From Examination Culture to Competency Assessment: Educational Evaluation in the Age of Artificial Intelligence
Keywords:
Examination Culture, Competency-Based Assessment, Artificial Intelligence, Educational Evaluation, Learning Analytics, Resource-Constrained CountriesAbstract
This paper examines the transition from examination-centered evaluation systems to competency-based assessment in the age of artificial intelligence (AI). Traditional examination culture, which emphasizes memorization and high-stakes testing, is increasingly inadequate for measuring the complex skills required in contemporary knowledge societies. Drawing on existing literature, the study analyzes the limitations of examination-based assessment and explores how competency-based approaches better capture learners’ ability to apply knowledge in authentic contexts. The paper further investigates the transformative role of AI in educational evaluation, highlighting its potential to support adaptive assessment, real-time feedback, and data-driven decision-making. A conceptual framework, the AI-Enabled Competency Evaluation Model (AICE Model), is proposed to integrate competency domains, authentic tasks, AI-supported tools, continuous feedback, and reflective learning processes. Particular attention is given to implementation in resource-constrained countries, where challenges such as limited infrastructure, digital inequality, and teacher readiness must be addressed through phased and context-sensitive strategies. The study concludes that the shift toward competency-based, AI-supported evaluation represents a fundamental reorientation of education toward developing transferable, future-oriented skills.
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