Guidelines for Enhancing Artificial Intelligence Literacy and Professional Competencies of Educational Personnel in Non-Formal Education: A Case Study of Phan Thong Non-Formal Education Center, Chonburi Province
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Abstract
Background and Aim: Artificial Intelligence (AI) has emerged as a transformative force in education, creating new opportunities for enhancing teaching, learning, and educational management. In non-formal education settings, where learners exhibit diverse educational needs and backgrounds, educational personnel are increasingly required to possess both AI literacy and the professional competencies necessary to effectively integrate AI technologies into instructional practices. This study aimed to examine the effectiveness of an AI literacy development program and to formulate practical guidelines for strengthening AI literacy and professional competencies among educational personnel at the Phan Thong Non-Formal Education Center, Chonburi Province, Thailand.
Materials and Methods: This study employed a concurrent mixed-methods research design. The quantitative phase involved 26 educational personnel selected through census sampling. Data were collected using a researcher-developed questionnaire measuring AI awareness, AI-related instructional competencies, and training effectiveness. The qualitative phase included semi-structured interviews, classroom observations, implementation records, and document analysis. Quantitative data were analyzed using descriptive statistics and paired-sample t-tests, whereas qualitative data were analyzed through thematic analysis. Findings from both phases were integrated to develop evidence-based guidelines.
Results: The findings revealed significant improvements in participants’ AI literacy and professional competencies following the intervention. Mean achievement scores increased substantially from 17.29 before the training to 34.27 after the training (p < .05). Improvements were observed across all dimensions of AI awareness, with self-reflection demonstrating the greatest gain. Despite these positive outcomes, technology readiness remained at a moderate level (M = 3.04), indicating continuing challenges related to infrastructure and institutional support. Based on the integrated findings, four key guidelines were developed: (1) targeted professional development in AI applications, (2) enhanced institutional support for digital infrastructure, (3) promotion of collaborative and professional learning communities, and (4) continuous monitoring and evaluation supported by clear organizational policies.
Conclusion: The study demonstrates that enhancing AI literacy and professional competencies among educational personnel requires a systematic and sustainable approach that extends beyond short-term training initiatives. Continuous professional development, supportive institutional policies, and adequate technological infrastructure are essential for effective AI integration in non-formal education. The proposed guidelines provide a practical framework for educational institutions seeking to strengthen AI readiness and adapt to ongoing digital transformation.
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