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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA)
Rosaniya E Rehiara
Universitas Cenderawasih
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics

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The Effectiveness of Implementing PBL and Susan Loucks Horsley Syntax Combination with the Deep Learning Approach to Science Process Skills in Junior High School Rosaniya E Rehiara
Jurnal Penelitian Pendidikan IPA Vol 12 No 6 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i6.15296

Abstract

This study aims to determine the effectiveness of the application of a combination of PBL and Susan Loucks Horsley (SLH) syntax with a deep learning approach on students' science process skills in junior high school science learning. This study used a quasi-experimental Nonequivalent Control Group design with a purposive sampling technique, where the school studied was grade VIII students of SMP Negeri 6 Sentani, Jayapura Regency. Data collection techniques were questionnaires and observation sheets. Data analysis was carried out descriptively and quantitatively, using independent sample-test, N-Gain, and effect-size tests. The results showed that the application of a combination of PBL and SLH syntax with a deep learning approach can improve students' science process skills in science learning at SMP Negeri 6 Sentani, Jayapura Regency. The results of the difference test showed a significant difference in the science process skills of students taught using a combination of PBL and SLH syntax with a deep learning approach with students taught using a conventional model. The value of the science process skills of students taught using a combination of PBL and SLH science syntax with a deep learning approach was higher than the value of students taught using a conventional model. The effectiveness of the combination of PBL and SLH syntax with the deep learning approach is in the high category based on the N-Gain value and effect-size test.
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