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Edusainstika: Jurnal Pembelajaran MIPA
Published by Universitas Islam Negeri Mahmud Yunus Batusangkar
ISSN : -     EISSN : 28079388     DOI : http://dx.doi.org/10.31958/je
Core Subject : Science, Education,
Biochemistry, Genetics & Molecular Biology Chemistry Education Mathematics Physics
Edusainstika : Jurnal Pembelajaran MIPA is a peer-reviewed journal and publishing education journal especially in the Natural Science Education, Biology Education, Chemistry Education, Physics Education, and Mathematics Education. The journal invites scholars, researchers, practitioners and experts of education to submit articles to be published in this journal.
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 62 Documents
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Need Need Analysis for the Design of an Online Module Based on Cognitive Conflict and the Deep Learning Approach to Correct Students’ Misconceptions About Light Waves Kesya Yumna Salsabila; Fatni Mufit; Ratnawulan; Fauziah Ulmi
Edusainstika Vol 6 No 1 (2026)
Publisher : Universitas Islam Negeri Mahmud Yunus Batusangkar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31958/je.v6i1.17441

Abstract

Students’ conceptual understanding of light waves remains relatively low, while the instructional materials currently in use have not been able to optimally facilitate the remediation of misconceptions. This study aims to analyze the need to develop a cognitive conflict-based e-module integrated with the deep learning approach—an approach that emphasizes meaningful, reflective, and enjoyable conceptual understanding through the components of meaningful learning, mindful learning, and joyful learning. The integration of cognitive conflict with the deep learning approach in the topic of light waves represents a novelty in this research, given that previous studies generally focused only on one of these approaches or combined cognitive conflict with Augmented Reality technology. This study is a preliminary investigation within Plomp’s preliminary research model for instructional design, with data collected through interviews with 2 physics teachers and 3 students, as well as a four-tier multiple-choice diagnostic test administered to 31 twelfth-grade students in Phase F at MAN 3 in Padang. The analysis results indicate that 69.7% of students held misconceptions, while the instructional materials used were still dominated by printed textbooks and worksheets and did not support concept visualization or the remediation of misconceptions. These findings underscore the need to develop e-modules based on cognitive conflict and a deep learning approach that align with the needs of teachers and students, while also contributing to the development of digital physics instructional materials capable of visualizing abstract concepts and supporting the remediation of misconceptions more effectively.
Pengembangan Lembar Kerja Peserta Didik (LKPD) Berbasis Problem-Based Learning (PBL) Dengan Pendekatan Deep Learning Pada Materi Ekosistem Kelas X SMAN 1 Rambatan Ghazi Hanif Ghazali; DWI RINI KURNIA FITRI
Edusainstika Vol 6 No 1 (2026)
Publisher : Universitas Islam Negeri Mahmud Yunus Batusangkar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31958/je.v6i1.17443

Abstract

Developing teaching materials in the modern era presents new challenges, particularly regarding technology integration and inclusivity. This study developed a student worksheet (LKPD) based on Problem-Based Learning (PBL) and a Deep Learning approach for the topic of ecosystems, employing the Research and Development (R&D) method with the 4D model (Define, Design, Develop, Disseminate). The research subjects consisted of 34 tenth-grade high school students. The results indicate that the PBL-based worksheet incorporating the Deep Learning approach for the ecosystem topic is highly valid, achieving a score of 94%. Practicality test results showed scores of 98% for teachers and 80% for students, corresponding to "highly practical" and "practical" categories, respectively. Thus, the PBL-based worksheet using the Deep Learning approach for the ecosystem topic has proven practical and suitable for supporting biology instruction.

Page 7 of 7 | Total Record : 62

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