KEEFEKTIFAN PEMBELAJARAN BERBASIS META AI DENGAN METODE DRILL PADA LEMBAGA KURSUS DAN PELATIHAN CENDITAMA

Abstract

Abstract
This study aims to evaluate the effectiveness of Meta AI-based learning combined with the drill method in
improving learning outcomes at the Cenditama Training and Course Institute. Meta AI, as an artificial
intelligence technology, allows learning processes to become more adaptive and personalized, while the
drill method focuses on strengthening skills through repetitive practice. The research employed a mixedmethod

approach with a quasi-experimental design involving pretests, posttests, observation, interviews,
and documentation. The analysis results showed a significant increase in the average participant score from
63.0 to 81.0 after the implementation. Additionally, learners demonstrated increased motivation and active
engagement during the learning process. Instructors also benefited from the real-time feedback system and
the ability to tailor the learning approach to individual student needs. Based on these findings, the
integration of Meta AI with the drill method has proven effective in enhancing both learning outcomes and
the overall learning experience. This study recommends broader adoption of similar technologies in
vocational education institutions to foster more relevant and efficient learning environments.
Keywords : Meta AI, Drill Method, Adaptive Learning, Learning Effectiveness, Vocational Education,
Cenditama Course Institute