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All Journal Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal)
Dhea Kamelia Fauziah
Universitas Pendidikan Indonesia
Agriculture, Biological Sciences & Forestry Chemistry Education Physics

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The Application of the Quantum Teaching Model with a Deep Learning Approach to Improve Students’ Problem-Solving Skills in the Topic of Static Fluids Dhea Kamelia Fauziah; Muslim; Hera Novia; Devi Eliviani
Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Vol. 7 No. 3 (2026): August (Inpres)
Publisher : Mataram University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/goescienceed.v7i3.2066

Abstract

This study aims to analyze students’ problem-solving skills through the application of the Quantum Teaching model with a deep learning approach to static fluid. The research method used is a quantitative method with a between-group design, specifically a quasi-experimental research design. The type of quasi-experimental research design used in this study is a nonequivalent control group design, in which there are two classes used, namely a control class and an experimental class. The research instrument used is a problem-solving ability instrument developed based on Polya’s indicators, consisting of three items. The data analysis employed N-Gain scores and a t-test hypothesis test, which met the prerequisites of normality and homogeneity. The results indicate that the N-Gain scores in the experimental class were higher than those in the control class, with respective values of 0.71 and 0.42. These results were supported by the t-test hypothesis test, which showed an Asyimp sig (2-tailed) value—under the assumption of unequal variances—of <0.05. This indicates a significant difference in the improvement of problem-solving skills between students in the experimental and control classes. Thus, the Quantum Teaching model with a deep learning approach can serve as an alternative for enhancing problem-solving skills students, particularly in the area of static fluids.
The Application of Guided Inquiry with a Deep Learning Approach in Improve Students' Cognitive Abilities on Heat Material Devi Eliviani; Muslim; Ridwan Efendi; Dhea Kamelia Fauziah
Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Vol. 7 No. 3 (2026): August (Inpres)
Publisher : Mataram University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/goescienceed.v7i3.2264

Abstract

The teaching of physics, specifically the topic of heat, is essentially aimed at facilitating a deep understanding of concepts and enhancing pupils’ higher-order cognitive skills. However, the results of a preliminary field study indicate that the learning process is still hampered by the presentation of abstract concepts, meaning that pupils tend to simply memorise formulas without meaningful understanding. This study aims to analyze students’ cognitive abilities through the application of a guided inquiry learning model with a deep learning approach to the topic of heat. The research method used was a quantitative method with a between-group design, specifically a quasi-experimental research design. The specific research design employed was a pretest-posttest design with a non-equivalent control group. The research instrument used was a cognitive ability test consisting of thirteen items. Data analysis utilized the N-Gain score and the Mann-Whitney U test, which met the prerequisites of normality and homogeneity. The results showed that the N-Gain scores in the experimental class were higher than those in the control class, with values of 0.67 and 0.57, respectively. These results were supported by the Mann-Whitney U test, which yielded an Asymp. Sig. (2-tailed) value of 0.029 under the assumption of unequal variances (0.029 < 0.05). This indicates a significant difference in the improvement of students’ cognitive abilities between the experimental and control classes. Therefore, the guided inquiry learning model with a deep learning approach can serve as an alternative solution for enhancing students’ cognitive abilities.
Co-Authors Devi Eliviani Efendi, Ridwan Hera Novia Muslim