Maria Senisum
Program Studi Pendidikan Guru Sekolah Dasar, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Katolik Indonesia Santu Paulus Ruteng, Jalan Ahmad Yani Nomor 10, Ruteng, Nusa Tenggara Timur 86516, Indonesia

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Implementasi Model GIReSiMCo Berorientasi Deep Learning untuk Meningkatkan Literasi Sains Siswa pada Pembelajaran Biologi Maria Senisum
Panthera : Jurnal Ilmiah Pendidikan Sains dan Terapan Vol. 6 No. 2 (2026): April
Publisher : Lembaga Pendidikan, Penelitian, dan Pengabdian Kamandanu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/panthera.v6i2.1218

Abstract

This study aims to determine the effect of the application of the GIReSiMCo model oriented to deep learning on students' scientific literacy, and analyze students' scientific literacy abilities based on scientific literacy indicators. The research design is quasi-experimental in the form of a pretest-posttest control group design involving 67 students of grade XI. The instrument used in this study is 22 questions on scientific literacy in biology in the form of multiple choices and essays. The 22 questions are a combination of four indicators of scientific literacy, namely scientific literacy explaining phenomena scientifically, designing investigations, interpreting data, and drawing conclusions. To determine the effect of the GIReSiMCo learning model oriented to deep learning, the data were analyzed using the independent sample t-test formula, while the analysis of scientific literacy abilities based on the four indicators was analyzed by calculating the average value per indicator in each class. The results of the t-test analysis showed that the p-value of 0.00 was smaller than 0.05, which means that the GIReSiMCo model oriented to deep learning had a significant effect on scientific literacy. Of the four scientific literacy indicators influenced by the GIReSiMCo learning model, the ability to explain phenomena achieved the highest average score, at 87.5. The indicator for designing investigations scored 87.1; the indicator for interpreting data scored 85.7; and the indicator for drawing conclusions scored 82.5. The deep learning-oriented GIReSiMCo learning model is suitable for application in biology instruction to improve students' scientific literacy skills.