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Teacher Competency and Readiness for Artificial Intelligence Integration in High School Education

Joe-m Mahilum, Samson Lausa
Psychology and Education: A Multidisciplinary Journal · 2026-05-04 · DOI 10.70838/pemj.560201
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Token#7820 of SciMatic Articles (ERC-1155), fixed supply 1,000,000
Contract0x0E596B4bb924937aA35D9b342A90347ed6F05eF8
Mint transaction0x8f3865bf1d19867a7795dd1dbf6391858f3388d077b82e50c356e6a335558f8a · block 12110917
Minted2026-10-02 12:45 UTC
Hash on chain0x90dd684bf0e5d444754ccbcacb3635973f03442146c4c9417832397ec59a8279
SHA-256 of the record0x90dd684bf0e5d444754ccbcacb3635973f03442146c4c9417832397ec59a8279
Article today Matches the anchored record.

Allocation at minting

HolderWalletMintedHolds now
SciMatic (10%) 0xc35709AB…277732 100,000 100,000
Joe-m Mahilum 0x56B9a69f…65e258 450,000 450,000
Samson Lausa 0x6e8CFe37…C13346 450,000 450,000

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{"abstract":"This study assessed the competency and readiness of high school teachers in the Division of Escalante City for the integration of Artificial Intelligence (AI) in classroom instruction. Anchored on the Technological Pedagogical Content Knowledge (TPACK) framework, AI Literacy Framework, and Diffusion of Innovation Theory, the research examined four domains: technical, pedagogical, ethical, and reflective competencies. A descriptive-correlational quantitative design was employed, involving 328 public secondary school teachers during the School Year 2025–2026. Data was collected using a validated and reliability-tested survey questionnaire and analyzed through descriptive and inferential statistics such as mean and standard deviation, Pearson R correlation, and regression analysis. Findings revealed that teachers demonstrated high levels of competence and readiness for AI integration, with stronger performance in pedagogical and ethical domains compared to technical skills. Despite these positive indicators, correlation analysis showed no significant relationship between competence and readiness, suggesting that these constructs function independently. Additionally, demographic factors such as years of service, access to digital resources, and prior training did not significantly influence readiness levels. The results indicate that while teachers possess the foundational skills and preparedness to integrate AI, gaps remain in advanced AI applications, infrastructure access, and specialized training. These findings imply that readiness to adopt AI may be shaped by broader contextual and institutional factors beyond individual competency. Hence, strengthening professional development programs focused on advanced AI competencies, ethical considerations, and reflective practices is essential. Furthermore, enhancing institutional support systems and aligning educational policies with emerging technological demands are critical to ensuring effective AI integration. The findings provide empirical evidence to inform policy development, strategic planning, and the implementation of sustainable AI integration initiatives in Philippine secondary education.","abstract_source":"original","authors":["Joe-m Mahilum","Samson Lausa"],"date":"2026-05-04","doi":"10.70838/pemj.560201","id":7820,"issue":2,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"7c74bc5f8f8c966aa8ea8a173cbbe3e2fb02b5c1e2b5286c12d140fc0c17110e","schema":"scimatic-article/1","title":"Teacher Competency and Readiness for Artificial Intelligence Integration in High School Education","volume":56}

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