Study on Evaluation Model of International Chinese Teachers’ Digital Competence in Online Teaching Based on K-Means Clustering Algorithm

Liqing Yang, Qicheng Wang, Tianyu Wang, Xintong Ma
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Abstract

The research aim of this paper is to evaluate the digital competence of international Chinese teachers.In order to accurately and objectively evaluate the international Chinese teachers’ digital competence standards, we used methods of data mining.The research procedure included the establishment of indicators of teachers’ digital competence and the construction of models.We chose the European Teachers’ Digital Competence Framework which includes 22 research indicators as the index dimension and used a developed convolutional neural network, k clustering and the fuzzy clustering algorithm. We created an evaluation model as a result. The results of several tests show that the model is stable and plausible. The model can be used to analyze the trend and distribution of digital ability among international Chinese teachers, as well as to evaluate international Chinese teachers’ s digital ability. The innovation of the result is the creation of a theoretical evaluation model to evaluate teachers’ digital ability.
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基于k均值聚类算法的国际汉语教师在线教学数字能力评价模型研究
本文的研究目的是评估国际汉语教师的数字能力。为了准确客观地评价国际汉语教师的数字能力标准,我们采用了数据挖掘的方法。研究过程包括教师数字能力指标的建立和模型的构建。我们选择了包含22个研究指标的欧洲教师数字能力框架作为指标维度,并使用了发达的卷积神经网络、k聚类和模糊聚类算法。因此,我们创建了一个评估模型。多次试验结果表明,该模型是稳定的、合理的。该模型可用于分析国际汉语教师数字能力的趋势和分布,并对国际汉语教师的数字能力进行评价。结果的创新是建立了评价教师数字化能力的理论评价模型。
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