Competence, Career, and Compliance: An Integrated Framework Aligning Teacher AI Literacy with National Performance, UNESCO Standards, and Data-Protection Law in Thailand

作者
Paritchaya Sarakan,Anucha Somabut,Lan Thi Nguyen,Parama Kwangmuang
出处
期刊:Journal of education and training studies [Redfame Publishing]
卷期号:15 (1): 77-77
标识
DOI:10.11114/jets.v15i1.9098
摘要

Teacher artificial intelligence (AI) literacy has become a policy priority, yet the frameworks defining it circulate apart from the national systems that govern how teachers are trained, appraised, and promoted, and apart from the data-protection regimes governing classroom AI use. This disconnection helps explain why professional development (PD) in AI remains fragmented, tool-centric, and weakly adopted. This article develops an integrated framework aligning teacher AI-literacy competencies with three policy layers in Thailand: the Office of the Teacher Civil Service and Educational Personnel Commission's Performance Agreement (PA) and academic-standing system, the UNESCO AI Competency Framework for Teachers (2024), and the Personal Data Protection Act B.E. 2562 (PDPA). Using a structured policy document analysis and a directed crosswalk synthesis, the study maps a six-dimension model of teacher AI literacy onto national performance indicators and career progression, aligns that progression with UNESCO's acquire–deepen–create trajectory, and embeds PDPA obligations as a cross-cutting governance layer. The framework's principal output is an alignment matrix that translates competencies into evidence recognizable within the national performance system, complemented by a developmental progression map, a data-governance overlay, and a phased implementation roadmap. An expert panel (n = 5) rated the framework favorably (overall mean = 4.68) with moderate inter-rater concordance (Kendall's W = 0.42), and item-objective congruence supported the content validity of all mappings. The article argues that anchoring AI-literacy PD in existing accountability and legal structures may offer a more durable route to adoption than standalone training, and discusses the possible transferability of its design logic, rather than its specific mappings, to comparable jurisdictions.

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