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All Journal International Journal of Contextual Science Education
Stefanie Astrid Aipassa
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Decision Sciences, Operations Research & Management Education Other

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The Effect of The Learning Cycle 5e Model On Mastery of Concepts and Creative Thinking Students On Renewable Energy Materials At SMAN 1 Gerung Barinta Nur Respasari; Joni Rokhmat; I Wayan Gunada; Hikmawati; Stefanie Astrid Aipassa
International Journal of Contextual Science Education Vol. 2 No. 3 (2024): July - September 2024
Publisher : Postgraduate Program, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijcse.v2i3.661

Abstract

This study aims to identify the effect of Learning Cycle 5E learning model on concept mastery and creative thinking ability of students on renewable energy material at SMAN 1 Gerung. The research method used is a pseudo-experimental method with a pre-test and post-test control group design. The research population used in this study were Phase E students of class X SMAN 1 Gerung. Samples were taken using purposive sampling technique and obtained XH class students as experimental class and XK as control class. The research instrument includes a description test that measures mastery of concepts and creative thinking skills that have been tested for validity, reliability, difficulty level of questions, and differentiation of questions. Data analysis used t-test and MANOVA. The results showed that the Learning Cycle 5E model significantly improved students' concept mastery and creative thinking skills compared to the conventional learning method. The average post-test score in the experimental group was higher than the control group, showing the effect of the Learning Cycle 5E model on students' concept mastery and creative thinking on renewable energy material with a significance showing 0.000. So this model provides opportunities for participants to be more active, critical, and creative in the learning process, and helps students better understand abstract and complex concepts. The implication of this research is the need for the application of innovative learning models such as Learning Cycle 5E to improve the quality of physics learning in schools, so that students can achieve the skills demanded by the curriculum and be able to compete in today's educational challenges.
The Redefining Scientific Literacy through AI-Augmented Contextual Learning: Preparing Future-Ready Students in a Digital Era: Redefining Scientific Literacy Through AI-Augmented Contextual Learning for Future-Ready Student Nadia Putri; Stefanie Astrid Aipassa
International Journal of Contextual Science Education Vol. 3 No. 4 (2025): October - December 2025
Publisher : Postgraduate Program, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijcse.v3i4.1232

Abstract

The rapid evolution of Artificial Intelligence (AI) has fundamentally transformed the educational landscape, reshaping how students learn, interact, and construct scientific understanding. This study seeks to redefine the construct of scientific literacy through the integration of AI-augmented contextual learning, aiming to prepare future-ready students capable of thriving in an era characterized by digital complexity and global interconnectivity. Using a mixed-methods design, this research examines the impact of AI-assisted contextual learning—utilizing intelligent tutoring systems, adaptive simulations, and data-driven feedback mechanisms—on students’ conceptual understanding, critical reasoning, and inquiry-based engagement in science learning. Quantitative findings indicate that students exposed to AI-augmented environments demonstrate significantly higher retention and application of scientific concepts compared to those taught through conventional methods. Qualitative analyses further reveal that AI tools foster metacognitive awareness, curiosity-driven exploration, and ethical sensitivity in scientific inquiry. The study emphasizing adaptability, creativity, and human–machine collaboration as integral dimensions of modern scientific understanding.
Co-Authors Barinta Nur Respasari Hikmawati I Wayan Gunada Joni Rokhmat Nadia Putri