Journal of Education for Sustainability and Transformation (JESTRA)

Peer-reviewed open-access journal

ISSN: XXXX-XXXX

Vol. 2 No. 1 (2026)
Articles

Development of an Environmental-Based Robotic Learning Media: Intelligent Object Sorter (ELIO) for Pre-Service Physics Teachers

  • Boris Agung Ramadhan

Keywords

  • Educational robotics
  • Environmental
  • Physics learning
  • Sustainable Development Goals
  • Pre-service physics teachers
  • Bibliometric analysis
    • ...More
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Abstract

Rapid technological advancements and the urgent need to align education with the 2030 Sustainable Development Goals require innovative, interactive approaches in environmental physics. Traditional instruction often struggles to connect abstract theoretical concepts with real-world sustainability challenges. Consequently, this study explores research trends regarding the integration of robotics, artificial intelligence, and Android technologies in education to establish a comprehensive scientific foundation for developing the Environment Learning Intelligent Object Sorter (ELIO). Employing a bibliometric approach, publication data from 2005 to 2025 were extracted from the Scopus database and analyzed to identify dominant themes, publication trajectories, and knowledge gaps. The results reveal an exponential surge in scientific production and citation impact starting in 2020. However, the findings also expose a profound geographical divide, with research heavily dominated by the United States and China. Furthermore, current literature remains predominantly anchored in technical engineering venues, lacking explicit pedagogical integration for environmental sustainability. In conclusion, this study confirms a critical gap in the holistic application of educational robotics, providing an evidence-based justification for designing the ELIO prototype. This research enriches the theoretical intersection of cyber-physical systems and physics education, while offering strategic policy insights to address global educational inequities and guiding future empirical classroom implementations.

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