Deep Learning-based Interactive E-module to Enhance English Learning Motivation in Elementary School
DOI:
https://doi.org/10.26877/eternal.v7i1.2165Keywords:
Interactive e-module , Deep Learning, Motivation, English as a Foreign Language (EFL), Elementary educationAbstract
This study investigates the impact of a Deep Learning-based interactive e-module on the motivation of primary school students learning English as a foreign language. A quasi-experimental design with a pre-test and post-test control group was employed, involving 60 fifth-grade students in West Java, Indonesia. The experimental group (n=30) used the Deep Learning-based module, while the control group (n=30) received traditional instruction. Motivation levels were measured using a validated questionnaire based on Self-Determination Theory, supported by interviews and classroom observations for qualitative insight. Quantitative analysis revealed a statistically significant increase in motivation among students in the experimental group (t(29) = 10.45, p < 0.001, d = 2.17), whereas the control group showed no significant change. Thematic analysis of interviews and observations confirmed higher engagement, enjoyment, and autonomy among students using the e-module. These findings demonstrate that Deep Learning technology, when applied thoughtfully, can create personalized, responsive learning experiences that foster intrinsic motivation in young learners. This study contributes to the limited body of research on AI-powered educational interventions at the primary level and offers practical implications for digital learning design in EFL contexts. Future research is recommended to explore long-term effects and broader implementation across diverse educational settings.
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