Aug 2026· International Journal of Research on Multidisciplinary Studies· Vol 1, pp. 252· 0 citations· 14 references
TL;DR
The study concludes that the CPD-accredited AI program effectively massified foundational AI literacy in historically underserved regions and recommends the institutionalization of a "Competency-Based Technology Skills Enhancement Workshop."
Abstract
This study investigated the impact of Department of Information and Communications Technology (DICT) CPD-accredited capacity-building programs on Artificial Intelligence (AI) in Region IX and BASULTA to develop evidence-based courses and digital competency advancement. As we navigate the complexities of the "age of intelligence" following the 2022 generative AI surge, this research explored participant proficiency across five specialized modules, while simultaneously documenting baseline implementation challenges and infrastructural friction. Utilizing a descriptive-quantitative research design, the study employed purposive sampling to evaluate training participants through the DICT Standardized Training Evaluation Tool. Key findings from empirical data gathered between March and May 2026 indicate exceptionally high proficiency levels among participants. Mean evaluation ratings consistently ranged between 4.0 and 5.0, specifically within the critical dimensions of Mastery of Subject Matter and Instructional Methodology. Furthermore, analysis indicated that the structured training successfully bridged demographic gaps. While demographic groupings showed no statistically significant variance in ultimate proficiency, systemic external challenges, most notably intermittent internet connectivity and course pacing, were identified as primary friction points affecting the learning experience. The study concludes that the CPD-accredited AI program effectively massified foundational AI literacy in historically underserved regions. The research recommends the institutionalization of a "Competency-Based Technology Skills Enhancement Workshop." This proposed framework focuses heavily on subject-specific AI applications and the integration of offline-compatible digital tools, thereby ensuring a resilient and sustainable pedagogical transformation in the current post-digital era.
Findings reveal that the teacher's engagement is non-linear and front-loaded: while Behavioral Engagement peaked during the Design and Development phases through active material generation, it significantly declined during the Implementation phase due to infrastructural anxiety and instability.
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