Strategies for Preparing Teachers for Coding and Artificial Intelligence Education
DOI:
https://doi.org/10.33541/edumatsains.v10i4.8078Keywords:
Teacher Preparation, Coding, Artificial InteligenceAbstract
The implementation of Coding and Artificial Intelligence (AI) as a subject within the national curriculum requires a high level of teacher readiness, while most teachers come from non-ICT backgrounds and face limitations in infrastructure and learning resources. This study aims to describe the implementation of teacher preparation for instruction through collaboration between the Ministry of Primary and Secondary Education (Kemendikdasmen) and Training Provider Institutions, as well as to identify its outcomes and challenges. This research employed a descriptive quantitative approach involving 10,061 teachers from primary, junior, and senior high school. Data were collected through online and offline questionnaires, supported by interviews and document analysis. The results indicate that the teachers preparation was conducted in a structured and phased manner through In-Service Training 1 (IN1), On-the-Job Training (OJT), and In-Service Training 2 (IN2), supported by an integrated quality assurance system. The average level of participants’ understanding reached 82%, and most teachers reported being ready to teach. However, several challenges remain, including limited pedagogical competence among non-ICT teachers, inadequate infrastructure, and unstable internet access. Coding and Artificial Intelligence instruction was implemented using unplugged, plugged, and internet-based approaches, which encourage collaborative and project-based learning. This study concludes that the collaboration between Kemendikdasmen and LPD is effective in preparing teachers for CAI instruction. Continuous mentoring and the strengthening of the school ecosystem are key factors for the successful implementation of adaptive CAI learning that is relevant to the demands of 21st-century education.
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