Abstract

Educational evaluation plays a strategic role in strengthening public accountability and enhancing institutional interrelationships amidst the acceleration of digital transformation. This study addresses the urgent need to explore how various evaluation models can effectively interact with technology and educational governance to create an adaptive, transparent, and sustainable quality assurance system. This research aims to synthesize dominant and relevant educational evaluation models across contexts and uncover the effectiveness of their implementation in the digital era. Using the Systematic Literature Review (SLR) method guided by PRISMA 2020, this study went through four main stages: identification, screening, eligibility, and inclusion. A total of 22 articles from Scopus and Web of Science for the 2022-2025 period were analyzed thematically. The findings revealed four prominent evaluation models: CIPP, Artificial Intelligence-Based (AI-Based) evaluation, participatory evaluation, and evidence-based evaluation. These four models emphasize a paradigm shift in evaluation systems toward data-driven, collaborative, and technology-integrated ones. Practically, this study confirms that the successful integration of evaluation models and digital technology is highly dependent on governance readiness, human resource capacity, and data-driven decision-making mechanisms. These implications form an important basis for educational institutions to strengthen evaluation systems that are responsive to change and oriented towards increasing sustainability.

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