Anggit Grahito Wicaksono
Univeritas Slamet Riyadi, Indonesia

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Deep Learning Approach in Education: A Systematic Literature Review on Mindful, Meaningful, and Joyful Learning Models Jumanto; Anggit Grahito Wicaksono
Attractive : Innovative Education Journal Vol. 8 No. 2 (2026): Attractive : Innovative Education Journal
Publisher : CV. Creative Tugu Pena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51278/aj.v8i2.2356

Abstract

This study aims to systematically examine instructional models that align with the principles of deep learning, specifically mindful learning, joyful learning, and meaningful learning. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines to ensure transparency and methodological rigor. Literature was retrieved from Google Scholar, Scopus, ERIC, and SpringerLink, covering publications from 2020 to 2025. After duplicate removal and multi-stage screening, 35 empirical studies met the inclusion criteria and were analyzed using thematic analysis through open, axial, and selective coding. Inter-rater reliability was established using Cohen’s Kappa (κ = 0.82), indicating substantial agreement. The findings reveal that meaningful learning is the most consistently supported dimension across instructional models, followed by joyful learning, while mindful learning remains less explicitly integrated. Project-Based Learning and Problem-Based Learning emerged as the most comprehensive models, demonstrating alignment across all three dimensions by integrating authentic problem contexts, collaborative engagement, and reflective processes. In contrast, gamified and play-based approaches predominantly support joyful engagement but often lack structured reflective scaffolding. The review suggests that deep learning is most effectively fostered through pedagogical frameworks that intentionally integrate cognitive integration, emotional engagement, and metacognitive awareness. These findings provide a conceptual foundation for developing more balanced and holistic instructional designs aligned with contemporary deep learning principles.