Transformasi Pembelajaran Kimia Melalui Deep Learning: Strategi Holistik Mengembangkan Kompetensi Emosional Siswa pada Topik Larutan Penyangga

Abstract

This study aims to analyze the impact of implementing a Deep Learning approach on students' emotional

competence during chemistry instruction on the topic of buffer solutions in Grade XI at SMA Negeri 48

Jakarta. The study employed a quantitative approach with a quasi-experimental, pretest-posttest design

involving 68 students, divided into an experimental group taught using the Deep Learning approach and a

control group receiving conventional instruction. Data on emotional competence were collected using a

questionnaire measuring aspects of self-awareness, emotional management, self-motivation, empathy, and

social skills. The data were analyzed using an Independent Sample t-test to examine differences in

emotional competence between the two groups. The results indicate that the implementation of the Deep

Learning approach had a significant effect on improving students' emotional competence (0.004 < 0.05).

These findings demonstrate that instruction focused on deep understanding, reflection, collaboration, and

authentic problem-solving not only supports the chemistry learning process but also contributes to the

development of students' emotional competence. Thus, the Deep Learning approach serves as an effective

instructional strategy for transforming chemistry education into a more holistic experience by

strengthening students' emotional competence, particularly regarding the topic of buffer solutions.

Keywords: Deep Learning, emotional competence, chemistry instruction, buffer solutions, instructional

transformation.