The Effectiveness of Flipped Classroom Integrated with Deep Learning Based on Multiple Representations on Chemical Equilibrium Material to Improve HOTS

Abstract

Abstract: The Effectiveness of Flipped Classroom Integrated with Deep Learning Based on Multiple Representations on Chemical Equilibrium Material to Improve HOTS. Objectives: This study aims to describe the effectiveness of a flipped classroom integrated with a deep learning approach based on multiple representations on chemical equilibrium material in improving students' Higher Order Thinking Skills (HOTS). Methods: This study employed a quasi-experimental method with a nonequivalent pretest-posttest control group design. The sample was selected through purposive sampling, consisting of class XI.F.4 as the experimental class and XI.F.5 as the control class. Data were analyzed using the Independent Sample T-Test. Findings: The average n-gain HOTS of students in the experimental class was 0.35, categorized as moderate and significantly higher than that of the control class. Conclusion: The flipped classroom integrated with deep learning based on multiple representations on chemical equilibrium material was effective in improving students' HOTS.