App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 6

LLm-driven generation of ideological and political materials for curriculum

He Feijuan1a,1b
Wang Xinping2
Xia Yue2
Ji Zhiguo1a,1b
Chen Haoran1a
1. a. School of Computer, b. Engineering Research Center of IoT Intelligent Sensing Interactive Platform, Universities of Shaanxi Province, Xi'an Jiaotong University City College, Xi'an Shaanxi 710018, China
2. School of Cyber Science and Engineering, Xi'an Jiaotong University, Xi'an Shaanxi 710049, China
DOI: 10.19734/j.issn.1001-3695.2025.09.0366

Abstract

Large Language Models (LLMs) demonstrate significant potential in curriculum Ideological and Political education, assisting teachers in rapidly generating ideological and political education cases integrated with value guidance. However, the challenge of aligning “knowledge points with ideological and political elements” limits their application. In response to this challenge, this paper proposed a “generator-evaluator” framework based on Cognitive Fluency (Cognitive Fluency-driven Ideological and Political Material Generation, CF-IPG) and constructed. an IPEC-GE dataset comprising 839 high-quality samples. The generator produces Ideological and Political Education cases following a structured chain: “case introduction (knowledge linkage ( ideological sublimation” guided by specific prompts. Two evaluators assess the two dimensions of cognitive fluency: logical consistency and semantic coherence. Through collaborative optimization, the generator and evaluators enhances the quality of generated content and resolves the alignment issue between “knowledge points and ideological and political elements. ” Experimental results show that CF-IPG method successfully generated ideological and political education cases for 100 knowledge points in Data Structure, achieving a human evaluation score of 0.9021. Through dual-dimensional evaluation of cognitive fluency and a collaborative training mechanism, it effectively achieves deep alignment between knowledge points and ideological and political education elements, providing an efficient and feasible technical way for the large-scale application of course-based ideological and political education.

Foundation Support

国家自然科学基金面上项目(62477037)
陕西省社会科学基金项目(2024P041)
陕西高校青年创新团队"多模态大数据挖掘与融合创新团队"

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.09.0366
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 6

Publish History

[2026-01-30] Accepted Paper

Cite This Article

何绯娟, 王鑫平, 夏悦, 等. 基于认知流畅性的课程思政素材生成方法 [J]. 计算机应用研究, 2026, 43 (6). (2026-02-25). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0366. (He Feijuan, Wang Xinping, Xia Yue, et al. LLm-driven generation of ideological and political materials for curriculum [J]. Application Research of Computers, 2026, 43 (6). (2026-02-25). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0366. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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