Analysis of the Influence of Some External Factors on Students’ Mathematics Achievement Based on Decision Tree Algorithm

Research Article
Open access

Analysis of the Influence of Some External Factors on Students’ Mathematics Achievement Based on Decision Tree Algorithm

Yichao Wang 1*
  • 1 North University of China    
  • *corresponding author 1220448818@qq.com
Published on 26 October 2023 | https://doi.org/10.54254/2753-7048/11/20230750
LNEP Vol.11
ISSN (Print): 2753-7056
ISSN (Online): 2753-7048
ISBN (Print): 978-1-83558-047-9
ISBN (Online): 978-1-83558-048-6

Abstract

With the continuous progress of the educational system in various countries, people attach more and more importance to education. In today’s school education, the math score of students is an important indicator for the assessment of student learning outcomes, on the one hand, can be a real, objective reflect students’ actual learning and teachers’ teaching level, on the other hand can also choose for students after learning methods, teachers to play a good role in guiding the teaching plan. This study analyzes the student performance data of math students in kaggle, explores the factors that affect the students’ performance of this course from many aspects, and then puts forward reasonable suggestions and applies them to practical teaching so as to improve the teaching quality. All of the data the research has been getting is from Kaggle math students. The data set contains nearly 400 pieces of relevant educational data about students, and there are dozens of factors that affect the performance of each student, such as parental cohabitation, educational support and the desire for higher education. The topic of our study is to analyze the impact of students’ family situations and educational support on their math performance by using the C4.5 algorithm in the decision tree algorithm as an auxiliary tool. And this paper finally came to this interesting conclusion: motivated students with poor parental relationships and little educational support from school and family tend to do better in math.

Keywords:

decision tree algorithm, parental relationship, educational support, student intention students’ math scores

Wang,Y. (2023). Analysis of the Influence of Some External Factors on Students’ Mathematics Achievement Based on Decision Tree Algorithm. Lecture Notes in Education Psychology and Public Media,11,250-258.
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References

[1]. P. Cortez and A. Silva. April, 2008.Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12. https://www.kaggle.com/datasets/janiobachmann/math-students

[2]. IT23131, October, 2021, The watermelon of the decision tree, https://blog.csdn.net/IT23131/article/details/121068259

[3]. Love_YourSelf, Novermber, 2022, Classification based on decision tree, https://blog.csdn.net/qq_48068259/article/details/127640315

[4]. Nine door data analysis research center, in June, 2021, the advantage of decision tree, http://www.jiudaomen.com.cn/question/newsdetail_68974687.html

[5]. Hu Mingming.,2008, Research on the Application of Decision Tree Algorithm in the Analysis of Students’ course scores,22-27. Master’s Thesis, Harbin Normal University.

[6]. Hu Mingming.,2008, Research on the Application of Decision Tree Algorithm in the Analysis of Students’ course scores,17-18. Master’s Thesis, Harbin Normal University.

[7]. Yogesh Sachdeva, Ayushi Arora and Kriti Suri，January,2022,Data Exploration & Visualization Project on Student-Mat dataset using Python. https://www.kaggle.com/code/yogeshsachdeva223/student-mat-exploration-and-visualisation/notebook

Cite this article

Wang,Y. (2023). Analysis of the Influence of Some External Factors on Students’ Mathematics Achievement Based on Decision Tree Algorithm. Lecture Notes in Education Psychology and Public Media,11,250-258.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 4th International Conference on Educational Innovation and Philosophical Inquiries

ISBN：978-1-83558-047-9(Print) / 978-1-83558-048-6(Online)
Editor：Enrique Mallen, Javier Cifuentes-Faura
Conference website: https://www.iceipi.org/
Conference date: 7 August 2023
Series: Lecture Notes in Education Psychology and Public Media
Volume number: Vol.11
ISSN：2753-7048(Print) / 2753-7056(Online)

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References

[1]. P. Cortez and A. Silva. April, 2008.Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12. https://www.kaggle.com/datasets/janiobachmann/math-students

[2]. IT23131, October, 2021, The watermelon of the decision tree, https://blog.csdn.net/IT23131/article/details/121068259

[3]. Love_YourSelf, Novermber, 2022, Classification based on decision tree, https://blog.csdn.net/qq_48068259/article/details/127640315

[4]. Nine door data analysis research center, in June, 2021, the advantage of decision tree, http://www.jiudaomen.com.cn/question/newsdetail_68974687.html

[5]. Hu Mingming.,2008, Research on the Application of Decision Tree Algorithm in the Analysis of Students’ course scores,22-27. Master’s Thesis, Harbin Normal University.

[6]. Hu Mingming.,2008, Research on the Application of Decision Tree Algorithm in the Analysis of Students’ course scores,17-18. Master’s Thesis, Harbin Normal University.

[7]. Yogesh Sachdeva, Ayushi Arora and Kriti Suri，January,2022,Data Exploration & Visualization Project on Student-Mat dataset using Python. https://www.kaggle.com/code/yogeshsachdeva223/student-mat-exploration-and-visualisation/notebook

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