데이터 맵핑 기반 실습형 한문법 교수학습 모형 연구― 〈出師表〉와 〈見乃梁破倭兵狀〉의 문장 네트워크를 중심으로

This study proposes a Data Mapping-based Practical Instructional Model for Classical Chinese grammar, designed to convert classical texts into machine-readable data. By integrating traditional humanities (grammar: mood, aspect, and word order), engineering (network simulation), and mathematics (weighting formulas), the model restructures linear texts into spatial nodes and edges. Analysis of Zhugeliang’s Chushibiao and Yi Sun-sin’s Gyeonnaeryang-pawaebyeongjang reveals that specific grammatical markers—namely mood and aspect—dictate discourse topologies, such as radial emotional clusters or linear causal chains. Utilizing the PPDAC cycle and U-C-A-V-I-F framework, the study systematizes a ‘Data Design Process’ that enables learners to actively design weights and manage physics-based simulations. Furthermore, a longitudinal analysis of the pedagogical paradigm shift over the past five years provides empirical evidence that this data-driven transition markedly improves learner interest and satisfaction. Ultimately, this model serves as a practical foundation for nurturing data sovereignty and critical literacy in the digital age.