistic educational values. This model offers significant implications for enhancing scientific literacy, experiential learning, and 21st-century skills development in science classrooms. The research contributes a conceptual framework for educational stakeholders to implement adaptive, technology-enhanced science education aligned with Society 5.0 principles.
Keywords:
Adaptive management AI-Based Learning Media Educational technology IoT Learning Media Science education Society 5.0References
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