中国电化教育

该研究聚焦于智能精准教研(IPTR)范式的理论构建与实践探索,基于2021—2024年覆盖全国28个省108个区县和276所学校的大规模试点实践,系统阐述了智能精准教研的理论框架,将其定位为一种以数据循证为基础、人机协同为核心机制、精准赋能教师个性化与规模化专业发展为价值旨归的教研新形态;揭示了智能精准教研的五大特征:数据化、智能化、精准化、个性化和规模化,并分析了教研主体、证据、情境、模式和生态等核心要素的转型;技术层面,构建了多模态数据采集与分析的技术基座,包括课堂教学行为数据、教学质量评价数据和课堂话语文本数据;实践层面,提炼了系统化的教学诊断方法、动态发展的教师画像体系及创新的教研活动模式;生态层面,提出了包含政府、教研机构、企业、高校和学校的GEBUS多元协同生态系统模型,并探讨了教研文化重塑的必要性。研究为促进教师专业发展和区域教研创新提供了理论指导与实践路径。

This study focuses on the theoretical construction and practical exploration of the Intelligent Precision Teaching Research(IPTR)paradigm, based on large-scale pilot practices covering 108 districts and counties and 276 schools across 28 provinces in China from 2021-2024. The paper systematically explains the theoretical framework of IPTR, positioning it as a new form of teaching research based on “evidence-based data”, human-machine collaboration as a core mechanism, and precision empowerment of teachers' personalized and scalable professional development as its value aim. The research reveals five major characteristics of IPTR: data-based, intelligent, precise, personalized, and scalable,and analyzes the transformation of core elements including stakeholders in educational, evidence, contexts, models, and ecosystems. At the technical level, a foundation for multimodal data collection and analysis has been constructed, including classroom teaching behavior data, teaching quality evaluation data, and classroom discourse text data. At the practical level, the study has refined a systematic teaching diagnostic method, a dynamic teacher portrait system, and innovative research activity models. At the ecosystem level, the research proposes a GEBUS multi-stakeholder collaborative ecosystem model encompassing government, educational research institutions, businesses, universities, and schools, and discusses the necessity of reshaping the research culture. The study provides theoretical guidance and practical pathways for promoting teacher professional development and regional educational research innovation.