DEVELOPMENT OF AN ADDIE-BASED DEEP LEARNING MODEL TO ACHIEVE HEALTH DIMENSION GRADUATE PROFILE IN ELEMENTARY SCHOOL STUDENTS
DOI:
https://doi.org/10.54124/jlmp.v22i2.174Keywords:
Deep Learning, ADDIE, Health DimensionAbstract
This study develops and evaluates a deep learning–based instructional model using the ADDIE framework integrated with the Deep Learning Cycle (exploration, concept integration, reflection, real-world action) to enhance the health dimension of elementary school students’ graduate profiles. The research addresses low health knowledge and healthy living practices among students, often resulting from conventional, theory-oriented teaching. Conducted at SDN Pulau Kelapa 02 Pagi, Kepulauan Seribu, during the 2024/2025 academic year, the study involved 54 sixth-grade students through total sampling. Data collection employed cognitive tests (pretest–posttest), attitude observation sheets, and skill performance rubrics. Results showed an increase in cognitive scores from 55.22 to 77.39 with a normalized gain of 0.62 (moderate). Attitude scores averaged 83.52 (good), and skills averaged 86.30 (very good). Student engagement reached 93.5% (very good). Expert validation on content, media, and language yielded scores above 90 (highly feasible). The findings confirm that the deep learning–based model effectively integrates cognitive, affective, and psychomotor domains, supporting the achievement of the Student Profile, particularly in the health dimension, in elementary schools.
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