Fitri Afrikasari, Enung Hasanah, Dian Hidayati

Implementation of the Deep Learning Approach in Elementary Schools

Introduction

Implementation of the deep learning approach in elementary schools . Discover deep learning implementation in Indonesian elementary schools. Qualitative study uncovers teacher challenges in planning, organization, and evaluation, noting limited innovation.

Abstract

The deep learning approach is the latest innovation in the Indonesian education system proposed by the Ministry of Primary and Secondary Education in early 2025. The essence of this approach is to create a learning process that is aware, meaningful, and joyful for students. The purpose of the study is to examine the implementation of deep learning from the way teachers plan, organize, implement, and evaluate deep learning in elementary schools. The research method uses a qualitative method with interview data collection techniques and observation of learning in the classroom. The respondent is an elementary school classroom teacher in the Mantrijeron Yogyakarta Ministry of Education who has implemented deep learning. Thematic data analysis with the help of atlas.ti application 9. The results of the research of elementary school teachers implementing deep learning are still very limited, starting from making a learning plan exactly the same as the example from the ministry, there are no new innovations, learning activities that are just following the directions of the curriculum reference book have not shown creativity independently of the teacher and in terms of organizing students, educators emphasize more on grouping students in learning. A tool to measure the success of deep learning can be done by means of project-based assessments, percentages and self-assessment.

Review

This timely study embarks on a crucial examination of the initial implementation of the deep learning approach, a new national educational initiative in Indonesian elementary schools. Given its recent introduction by the Ministry of Primary and Secondary Education in early 2025, the research addresses a highly relevant and pressing issue. The stated purpose—to explore how teachers plan, organize, implement, and evaluate deep learning—is well-defined and aligns perfectly with the need for early insights into a significant policy shift. The qualitative methodological approach, employing interviews and classroom observations, is appropriate for exploring the nuanced realities of pedagogical change at the ground level, offering a valuable preliminary understanding of this ambitious reform. The abstract presents compelling, albeit concerning, findings. The observation that elementary school teachers' implementation of deep learning remains "very limited," largely adhering strictly to ministerial examples without new innovations or independent creativity, is a critical insight. This suggests a potential gap between policy intent (to create "aware, meaningful, and joyful" learning) and current classroom practice, where rote compliance may supersede genuine pedagogical transformation. While the abstract mentions grouping students and proposing project-based assessments, percentages, and self-assessment as tools for success, further detail on what "percentages" entails would be beneficial. Methodologically, clarity is needed regarding the "respondent is an elementary school classroom teacher in the Mantrijeron Yogyakarta Ministry of Education"; presumably, this refers to teachers *within schools overseen by* that specific Ministry unit. Additionally, specifying the number of respondents would strengthen the methodological description. Despite these minor areas for clarification, the study offers valuable early evidence that should be seriously considered by policymakers and teacher educators. The findings underscore the imperative for more targeted and empowering professional development that genuinely fosters teacher creativity and adaptability, moving beyond mere adherence to curriculum references. For future iterations of this research, it would be beneficial to delve deeper into the systemic factors contributing to the limited innovation, such as resource availability, training quality, or perceived pressures. Furthermore, exploring the actual impact of this nascent implementation on student engagement and learning outcomes would provide a comprehensive picture. This paper serves as an important foundational piece, highlighting the challenges inherent in large-scale educational reforms and pointing towards areas requiring immediate attention for the deep learning approach to achieve its ambitious goals.

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