我国教师网络培训质量影响因素的元分析

A Meta-Analysis of the Factors Affecting the Quality of Teacher Online Training in China

网络培训现已被广泛应用于我国教师培训中,但质量却并未完全达到预期。目前,已有较多研究关注到培训质量的影响因素,但研究结果并不一致。在采用元分析的方法对已有21项研究进行综合量化分析后发现:从整体上看,网络培训具有普适的工具性价值,其质量不受学员背景信息影响;网络培训暂未发挥出信息技术的最佳优势。从培训方式上看,在集中培训时,学员的个人因素是实现网络培训质量增量的因素;在自主学习时,培训的固定设计是保障网络培训基本质量的因素;而混合培训受到集中培训与自主学习的双重影响。从调查地区看,东部地区教师需要交流互促,西部地区教师需要情感支持与专业引领,中部地区教师需要课程资源供给。基于此,对我国今后的教师网络培训提出三方面建议:着眼于信息技术优势的充分发挥,推动培训功能的结构性优化;整合保障型因素与增量型因素,推进网络培训的“参与式革命”;基于不同地域的差异性特征,推行网络培训模式的供给侧改革。

Online Training has been widely used in teacher training in China.But the quality of the training was not as good as expected.At present,there are many researches about the influencing factors of teacher online training quality in China.But the research results are complicated and inconsistent.The paper applies meta-analysis method to analyze 21 quantitative literatures on the factors affecting online training of teachers.It is found that network training has universal instrumental value,and its quality is not affected by the background information of the students.From the different training methods,the individual factor of the students in centralized training is the factor of realizing the increment of network training quality,while and the fixed design of training in independent learning is the factor of guaranteeing the basic quality of network training.Mixed training is influenced by both of the above training methods.From the survey area,teachers in the eastern region need mutual promotion;teachers in the western region need emotional support and professional guidance;and teachers in the central region need the supply of curriculum resources.After analysis,this study puts forward the following suggestions:Focusing on giving full play to the advantages of information technology and promoting the structural optimization of training functions;integrating the supporting factors and the incremental factors to promote the“participatory revolution”of online training;implementing the supply-side reform of online training mode based on the different characteristics.