教育研究的硅基样本——基于大模型技术路线的分析  

Silicon-Based Samples in Educational Research: Technological Approaches Based on LargeLanguage Models

作　　者：刘泽民 陈向东[1] Liu Zemin;Chen Xiangdong(Department of Educational Information Technology,East China Normal University,Shanghai 200062)

机构地区：[1]华东师范大学教育信息技术学系,上海200062

出　　处：《远程教育杂志》2025年第1期19-32,45,共15页Journal of Distance Education

基　　金：2023年全国教育科学规划一般课题“基于大语言模型的青少年人工智能教育研究”(项目编号:BCA230276);中央高校基本科研业务费专项资金资助项目(项目编号:YBNLTS2024-030)的阶段性研究成果。

摘　　要：大模型技术的蓬勃兴起,为教育研究方法论带来了前所未有的革新契机。基于此背景,研究聚焦于大模型驱动的硅基样本在教育研究领域的应用,对其理论基础、实现路径以及潜在影响展开了系统且深入的探究。研究伊始,深入剖析了大模型通过世界知识的广泛习得、认知能力的自然涌现以及心理理论能力的精准模拟,为硅基样本提供坚实理论支撑的内在机制。在此基础上,研究进一步提炼虚拟抽样、数字孪生和社会模拟这三种实现教育硅基样本的关键技术路线,为其在教育研究中的实际应用提供了切实可行的操作指南。为切实验证硅基样本在教育研究中的可行性,研究设计了一项探索性案例,模拟针对不同职业背景和技术熟练度的教育工作者开展的虚拟访谈。通过对案例的细致分析,研究初步证实了硅基样本在教育研究中的可行性,以及其在捕捉教育群体异质性方面的有效性。研究还进一步探讨了硅基样本对教育研究知识生产模式所引发的深刻变革。同时,研究也客观地指出了在应用过程中可能遭遇的方法论风险,如确认偏误、模型坍缩以及生态效度等方面的挑战。展望未来,教育研究或将呈现出“赛博格化”的发展趋势,在人机协同的全新模式下开拓崭新的探索空间,不断重塑教育研究的范式与边界,可为教育领域的理论与实践发展注入新的活力。The rapid development of large language models(LLMs)has created unprecedented opportunities for innovation in educational research methodologies.This study examines the application of LLM-driven silicon-based samples in educational research,offering a comprehensive exploration of their theoretical foundations,implementation strategies,and potential impacts.The research begins by analyzing the theoretical mechanisms that support silicon-based samples,focusing on the broad acquisition of world knowledge by LLMs,the natural emergence of cognitive abilities,and the simulation of theory of mind capabilities.Building on these foundations,the study identifies three key technological approaches for implementing silicon-based samples in educational research,including virtual sampling,digital twinning,and social simulation,and provides practical frameworks for their application.To assess the feasibility of silicon-based samples,an exploratory case study was designed,simulating virtual interviews with educators from diverse professional backgrounds and varying levels of technological proficiency.The case study preliminarily confirms the feasibility of silicon-based samples in educational research and demonstrates their effectiveness in capturing the heterogeneity of educational groups.The study also explores the profound impact silicon-based samples have on knowledge production models in educational research,while addressing potential methodological risks,such as confirmation bias,model collapse,and challenges related to ecological validity.Looking to the future,educational research may undergo a“cyborgization”process,unlocking new avenues for exploration through human-machine collaboration and reshaping the paradigms and boundaries of educational research.

关 键 词：硅基样本 大模型智能体 虚拟抽样 数字孪生 社会模拟 教育研究方法 

分 类 号：G40-03[文化科学—教育学原理]