数据驱动的高职课堂教学反馈机制构建研究

摘要

随着教育数字化战略深入推进，数据要素逐渐成为推动课堂教学改革的重要支撑。传统高职课堂教学反馈主要依赖教师经验判断、课堂观察以及结果性评价，存在反馈滞后、过程感知不足和个性化支持能力有限等问题。学习分析技术的发展为基于学习过程数据优化教学反馈提供了新的可能。本文基于学习分析理论、形成性评价理论和精准教学理论，分析数据驱动教学反馈的内涵及其作用机制，构建“数据感知—学习分析—反馈干预—教学优化”的高职课堂教学反馈机制模型，并结合高职编程类课程实践特点，提出数据驱动教学反馈机制的实施路径。研究认为，数据驱动教学反馈能够突破传统教学评价的结果导向限制，实现对学生学习过程的动态感知和精准支持，促进教师教学决策由经验驱动向数据赋能转变，为高职课堂数字化转型提供理论参考和实践路径。

Abstract

With the continuous advancement of educational digitalization, data has become an important driving force for classroom teaching reform. Traditional teaching feedback in higher vocational education mainly relies on teachers’ experience, classroom observation and summative evaluation, which often suffers from delayed feedback, insufficient perception of learning processes and limited personalized support. The development of learning analytics provides new opportunities for improving teaching feedback based on learning process data. Based on learning analytics theory, formative assessment theory and precision teaching theory, this paper analyzes the connotation and mechanism of data-driven teaching feedback, constructs a theoretical model consisting of four stages: data perception, learning analysis, feedback intervention and teaching optimization. Furthermore, considering the characteristics of higher vocational programming courses, this paper proposes practical implementation paths for data-driven teaching feedback mechanisms. The study argues that data-driven feedback can transform traditional evaluation from outcome-oriented assessment to process-oriented support, enhance teachers’ decision-making capabilities, and promote the digital transformation of higher vocational classroom teaching.

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