Grounding AI-in-Education Development in Teachers' Voices: Findings from a National Survey in Indonesia

2026-04-02

AI Summary

This study addresses the scarcity of large-scale, teacher-centered empirical research in Indonesia, which has hindered the development of localized AI-in-education systems and policies. Through a nationwide survey of 349 K–12 teachers, it offers the first systematic investigation—grounded in teachers’ perspectives—into the current use, needs, and barriers related to AI applications in lesson preparation, content generation, and media production. Integrating quantitative analysis with multidimensional indicators, the findings reveal significant disparities in AI adoption: primary school teachers exhibit more consistent usage, while educators in eastern regions report higher acceptance. Key constraints include suboptimal generic output quality, inadequate infrastructure, and insufficient localization. The study underscores how geographic region, educational level, and teaching experience shape AI uptake, highlighting the critical role of contextual adaptation in effectively implementing AI in educational settings.

Abstract

Despite emerging use in Indonesian classrooms, there is limited large-scale, teacher-centred evidence on how AI is used in practice and what support teachers need, hindering the development of context-appropriate AI systems and policies. To address this gap, we conduct a nationwide survey of 349 K-12 teachers across elementary, junior high, and senior high schools. We find increasing use of AI for pedagogy, content development, and teaching media, although adoption remains uneven. Elementary teachers report more consistent use, while senior high teachers engage less; mid-career teachers assign higher importance to AI, and teachers in Eastern Indonesia perceive greater value. Across levels, teachers primarily use AI to reduce instructional preparation workload (e.g., assessment, lesson planning, and material development). However, generic outputs, infrastructure constraints, and limited contextual alignment continue to hinder effective classroom integration.

Problem

• AI in Education
• teacher perspectives
• classroom integration
• contextual alignment
• educational policy

Innovation

• teacher-centered AI
• national survey
• AI in education
• contextual alignment
• instructional workload reduction