College English Smart Classroom Learning Model Utilizing Data Mining Technology

Q2 Social Sciences
Xinning Zheng
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Abstract

The integration of Internet technology and the collaborative development of smart classrooms is an essential step for colleges and universities to advance English instruction reform. This study utilized data mining (DM) technology to analyze the learning process in college English smart classrooms. The results indicate that the DM algorithm used in this study outperforms the other two algorithms across all metrics. After conducting 15 experiments, the centrality of the DM algorithm in this study reached 0.58, exceeding the ant colony algorithm's centrality of 0.42. The decision tree algorithm exhibited the lowest centrality, reaching a maximum value of only 0.39. Consequently, the methodology utilized in this study demonstrates a significant centrality within the classroom, indicating its suitability for investigating University English smart classroom learning. Hence, implementing a University English smart classroom learning model utilizing DM technology represents the primary approach to achieving intelligent education.
利用数据挖掘技术的大学英语智慧课堂学习模式
融合互联网技术,协同发展智慧课堂,是高校推进英语教学改革的必要举措。本研究利用数据挖掘(DM)技术分析了大学英语智慧课堂的学习过程。结果表明,本研究采用的DM算法在所有指标上都优于其他两种算法。在进行了 15 次实验后,本研究中 DM 算法的中心度达到了 0.58,超过了蚁群算法的中心度 0.42。决策树算法的中心度最低,最大值仅为 0.39。因此,本研究采用的方法在课堂内表现出显著的中心性,表明其适合研究大学英语智慧课堂学习。因此,利用 DM 技术实施大学英语智慧课堂学习模式是实现智慧教育的主要途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.40
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0.00%
发文量
68
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