A Framework to Analyze Performance of Student's in Programming Language Using Educational Data Mining

V. Hegde, Sushma Rao H S
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引用次数: 4

Abstract

In the current era, the knowledge of programming language provides a greater fortune in the career of students'. This paper is on students' centric approach for analyzing their performance, improvisation in the programming language such as in C, C++, and Java. For the fetching knowledge extraction from the educational field, Educational Data Mining is used. Hence, the study helps in empowering grit level in students' to enrich themselves towards success based on their performance. The general survey, technical concepts based test, logical and reasoning based test is collected using Google forms. The model is framed based on the survey and test data set to know the slow learner student's in academic. The proposed model identifies the student's based on analyzing them better, than only considering internal marks and assessment conducted. The framework provides greater efficiency in identifying the right students' for analysis and validated based on entropy value. The model is beneficial to the students' to improvise their weaker concept with frequent faculty assistance and also provide greater advantage to the university
基于教育数据挖掘的学生程序设计语言性能分析框架
在当今时代,编程语言的知识为学生的职业生涯提供了更大的财富。本文以学生为中心,分析他们在C、c++和Java等编程语言中的表现和即兴发挥。对于教育领域的知识提取,采用教育数据挖掘技术。因此,该研究有助于增强学生的毅力水平,从而根据他们的表现丰富自己走向成功。总体调查,基于技术概念的测试,基于逻辑和推理的测试是使用谷歌表格收集的。该模型是在调查和测试数据集的基础上建立起来的,以了解学习缓慢的学生在学业上的表现。该模型通过对学生的分析来更好地识别学生,而不是仅仅考虑内部分数和所进行的评估。该框架在确定合适的学生进行分析和基于熵值验证方面提供了更高的效率。这种模式有利于学生在教师的频繁帮助下即兴发挥自己薄弱的概念,也为学校提供了更大的优势
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