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Bibliometric Analysis using R Studio: Sixteen Years of Education for Sustainable Development Studies in Science Learning Gita Nurul Puspita; Ari Widodo; Siti Sriyati; Achmad Samsudin
Proceeding of the International Conference on Mathematical Sciences, Natural Sciences, and Computing Vol. 1 No. 1 (2024): June : Proceeding of the International Conference on Mathematical Sciences, Nat
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/icmsnsc.v1i1.15

Abstract

This study investigates the trends, contributions, and impact of research in the field of Education for Sustainable Development (ESD) in science learning through a bibliometric analysis of Scopus data. The Bibliometrix R package was used as the primary tool for analysis, with visualization supported by Microsoft Excel. The analysis reveals consistent growth in research output, with Indonesia identified as the leading contributor and Universitas Pendidikan Indonesia as the top-performing institution. Based on significant publications in high-impact journals, the most influential author is Ingo Eilks. The study recorded publication peaks in 2022 and 2024, possibly driven by the increasing urgency to address sustainability issues. The findings highlight the importance of international collaboration and continuous adaptation to emerging trends. These insights provide a comprehensive overview of research trends and impacts in ESD and offer straightforward directions for future research development, particularly in the context of global collaboration and responses to evolving sustainability challenges.
Enhancing Self-Regulated Learning with ChatGPT: A Study in Science Education Fanny Rahmatina Rahim; Ari Widodo; Achmad Samsudin; Tina Hayati Dahlan
Proceeding of the International Conference on Mathematical Sciences, Natural Sciences, and Computing Vol. 1 No. 2 (2024): December : Proceeding of the International Conference on Mathematical Sciences,
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/icmsnsc.v1i2.21

Abstract

In the dynamic digital era, artificial intelligence (AI) like ChatGPT presents revolutionary opportunities to advance classroom learning, particularly in science education. This research focuses on the utilization of ChatGPT to develop a learning model that supports the enhancement of students' Self-Regulated Learning (SRL) abilities. The study investigates four main aspects: (1) How can student-centered science learning improve SRL skills such as goal setting, self-management, and reflection? (2) How can the use of active and collaborative learning strategies in science increase students' motivation and SRL? (3) How can formative and summative assessments focused on developing SRL skills enhance science learning? (4) What are the researchers' experiences in using ChatGPT as a tool to develop and refine learning units, and their reflective research on its use as a teaching aid? An exploratory methodology was applied, utilizing ChatGPT to generate teaching materials tailored to classroom needs. Initial findings highlight ChatGPT's potential to support the development of SRL skills by providing quick access to structured and verified information. However, its use must be carefully managed to prevent over-reliance and ensure critical evaluation of sources. Educators are responsible for guiding students in the wise use of AI, fostering critical thinking, and promoting independent learning. Integrating ChatGPT into lesson design can enhance science education by creating engaging units, providing clear rubrics, and supporting formative assessment. This research underscores the positive potential of ChatGPT in fostering inclusive and adaptive science education, while also addressing the need for responsible technology management to ensure student development and well-being.