# The impact of cognitive schema on learning transfer ability and stability of classical Chinese poetry

**Authors:** Dawei Liu, Ping He, Huifen Yan

PMC · DOI: 10.1371/journal.pone.0336135 · PLOS One · 2025-11-06

## TL;DR

This study shows that using cognitive schema improves learning transfer and stability when studying classical Chinese poetry.

## Contribution

The novel contribution is demonstrating how cognitive schema enhances learning outcomes in classical Chinese poetry education.

## Key findings

- The experimental group using cognitive schema scored higher in tests.
- Cognitive schema improved transfer ability and stability in learning.
- Results showed significant differences between experimental and control groups.

## Abstract

Classical Chinese poetry is a condensed vessel of Chinese culture, bearing the core ethos of history, philosophy, and ethics. The symbolic imagery system in poetry facilitates the construction of cognitive schemata, thereby advancing transfer learning. Based on Schema Theory and Cognitive Structure Migration Theory, this research conducted a controlled experiment, with the participants being undergraduate students, to examine how “cognitive schema’‘ influences transfer ability and stability in learning classical Chinese poetry. The results revealed that the experimental group (n = 63) achieved higher scores in both tests, indicating that learners who employed the cognitive schema learning method demonstrated greater transfer ability and stability than the control group (n = 64). Significant differences in results between the experimental group and control group highlighted the positive impact of cognitive schema on learners’ transfer ability and stability in learning classical Chinese poetry. It is hoped that this research will provide valuable implications for the teaching and learning of classical Chinese poetry.

## Full-text entities

- **Diseases:** starvation (MESH:D013217), pains (MESH:D010146)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12591414/full.md

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12591414/full.md

## References

36 references — full list in the complete paper: https://tomesphere.com/paper/PMC12591414/full.md

---
Source: https://tomesphere.com/paper/PMC12591414