计算机科学与探索2026，Vol.20Issue(4)：1006-1018,13.DOI:10.3778/j.issn.1673-9418.2508002
基于大语言模型提示调优的教育文本分类方法
Research on Education Text Classification Based on Prompts Learning and Large Language Models
摘要
Abstract
Educational text classification is a core task in intelligent education,with wide applications in textbook content analysis,automatic exam-question categorization,and educational-resource recommendation.Compared with general texts such as news or reviews,educational texts are characterized by dense terminology and rich structured knowledge,which substantially increase the difficulty of semantic understanding and transfer learning.Under low-resource and small-sample conditions,mainstream approaches that rely on large-scale annotated data and supervised fine-tuning suffer from severe data scarcity.This paper proposes a text-classification method tailored for low-resource and small-sample scenarios,based on a prompt-tuning strategy that facilitates the transfer of prior knowledge from pre-trained language models(PLMs)and large language models(LLMs).This paper designs three types of prompt templates:discrete,continuous,and hybrid.It incorporates a bidirectional long short-term memory network(BiLSTM)to model dependencies among prompt tokens,thereby improving the model's task-specific semantic adaptation.Experiments on four representative benchmarks(EduBooks,AGNews,MELD,and IMDB)show that the proposed method outperforms eight strong baselines on Fl by 3.7％,3.3％,5.7％,and 1.1％,respectively.The results indicate that the proposed approach can efficiently and accurately classify diverse text types with strong generalizability,without fine-tuning the parameters of the pre-trained models.Abla-tion studies further validate the effectiveness of the parameter-freezing strategy.关键词
大语言模型/文本分类/提示学习Key words
large language models/text classification/prompt learning分类
信息技术与安全科学引用本文复制引用
戎璐,喻梅,赵东明,王永刚,张亚洲..基于大语言模型提示调优的教育文本分类方法[J].计算机科学与探索,2026,20(4):1006-1018,13.基金项目
国家自然科学基金青年基金(62006212) （62006212）
河南省自然科学基金面上项目(242300421412) （242300421412）
2024年天津市制造业高质量发展项目(24ZGZNGX00020).This work was supported by the Youth Program of the National Natural Science Foundation of China(62006212),the General Program of the Natural Science Foundation of Henan Province(242300421412),and the Tianjin's Manufacturing Industry High-Quality Development Project in 2024(24ZGZNGX00020). （24ZGZNGX00020）
