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<p>Deep learning is an important learning method for smart classroom. Building a scientific teaching evaluation index system of smart classroom is of great significance in promoting students' deep learning. Currently, research in related fields mainly includes pattern design, interaction framework design, and analysis of influencing factors, which are relatively little research on evaluation index systems. The grounded theory method was used to preliminarily construct an evaluation index system, which combined Delphi expert consultation, analytic hierarchy process (AHP) weight assignment, and exploration and confirmatory factors to revise and validate it. An evaluation index system (4 primary indicators, 13 secondary indicators, and 34 tertiary indicators) was constructed, which included the level of intelligent talents, intelligent learning environment, intelligent learning activities, and intelligent evaluation feedback. The results offer potential methodological guidance for teachers to build high-quality smart classrooms and promote students' deep learning, pending further empirical validation.</p>

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Construction and Empirical of Smart Classroom Teaching Evaluation Index System to Promote Deep Learning in Primary and Secondary Schools

  • 期刊论文

  • 发表日期：

    2025年9月25日

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  • Xundiao Ma,
  • Hanxi Wang

摘要

Deep learning is an important learning method for smart classroom. Building a scientific teaching evaluation index system of smart classroom is of great significance in promoting students' deep learning. Currently, research in related fields mainly includes pattern design, interaction framework design, and analysis of influencing factors, which are relatively little research on evaluation index systems. The grounded theory method was used to preliminarily construct an evaluation index system, which combined Delphi expert consultation, analytic hierarchy process (AHP) weight assignment, and exploration and confirmatory factors to revise and validate it. An evaluation index system (4 primary indicators, 13 secondary indicators, and 34 tertiary indicators) was constructed, which included the level of intelligent talents, intelligent learning environment, intelligent learning activities, and intelligent evaluation feedback. The results offer potential methodological guidance for teachers to build high-quality smart classrooms and promote students' deep learning, pending further empirical validation.