创新创业理论研究与实践 ›› 2025, Vol. 8 ›› Issue (23): 7-10.

• 理论研究 • 上一篇    下一篇

混合式教学模式下教师精准教学能力评价指标体系探究

闫观渭   

  1. 九江学院 经济学院,江西九江 332005
  • 出版日期:2025-12-10 发布日期:2026-05-14
  • 作者简介:闫观渭(1982—),男,陕西渭南人,博士研究生,讲师,研究方向:经济学教学与研究。
  • 基金资助:
    江西省教育科学“十四五”规划2023年度课题“混合式教学模式下教师精准教学能力体系构建与提升路径研究”(23YB235)

Exploration of the Evaluation Index System for Teachers' Precise Teaching Ability in Blended Learning Mode

YAN Guanwei   

  1. Economics School of Jiujiang University, Jiujiang Jiangxi, 332005, China
  • Online:2025-12-10 Published:2026-05-14

摘要: 该文基于精准教学理论与混合式教学特点,旨在构建一套逻辑严谨、适配性强的教师精准教学能力评价指标体系,为教师专业发展与教学实践提供理论指引。该文以精准教学能力相关模型为基础,结合混合式教学“双线协同”特征,通过文献梳理、理论推演及专家访谈完成指标体系构建,形成包含5个一级指标、18个二级指标的评价体系,体系突出混合式教学中线上线下数据整合、资源适配等核心要求,体现“认知—数据—技术—画像—干预”的能力逻辑链。研究结果表明:该指标体系可为混合式教学场景下教师精准教学能力的培养与评价提供系统性框架,丰富精准教学能力理论的场景化应用研究。

关键词: 混合式教学, 精准教学能力, “双线协同”干预, 智能技术融合, 学情数据整合, 指标体系

Abstract: This article is based on the theory of precision teaching and the characteristics of blended learning, aiming to construct a logically rigorous and adaptable evaluation index system for teachers'precision teaching ability, providing theoretical guidance for teachers'professional development and teaching practice. This article is based on the precision teaching ability related model, combined with the“dual line collaboration”characteristics of blended learning. Through literature review, theoretical deduction, and expert interviews, the indicator system is constructed, forming an evaluation system consisting of 5 primary indicators and 18 secondary indicators. The system highlights the core requirements of online and offline data integration and resource adaptation in blended learning, reflecting the ability logic chain of“cognition data technology portrait intervention”. The research results indicates that this indicator system can provide a systematic framework for the cultivation and evaluation of teachers'precision teaching ability in blended learning scenarios, enriching the scenario based application research of precision teaching ability theory.

Key words: Blended learning, Precision teaching ability, “Dual line collaboration”intervention, Integration of intelligent technology, Integration of academic data, Indicator system

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