"Education Council" Reports on Thailand's educational status for Q2 and accelerates development of the "education database" to serve as an infrastructure for analysis connecting data both inside and outside the system.
On 21 May 2026, a reporter stated that Associate Professor Prawit Erawan, Secretary-General of the Education Council (EC), chaired a seminar to present the Q2 report of Thailand's educational status for fiscal year 2026. The event was attended by Mr. Supachai Chanpum, Deputy Secretary-General of the Education Council; Ms. Rungnapa Jitrorojanarak, Advisor on Research and Educational Assessment; Ms. Ampa Promwat, Advisor on Educational Policy and Planning; Mr. Weerapong Ujaroen, Director of the Educational Management Assessment Office; alongside experts, academics, representatives from related agencies, administrators, teachers, and education personnel. The seminar took place at Prince Palace Hotel, Mahanak, Bangkok, and was simultaneously broadcast live via the Education Council's Facebook page.
Associate Professor Prawit opened the seminar and presented the Q2 educational status report for fiscal year 2026 under the theme "Educational Data for Designing Learning Pathways in a Human-Centered AI Society." A key concept in this quarterly report is upgrading the education database to connect with real life, future learners, and international standards. The Q1 report highlighted that Thailand's education system faces structural crossroads amid global changes.
Currently, the EC is developing INES (the education database) to serve as an analytical infrastructure connecting data both inside and outside the system in line with the OECD international framework. This will enable effective future forecasting and international trend comparisons. To design a stable educational architecture, four interconnected challenges must be addressed:
Part 1: Linking real-world data with the education system. The education system must look beyond schools and exam results. Using real-world data as a foundation for education system design and policy must align with labor market needs by analyzing three dimensions:
1. Labor market data and real-life outcomes of learners. Although Thailand has a high employment rate of 67.2% and a low unemployment rate of 0.8% (2024 data), it faces significant challenges in income and job productivity. Comparatively, Thai bachelor's graduates have a 75.3% employment rate, 12.7% below the OECD average of 88%. Thai youth aged 15-24 also have employment rates 12% below the OECD average.
These reflect difficulties in transition: graduates working outside their fields and lacking market-demanded skills and experience. Linking learner-curriculum-skill-job-income data to support Credit Bank, Micro-Credential, and Skill Bridge initiatives will help create a more career-connected education system.
2. Data on skills and occupational demands. Thailand faces a basic skills crisis: 65% of the population and youth have below-threshold abilities in basic literacy tasks, and 74% lack basic digital skills. Those with higher skills tend to earn significantly more.
Additionally, Thai workers face skill mismatches: high qualifications but skills not aligned with market professions such as production technology, business processes, communication, and STEM fields. Consequently, 34% of highly educated new workers hold low- or mid-skill jobs, twice the OECD average. Access to upskilling for Thai workers remains limited.
3. Household, regional data, and learner opportunities. Economic and geographic inequalities persist as major barriers. Students from the poorest households have higher dropout risks. Household debt exceeding 89% of GDP worsens educational access. Regionally, high school graduation rates in rural areas are 18% lower than urban areas. Bangkok leads with an 80% rate, while the North, South, and Northeast average 63-65%, correlating to high informal labor proportions in those regions.
Part 2: Using education data to guide learner pathways focuses on internal system data, especially about teachers and classrooms, to understand actual learning conditions in terms of quality, efficiency, and equity. This aligns with the development of the education database following OECD's INES framework to enable systematic international data comparisons.
This reflects the system’s effectiveness and readiness to support learners. Regarding classroom data, linking class size and student-teacher ratios shows that small classes and suitable ratios do not guarantee teaching quality. Therefore, designing school networks and teacher sharing models is necessary to reflect true resource utilization outcomes.
Part 3: Designing learner pathways in a human-centered AI society. Amid transition to an AI society and skills-based economy, pathway design must connect learner data, AI-guided counseling, and flexible pathway systems. This enables learners to make informed decisions with AI as a support tool.
Additionally, mechanisms supporting real data linkage, skill enhancement, experiential learning, and lifelong learning help reduce dropout rates and increase employment opportunities. The Skill Bridge Platform will be Thailand’s new educational infrastructure, shifting from producing graduates to developing competent, work-ready human capital, seamlessly linking learning with employment.
Part 4: Repositioning the essential learning framework for learners. Preparing learners for the future is not about adding new subjects, which would burden teachers and students, but reorganizing existing content to integrate real data, real problems, and real-world work. This is categorized into four key domains:
1. Reading and Information Learning: Developing skills in reading, comprehension, verification, and critical thinking so learners can use information judiciously in real-life decisions, addressing the country's basic skills crisis.
2. STEM and Innovation Learning: Integrating science, technology, engineering, and mathematics knowledge to foster mindsets that apply advanced technology and AI in problem-solving and value-creating innovation.
3. Language and Global Communication Learning: Enhancing language abilities as crucial tools for accessing global knowledge and connecting to the borderless modern workforce.
4. Social, Emotional and Ethical Learning: Focusing on human potential, ethics, and responsibility as guiding principles for safely and creatively using data, technology, and AI.
The reporter further noted that the seminar included a discussion titled "Learner Pathways to the Future World of Work" featuring education development experts exchanging views. Participants included Dr. Kesara Omrawutivor, Director of SEAMEO STEM-ED Center; Mr. Koji Miyamoto, Senior Economist at the World Bank; Mr. Danny Whitehead, Director of British Council Thailand; and Dr. Nipaporn Kulsomboon, Director of Organizational Development and Planning at Vajiravudh College, who also served as moderator.
The overall direction of education today is influenced by three key factors affecting the world of work, learning, and learners:
1. Repetitive routine jobs are disappearing. Fixed-rule, repetitive jobs are being fully replaced by AI systems. Thus, traditional learning focused on memorization or following orders is no longer sufficient.
2. Human value lies in thinking and interaction. Jobs requiring creativity, deep analysis, or interpersonal interaction remain highly valued and cannot be replaced by AI.
3. The emergence of new professions and working alongside AI as personal assistants will enhance work efficiency, alongside entirely new job types. The future work world will be full of changes. As the work environment evolves, learners must adapt by acquiring new skills and applying existing knowledge to handle unfamiliar situations, ensuring stable professional development and self-improvement.