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Portrait-Based Academic Performance Evaluation of College Students from the Perspective of Big Data

机译:大型数据视角下基于肖像的学术绩效评估

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With the advent of the big data era, significant changes have taken place in every aspect of education. To effectively evaluate the academic performance of college students, this paper firstly establishes a scientific evaluation index system for student portrait. Taking the course Object-Oriented Programming as an example, the authors collected various data on the academic performance of college students. The collected data were normalized, and the weight of each evaluation index was determined through analytic hierarchy process (AHP). Next, a fuzzy evaluation model was constructed based on big data, and used to assess each dimension of college students’ academic performance. The evaluation reveals the problems of college students in learning and practice, and helps to generate the portrait of each student. The research results promote the realization of personalized education.
机译:随着大数据的出现,教育的各个方面都发生了重大变化。 为了有效评估大学生的学术表现,本文首先为学生肖像建立了一个科学评价指标体系。 以面向对象的编程为例,提交人员收集了大学生的学术表现的各种数据。 收集的数据被标准化,通过分析层次处理(AHP)确定每个评估指标的重量。 接下来,基于大数据构建模糊评估模型,用来评估大学生学术表现的每维度。 评估揭示了大学生在学习和实践中的问题,并有助于生成每个学生的肖像。 研究成果促进了个性化教育的实现。

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