大模型如何融入教育的质性研究:理论潜力与案例实践

HowdoLarge Language Models FitintoQualitative Researchin Education: Theoretical Potential and Case Practice

当前,面对教育质性研究中日益增多的非结构化数据,传统的手动编码和解释方法已难以有效应对,而大模型(Large Language Model,LLM)的快速发展为社会科学的质性研究带来了新的机遇与挑战。为此,文章聚焦LLM在教育质性研究中的应用,首先从理论层面阐释了LLM的潜力,包括其在心理理论应用、非结构化数据分析、背景知识利用以及数据增强技术介入等方面的优势;然后,文章提出了LLM在教育质性研究不同阶段的应用框架,涵盖研究设计与预备分析,数据收集与信息交互,数据分析与模式识别,成果展示、验证与传播等环节;最后,文章通过一个基于GPT-4的智能访谈案例,展示了LLM优化教育质性研究设计、改进数据收集与分析方法的过程。文章通过研究,旨在为LLM在教育质性研究中的应用提供理论框架,并为未来教育质性研究方法的实践创新提供思路。

At present,in the face of the increasing number of unstructured data in the qualitative research of education,the traditional manual coding and interpretation methods have been difficult to effectively cope with,and the rapid development of Large Language Model(LLM)has brought new opportunities and challenges to the qualitative research of social science.Therefore,focusing on the application of LLM in qualitative research in education,this paper firstly explained the potential of LLM from theoretical perspective,including its advantages in the application of psychological theory,unstructured data analysis,background knowledge utilization,and data augmentation technology.Second,this paper proposed an application framework for LLM at different stages of qualitative research in education,covering research design and preliminary analysis,data collection and information interaction,data analysis and pattern recognition,and output presentation,validation and dissemination.Finally,through an intelligent interview case based on GPT-4,the paper demonstrated the process of LLM optimizing educational qualitative research design and improving data collection and analysis methods.This paper aimed to provide a theoretical framework for the application of LLM in the qualitative research of education and provide ideas for the practical innovation of the qualitative research methods of education in future.