School Readiness for Coding and AI Education: A Case Study of Policy Implementation and Pedagogical Adaptation in Indonesia

Bagus Sulasmono, Yuliana Friska, Supardi Uki Sajiman, Hasbullah Hasbullah, Syahfitri Purnama

Abstract


The educational transformation driven by the Industrial Revolution 4.0 necessitates digital literacy and computational thinking, reflected in Indonesia’s 2025 policy mandating Coding and AI as compulsory electives. This study examines policy implementation, student competency outcomes, barriers, and adaptive strategies within an early-adopting school context.A single instrumental case study was conducted at HelloMotion High School, selected for its pioneering role in digital curriculum integration prior to the national mandate. Data were collected from September to November 2025 through in-depth interviews with six key informants (one principal, one vice-principal, one teacher, and three students) and a survey of 99 students. Analysis employed Miles and Huberman’s interactive model alongside descriptive statistics.Findings reveal a “Literacy–Aspiration Gap,” where students demonstrated improved logical thinking (M = 3.35, SD = 0.91) but low interest in technology-related careers (M = 2.21, SD = 1.11). The primary challenges were identified as second-order barriers, including teacher beliefs and students’ “instant generation” mindset, rather than infrastructural limitations. In response, the school implemented an Integrative Strategy Model combining project-based learning with specialized, diverse grouping to enhance engagement and learning outcomes.The study highlights that successful implementation of Coding and AI education extends beyond infrastructure provision to addressing pedagogical and attitudinal barriers. It contributes to policy discourse by emphasizing the need for interventions targeting internal resistance and aligning skill development with student motivation, ensuring more effective and sustainable digital education reform.

Keywords


education policy; digital education; coding; artificial intelligence; instrumental case study

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DOI: https://doi.org/10.35445/alishlah.v18i1.8910

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