In this paper, we conduct an in-depth study and analysis of “Internet+ Business English” teaching through teaching big data model and visualization and elaborate on the change of educational objectives in the context of Internet education. From the perspective of individual value coordinates, the goal of education is to adhere to the people-oriented, personalized, and comprehensive free development of human beings; from the perspective of social value coordinates, the goal of education is to cultivate innovative talents for social innovation and development; through the multiple perspectives of the curriculum in the context of Internet education, we analyze the goal orientation and value reshaping of the curriculum in the context of educational change. The curriculum of the future will develop toward an intelligent curriculum and introduces the curriculum design and the form of curriculum organization in the context of Internet education. A comparison of the constructed regression and classification of a total of 27 data models reveals that the model constructed based on all data in the integrated education system is the most effective. The multiple linear regression model explained up to 66.5% of the variance in student academic performance; the explanatory power of the social and demographic characteristics dimension variables ranged from approximately 13% to 18%, the personal characteristics dimension variables ranged from 7% to 20%, and the student input dimension variables ranged from 10% to 17%. The highest correct prediction rate of the binary logistic regression model was 69%.

中文翻译：

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大数据模型与Internet +教学可视化的实证研究

本文通过大数据模型的教学和可视化，对“ Internet +商务英语”教学进行了深入的研究和分析，并详细阐述了网络教育背景下教育目标的变化。从个人价值坐标的角度出发，教育的目标是坚持以人为本，个性化，全面的人的自由发展。从社会价值坐标的角度出发，教育的目标是为社会创新和发展培养创新型人才。通过网络教育背景下课程的多种视角，我们分析了教育变革背景下课程的目标取向和价值重塑。未来的课程将向智能课程发展，并在互联网教育的背景下介绍课程设计和课程组织形式。通过对总共27个数据模型的构造回归和分类进行比较，发现基于综合教育系统中所有数据构造的模型是最有效的。多元线性回归模型最多可解释学生学习成绩差异的66.5％；社会和人口特征维度变量的解释力范围约为13％至18％，个人特征维度变量的解释力范围为7％至20％，学生投入维度变量的范围为10％至17％。二元逻辑回归模型的最高正确预测率是69％。