Implementation of Artificial Intelligence in Educational Assessment and Its Implications for Learning Outcomes: A Scoping Review

This study aims to examine the implementation of AI in educational assessment and its effects on student learning outcomes, including the multidimensional impact of AI on cognitive and affective achievements, as well as a comparison between AI-based assessment and conventional methods. This study employs a scoping review design based on the PRISMA (Preferred Reporting Items for Systematic Reviews) protocol, using the PCC (Population, Concept, Context) approach as the framework for inclusion criteria. A literature search was conducted in four reputable databases Scopus, PubMed, EBSCOhost, and SpringerLink covering the years 2016–2026. Of the 275 articles identified, 13 met the inclusion criteria and were analyzed through data extraction and narrative synthesis. The use of artificial intelligence (AI) in educational assessment has a positive impact on conceptual understanding, higher-order thinking skills, assessment accuracy, and affective domains such as intrinsic motivation, emotional regulation, and engagement in learning.