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Enhancing Junior High School Teachers’ English Vocabulary Competence through AI-Based Neo-Sorogan Learning Model Training Dewi Utari; Andi Kristanto; Husni Mubarok; Mujahidah Auliya Ihsani
Aktual: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 3 (2026): Aktual: Jurnal Pengabdian Kepada Masyarakat
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/aktual.v4i3.907

Abstract

Background: Rapid advances in digital technology and artificial intelligence (AI) are transforming the educational landscape, particularly at the junior high school level. This stage is crucial for developing students' critical thinking skills, fostering independent learning, and shaping their character. During this transitional phase of cognitive and social development, students need intensive mentorship, meaningful interactions, and learning experiences that accommodate diverse abilities and learning styles.Aims: This study aimed to better equip teachers to implement more personalized, effective, and meaningful English vocabulary learning experiences through the AI-based Neo-Sorogan model.  Ultimately, it aimed to enhance the quality of human resources in education and prepare them to address 21st-century challenges.Methods: A mixed-methods research design integrating quantitative and qualitative techniques was employed, using paired comparisons, a Likert scale, and descriptive statistics.Results: The study's results demonstrated a significant improvement in vocabulary skills, with pre-test scores averaging (M = 64.28, SD = 8.47) and post-test scores averaging (M = 78.63, SD = 7.21). The analysis yielded a t-value of -11.98 with 42 degrees of freedom (t(42) = -11.98, p < 0.001), indicating strong statistical significance and a robust effect size (d = 1.83). Furthermore, participant satisfaction was categorized as high.Conclusion: This study showed participants' enthusiasm improved understanding of the AI-based Neo-Sorogan model, focusing on individualized learning and interaction. They designed subject-specific activities and rated their satisfaction at an average of 4.59 out of 5, reflecting their increased willingness to implement AI strategies in the classroom.