The Use of Deep Learning in Fostering Independence and Discipline Among Elementary School Students: A Literature Review

Abstract

The weakening of independence and discipline among elementary school students in the digital age has become a fundamental issue that demands a more substantial pedagogical response. The deep learning approach, which emphasizes meaningful, reflective, and enjoyable cognitive engagement, is believed to hold great potential for holistically shaping students’ character. This article aims to analyze the role of the deep learning approach in fostering independence and discipline in elementary school students through a systematic literature review. This study employs a literature review method, analyzing 31 scholarly sources comprising national and international journal articles, policy documents, and monographs published between 1976 and 2026. The analytical technique used is content analysis with a descriptive-analytical approach. The study findings indicate that a deep learning approach characterized by mindful, meaningful, and joyful learning significantly supports the development of independent character through improvements in students’ self-regulation, learning initiative, and decision-making skills. On the other hand, deep learning also contributes to strengthening disciplined character through the internalization of values, reflective habits, and an appreciation of rules that grow from students’ self-awareness. Implementing this approach in elementary schools requires support from teachers as facilitators, contextual learning design, and education policies oriented toward meaningful learning.