Mapping Deep Learning Quality in Senior High Schools Adopting the Deep Learning, Coding & Artificial Intelligence (DLCAAI) Model in Central Java as a Foundation for Evidence-Based Educational Policy

Abstract

Educational transformation in the era of artificial intelligence requires schools to build a humanistic-digital, reflective, collaborative, and data-driven learning ecosystem. This study aims to map the implementation quality of deep learning in State Senior High Schools adopting the Deep Learning, Coding & Artificial Intelligence (DLCAAI) model in Central Java and formulate its implications for evidence-based policy development (baseline assessment), involving 316 teachers from all DLCAAI model schools in the region. The research instrument was a 5-point Likert-scale questionnaire with 75 items covering deep learning principles, learning experiences,t he deep learning framework, graduate profiles, and learning assessment. Validity tests showed all items were valid (corrected item-total correlation > 0.30), while instrument reliability was very high (Cronbach’s Alpha = 0.992). Data analysis employed means, percentages, categories, and comparative dimensional analysis. Results indicate that the quality of deep learning implementation is 93.43%. The strongest dimensions include student-centered learning, psychological safety, character development, inclusivity, and digital integration. However, metacognitive reflection, formative assessment, learning differentiation, cross-disciplinary learning, and the utilization of learning data still require strengthening. The novelty of this research lies in developing the Baseline Architecture of Humanistic-Digital Deep Learning Ecosystem framework, which integrates deep learning, AI, reflective pedagogy, student agency, and evidence-based educational policy. This study confirms that baseline assessment functions as an educational diagnostic, a compass for school transformation, and a policy navigation system in the humanistic and sustainable AI-based educational transformation.