The Development of RBL-STEAM Learning Design to Improve Climate Change Literacy Through the Construction of Energy-Efficient Houses in Sixth Grade of Elementary School Students

Abstract : Climate change literacy is essential for preparing future generations to understand environmental challenges and take an active role in mitigation and adaptation efforts. This study aims to enhance students’ climate change literacy through the development of Research-Based Learning (RBL) integrated with the STEAM approach, which combines Science, Technology, Engineering, Arts, and Mathematics. Students were engaged in the construction of energy-efficient house projects that incorporated simple electrical circuits, allowing them to apply scientific concepts in a meaningful context. The study employed a research and development methodology using the 4D model, which consists of the stages Define, Design, Develop, and Disseminate. The developed learning materials included lesson plans, student worksheets (LKPD), and a climate change literacy test. A sequential exploratory mixed-methods design was implemented, beginning with qualitative data collection and analysis, followed by quantitative data collection and analysis. The study was conducted at SDN Banjarwungu 2 as the experimental group and SDN Gempolklutuk as the control group. The findings indicate that the RBL-STEAM learning materials are valid, practical, and effective in improving students’ understanding of the causes, impacts, and potential solutions to climate change. The study concludes that integrating RBL-STEAM with project-based learning activities can significantly enhance climate change literacy in primary education.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-30
DOI
https://doi.org/10.5281/zenodo.16602332
Primary Topic
Network Traffic and Congestion Control
Type
article
Field-Weighted Citation Impact
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article

The Development of RBL-STEAM Learning Design to Improve Climate Change Literacy Through the Construction of Energy-Efficient Houses in Sixth Grade of Elementary School Students

Zenodo (CERN European Organization for Nuclear Research)
Network Traffic and Congestion Control
article

The Development of RBL-STEAM Learning Design to Improve Climate Change Literacy Through the Construction of Energy-Efficient Houses in Sixth Grade of Elementary School Students

article en

Abstract

Abstract : Climate change literacy is essential for preparing future generations to understand environmental challenges and take an active role in mitigation and adaptation efforts. This study aims to enhance students’ climate change literacy through the development of Research-Based Learning (RBL) integrated with the STEAM approach, which combines Science, Technology, Engineering, Arts, and Mathematics. Students were engaged in the construction of energy-efficient house projects that incorporated simple electrical circuits, allowing them to apply scientific concepts in a meaningful context. The study employed a research and development methodology using the 4D model, which consists of the stages Define, Design, Develop, and Disseminate. The developed learning materials included lesson plans, student worksheets (LKPD), and a climate change literacy test. A sequential exploratory mixed-methods design was implemented, beginning with qualitative data collection and analysis, followed by quantitative data collection and analysis. The study was conducted at SDN Banjarwungu 2 as the experimental group and SDN Gempolklutuk as the control group. The findings indicate that the RBL-STEAM learning materials are valid, practical, and effective in improving students’ understanding of the causes, impacts, and potential solutions to climate change. The study concludes that integrating RBL-STEAM with project-based learning activities can significantly enhance climate change literacy in primary education.

Zenodo (CERN European Organization for Nuclear Research)
Universitas Jember (ID), Indonesia Open University (ID)
Quality Education
Openalex Percentile: Top 49%
Network Traffic and Congestion Control
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