This scoping review critically examines the application of alignment optimization in international large-scale assessments (ILSAs) to address measurement invariance challenges, a fundamental issue for ensuring valid cross-national comparisons in educational research. By systematically analyzing 18 empirical studies across prominent ILSAs—including PISA, TALIS, TIMSS, and ICCS—this review synthesizes evidence on the effectiveness of alignment optimization in enhancing cross-national comparability across diverse cultural and linguistic contexts. While alignment optimization demonstrates promise in achieving approximate measurement invariance, findings reveal significant variability in its performance, particularly for constructs influenced by cultural and linguistic diversity. The review identifies key limitations, such as high non-invariance rates for culturally sensitive constructs and inconsistencies in reporting standards, which hinder the method's reliability and generalizability.
The study contributes to the theoretical and methodological discourse on educational measurement by proposing targeted recommendations for advancing alignment optimization, including the integration of hybrid approaches, improved reporting protocols, and the exploration of underrepresented cultural contexts. These insights are critical for refining the robustness of cross-national comparisons in ILSAs, ultimately supporting more equitable and reliable educational assessments globally. By addressing these challenges, this review lays the groundwork for future research to enhance the validity and applicability of alignment optimization in international educational research, offering significant implications for policy and practice.