Artificial Intelligence-Based Teacher Training in the Context of Coastal Schools: Evaluation Using the Kirkpatrick Model

Abstract

The development of artificial intelligence (AI) provides new opportunities for improving teachers' professional competencies, particularly in the development of digital learning tools. However, the implementation of AI-based training in coastal schools still faces obstacles, mainly related to infrastructure limitations and digital literacy. This study aims to evaluate the effectiveness of the Teacher Capacity Building Programme in the Use of AI for the development of learning tools at SMA Negeri 2 Bintan Pesisir, Riau Islands Province. The evaluation was conducted using Kirkpatrick's four-level model, which includes reaction, learning, behaviour, and results. This study used a mixed methods approach with data collection through questionnaires, pretest–posttest tests, and observation. The results showed that the training programme obtained an overall average score of 84.3, which is in the good to very good category. Specifically, the participants' reaction level scored 86.8, learning level 84.4, behavioural change 80.3, and final results 85.7. Correlation analysis between levels showed a coefficient of 0.87, indicating a strong linear relationship between evaluation components. These findings indicate that AI-based training contributes positively to improving teachers' ability to design digital learning tools, although its implementation is still influenced by contextual factors in schools. Theoretically, this study reinforces the relevance of the Kirkpatrick model in evaluating digital training. Practically, the results of this study can be used as a reference in designing technology-based teacher training programmes, especially in coastal areas and regions with digital limitations.