This study proposes an integrated theoretical framework to support deep learning in Chinese character instruction by synthesizing three major theoretical perspectives: the Cognitive Theory of Multimedia Learning (CTML), Bloom’s Taxonomy, and Cognitive Semantics. While Chinese character learning presents significant challenges due to its complex visual forms and semantic depth, multimedia technology offers promising but underutilized potential to support meaningful learning. Drawing on critical analysis of prior empirical and theoretical studies, the framework aligns CTML’s design principles with Bloom’s hierarchical cognitive objectives and the meaning construction mechanisms of Cognitive Semantics. The result is a comprehensive conceptual model designed to guide the development of multimedia-assisted modules that foster deep learning. This framework offers theoretical contributions to language learning and practical implications for instructional design, particularly in ideographic languages. Future empirical validation of this framework is recommended.
- Open Access
- Article
An Integrated Theoretical Framework for Deep Learning in Chinese Characters: Insights from Multimedia, Taxonomy, and Cognitive Semantics
- Yu-Lu Jin 1,
- Bao-Wen Shao 1,2,
- Nik Muhammad Hanis Bin Nek Rakami 1,*,
- Md. Nasir Masran 1,
- Qun-Fang Zeng 3
Author Information
Received: 31 Oct 2025 | Revised: 28 Feb 2026 | Accepted: 10 Apr 2026 | Published: 30 Jun 2026
Abstract
Keywords
deep learning | Chinese characters | cognitive theory of multimedia learning | bloom’s taxonomy | cognitive semantics
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