学生表现与困难预测

Kumuda Kanatti, Kehkashaan Khanum A, Janani Jayashankar, G. P, Ambeshwar Kumar
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引用次数: 0

摘要

世界上每个政府和国家都努力在教育领域取得进步,因为教育是社会的关键要素。根据研究,学生的成绩在“灵光”——一种传染病在2020年瓦解了生活之后有所下降,这强调了更严肃对待这一问题的必要性,并寻求找出原因和有效的治疗方法。教育系统受到了多方面的影响。通过分析和评估学者的学业表现,同时考虑到各个方面,该设计旨在改善学术,专业和大学的指导。本次设计将使用问卷对学者进行调查,并使用UCI机器学习存储库中的数据。通过使用丰富多彩的机器学习算法来剖析学生数据和问题,了解影响学者表现的丰富多彩的方面,并预测学者的成功。学生特征的三种不同顺序包括特殊特征、学术属性和行为特征。小学生的读写成绩是通过他们的行为特征来反映的。已经注意到回归模型和分类模型经常用于预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Student’s Performance and Difficulties Prediction
Every government and nation in the world strives to make advancements in the area of education because it’s a pivotal element of society. According to studies, pupil performance has declined after the nimbus- contagion epidemic that disintegrated life in 2020, which emphasizes the need to treat this prob-lem more seriously and seek to pinpoint both the causes and the effective treatments. The educational system has been impacted in numerous ways. By assay-ing and assessing scholars’ academic performance while taking a variety of aspects into the account, the design aims to ameliorate academic, professional, and university guidance. Scholars will be surveyed using a questionnaire for this design, and data from the UCI Machine Learning Repository will also be used. Understanding the colorful aspects that affect scholars’ performance and prognosticating scholars’ success through the use of colorful machine learning algorithms to dissect pupil data and one’s issues The three different orders of pupil characteristics include particular traits, academic attributes, and behavioral traits. The pupils’ literacy achievements are told by their behavioral traits. It has been noted that regression and Classification models are con-stantly used in prediction.
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