Policy Learning and Adaptation: Lessons from PISA for Educational Reform Worldwide
This paper examines how insights from the Program for International Student Assessment (PISA) have shaped educational reforms across diverse countries, underscoring both achievements and persistent challenges. Through a comparative analysis of reforms in high-performing nations like Finland and Singapore, as well as emerging economies such as Thailand, Vietnam, and Brazil, the study investigates the adaptation of educational policies to different national contexts. Key reform areas include curriculum innovation, teacher training enhancement, and policies designed to foster equity in access to quality education, with particular focus on science, technology, engineering, and mathematics (STEM) disciplines. Each country's distinct sociocultural, economic, and institutional landscapes reflect notable variations in the prioritization and operationalization of these reforms, as highlighted by the findings. The study identifies several critical barriers to effective policy transfer, such as cultural divergences, economic inequality, and differences in governance structures that impact the scalability of reforms. Furthermore, the study underscores the significance of employing context-sensitive methods to adjust policies and promote reforms that are not only in line with global standards but also tailored to local requirements and capabilities. Stakeholder involvement, particularly from educators, policymakers, and community members, emerges as essential in refining and sustaining reform efforts. This research underscores the dual role of PISA: while it provides a valuable framework for measuring educational success, it also requires adaptation and contextual awareness to inform meaningful and sustainable improvements. Ultimately, a flexible, inclusive approach to policy reform is critical for advancing educational quality and equity on a global scale.
Institutions
- Thaksin University (TH)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-11-14
- DOI
- https://doi.org/10.5281/zenodo.14179522
- Primary Topic
- Advanced Statistical Methods and Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00