Deep learning as an innovative solution to literacy and numeracy challenges in elementary schools
DOI:
https://doi.org/10.26740/eds.v10n1.p67-86Keywords:
Deep learning, Literacy achievement, Numeracy achievement, Elementary educationAbstract
Low literacy and numeracy achievement among Indonesian elementary school students remains a critical pedagogical challenge demanding systematic and contextual innovation. This study aims to analyze the implementation of the deep learning approach as an innovative solution to literacy and numeracy challenges. A qualitative methodology with a case study design was employed to enable in-depth exploration within real-life contexts. Participants consisted of one school principal, four teachers (Grades IV-VI), eight students, and three parents selected through purposive sampling. Data were collected through participatory observation, semi-structured in-depth interviews, and document analysis, and analyzed using Miles and Huberman's interactive model encompassing data reduction, data display, and iterative conclusion drawing. Trustworthiness was ensured through source and method triangulation alongside member checking. Findings reveal that the implementation of deep learning across three integrated stages mindful, meaningful, and joyful learning improved average literacy scores by 17 percentage points (from 62% to 79%) and numeracy by 16 percentage points (from 60% to 76%) over a three-month intervention period. Beyond quantitative gains, significant qualitative improvements were documented in student motivation, collaborative engagement, critical thinking, and academic self-confidence. Eighty-seven percent of teachers reported that this approach effectively facilitated the integration of digital technology in learning. This study concludes that deep learning constitutes a relevant, innovative, and replicable pedagogical strategy for addressing elementary-level literacy and numeracy challenges while simultaneously enhancing the quality of technology-integrated learning.
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