Optimizing the Role of English Sensor in Improving Students’ English Vocabulary Mastery through Digital Learning at MGMP SMAN 6 Makassar
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Abstract
Background: Students’ English vocabulary proficiency at SMAN 6 Makassar remains relatively low, with average scores ranging from 65 to 75. This issue is partly attributed to the suboptimal integration of digital technology in classroom instruction, despite the availability of adequate technological infrastructure.
Aims: This community service program aimed to optimize the use of the English Sensor platform for vocabulary learning, enhance the digital competence of MGMP English teachers, and strengthen students’ vocabulary mastery through the Word by Word Adventure model based on scaffolding and gamification.
Methods: The population consisted of English teachers in the MGMP forum and tenth-grade students at SMAN 6 Makassar. A total of 15 students were selected using purposive sampling, representing different proficiency levels based on teacher recommendations. The program was implemented through five stages: (1) socialization, (2) workshops implementing the Word by Word Adventure approach, (3) digital content development training, (4) classroom-based integration of English Sensor, and (5) monitoring and evaluation using pretest-posttest assessments, classroom observations, and participant feedback.
Results: Preliminary findings indicated that teachers began to adapt to technology-assisted instruction, while students demonstrated increased learning motivation. Pilot implementation showed a 27% improvement in students’ vocabulary mastery compared with pretest scores, indicating the effectiveness of English Sensor in supporting digital-based vocabulary learning.
Conclusion: The optimization of English Sensor contributed positively to improve students’ vocabulary mastery and strengthen teachers’ digital integration skills. The program also supported the achievement of SDG 4 (Quality Education), SDG 10 (Reduced Inequalities), and Higher Education Key Performance Indicators (IKU).
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Copyright (c) 2025 Supriadi Supriadi, Rizka Indahyanti, Andi Muh Akbar Saputra, Arif Hukmi, Andi Faizal, Nurul Ilmi Hairullah

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