Work

Kanji-based lexical knowledge as a predictor of Japanese text comprehension in Chinese JFL learners: A structural equation modeling (SEM) approach

Year: 2026

Type: article

Abstract: Chinese learners of Japanese as a foreign language (JFL) are often assumed to benefit from first-language kanji knowledge when reading Japanese, but this contribution has seldom been tested within an explicit causal framework. Here, we examine how kanji-based lexical knowledge supports Japanese text comprehension in Chinese JFL learners. Two-kanji words were categorized into three types based on orthographic and semantic similarity between Chinese and Japanese (i.e., Identical, Partially Overlapping, and Unrelated) and confirmatory factor analysis showed that all three types significantly loaded onto a single latent construct of kanji word knowledge. Structural equation modeling (SEM) further revealed that kanji word knowledge strongly predicts text comprehension, both indirectly through its facilitative effect on general lexical knowledge and directly as an independent contributor. These findings extend previous research by demonstrating, within a unified causal model, the central and robust role of kanji-based lexical knowledge in Japanese text comprehension among Chinese JFL learners.

Source: Acta Psychologica

DOI: 10.1016/j.actpsy.2026.107460

Authors: Mengxia Chen, Katsuo Tamaoka

Institutions: Ningbo University, Shanghai University, Nagoya University

Language: English

Topic: Second Language Acquisition and Learning

Subfield: Developmental and Educational Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,670