Evaluating the Key Success Factors of “Merdeka” Curriculum: Evidence from East Nusa Tenggara, Indonesia

Abstract

21st-century Education demands an adaptive system to prepare graduates for dynamic global changes. The “Merdeka” Curriculum in Indonesia is designed to meet these demands through learning based on the Pancasila Student Profile. Thus, this research aims to evaluate the key success factors of the implementation of “Merdeka” Curriculum at the Senior High School (SMA) level by using the CIPP (Context, Input, Process, Product) evaluation model combined with Structural Equation Modeling-Partial Least Squares (SEM-PLS). Data were collected through a survey of 110 respondents, including driving school facilitators, supervisors, principals, and teachers in Manggarai Regency, East Nusa Tenggara, Indonesia. The data analysis covers four dimensions of CIPP with 52 indicators. The study revealed that Context significantly influences Input (path coefficient 0.809) and that Input directly affects Process (path coefficient 0.648). However, the direct influence of Input on the Product is not significant (path coefficient 0.019), while Process is the primary mediator that connects Input and Product with significant influence (path coefficient 0.672). This research highlights the importance of Process as a key factor in implementing the “Merdeka” Curriculum. Policy support and initial readiness (Context) significantly contribute to resources (Inputs), but the success of implementation depends on the effectiveness of the implementation process in the field. In addition, the validity and reliability of the evaluation model showed adequate results, with modifications that improved the quality of measurements on each component. This research provides a theoretical contribution to the quality of “Merdeka” Curriculum implementation in Indonesia. Recommendations include strengthening teacher capacity through continuous training, improving infrastructure, and intensifying the monitoring of the learning process. The study also allows further exploration through a mixed-methods approach in regions with different contexts to generalize findings.