A multi-criteria assessment of Japanese Kanji learning difficulty for educational prioritization using ANP-VIKOR

Japanese Kanji acquisition remains a major challenge for non-native learners because character learning involves multiple cognitive and linguistic factors, including visual complexity, semantic transparency, usage frequency, and pronunciation variability. Although previous studies have examined individual aspects of Kanji difficulty, few have integrated these factors within a transparent multi-criteria decision-making framework.

This study proposes a hybrid Analytic Network Process (ANP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) framework to evaluate the difficulty of learning Kanji. Four evaluation criteria, namely stroke count, frequency of use, semantic transparency, and phonetic variability, were identified through a literature review and validated by an expert panel. ANP was used to determine the relative importance of the criteria, while VIKOR generated compromise rankings for representative high-frequency Kanji characters. Learner ratings from 50 non-native Japanese learners and expert evaluations were incorporated into the decision-making process.

The ANP analysis identified stroke count as the most influential criterion (0.30), followed by frequency of use (0.25), semantic transparency (0.25), and phonetic variability (0.20). The VIKOR analysis ranked as the least difficult Kanji and as the most difficult among the evaluated characters. Sensitivity analysis demonstrated stable rankings under different decision-making scenarios, indicating the methodological robustness of the proposed framework.

The proposed ANP-VIKOR framework provides a transparent and systematic approach for evaluating Kanji learning difficulty by integrating expert knowledge, learner perceptions, and multiple linguistic criteria. The resulting rankings provide a transparent methodological framework for Kanji prioritization and educational planning. The proposed framework serves as a decision-support tool and provides a foundation for future classroom-based validation and educational research.