For decades, researchers argued the relations between educational inputs and students outcomes. Some researchers argued there are positive relations between educational inputs and outcomes. Others revealed the relationship between educational inputs and student outcomes doesn't exist.
In the article, I will address the aforementioned argument by analysing the relations between upper secondary school teachers’ salary and PISA. Teachers’ salary is an important index for many researchers to evaluate the educational inputs. The PISA is an index that evaluates countries’ student's performance summarised by OECD, which is a famous data collection website.
I will utilise two quantitative research methods, time series graph and Pearson correlation coefficient to achieve my objectives. The sampling, data validity, details of the methodologies are mentioned in the following chapters. I will come up with a result which illustrates the statistical relations between educational inputs and outputs.
The process of the research can be considered as applying educational production function or cost-benefit analysis. Finally, I will provide implications of my research on education policy making. I doubted the validity of input-based policy based on the results of my research, while I provide guide and suggestions to educational policymakers.
Table of Contents
1. Purpose
2. Literature Review
3. Method
4. Questions/Expectations
5. Relevance of data
6. Implication
7. References
Research Objectives and Topics
The primary objective of this research is to analyze the correlation between upper secondary school teachers' salaries and student performance in the United States, utilizing PISA scores as a metric for educational outcomes to determine if variations in expenditure influence student achievement.
- Analysis of the education production function and cost-benefit perspectives in public schooling.
- Evaluation of the impact of input-based versus output-based educational policies.
- Application of time series analysis to identify trends between teacher salary and student performance.
- Utilization of the Pearson correlation coefficient to assess the strength of statistical relationships.
- Development of policy recommendations regarding educational resource allocation.
Excerpt from the Book
Method
I will utilise two different kinds of quantitative research method to address the aforementioned questions. Firstly, I will present a time series graph of the data. Results will be interpreted based on the time series graph. Secondly, I will utilise Pearson correlation coefficient to analyse the linear relation between teacher’s salary and the Programme International Students Assessment.
The Pearson correlation coefficient is a statistical tool to evaluation the strength of the linear relationship between two variables (Kreinovich, et al. 2013). There are multiple formulas of Pearson correlation coefficient. The formula that I will utilise is as follows (Statisticshowto, 2017):
The result r evaluate the linear relationship between x and y, in my research, x will be teachers’ salary, y will be International Students Assessments (PISA). If x and y have perfect positive relations, the value of r will be equal to 1. If x and y don’t have relations, the value of r will be around 0.
Summary of Chapters
1. Purpose: This chapter introduces the core research question regarding the correlation between teacher salaries and student performance in U.S. secondary schools.
2. Literature Review: This section examines existing theories on education production functions and debates the effectiveness of resource-based inputs in education.
3. Method: This chapter details the quantitative approach, utilizing time series graphs and Pearson correlation coefficients to analyze the relationship between inputs and outputs.
4. Questions/Expectations: This section outlines the research hypotheses and the expectation that the study will provide clarity on the impact of educational expenditures.
5. Relevance of data: This chapter explains the selection of PISA data and teacher salary indices as appropriate variables for evaluating educational production.
6. Implication: This chapter discusses policy consequences, suggesting that input-based policies may be less effective than output-based incentives.
7. References: This section lists all academic sources and datasets utilized to support the findings of the research.
Keywords
Education, Teacher Salary, PISA, Student Performance, Production Function, Cost-Benefit Analysis, Input-Based Policy, Output-Based Policy, Pearson Correlation, Quantitative Research, Educational Expenditure, Efficiency, Equity, Resource Allocation, Statistical Analysis.
Frequently Asked Questions
What is the core focus of this research?
The research examines whether there is a statistically significant relationship between teachers' salaries and student performance outcomes in the United States.
What are the central themes discussed in this study?
The study centers on the economics of education, specifically the effectiveness of input-based investments (like teacher salary) versus output-based incentives for schools.
What is the primary research goal?
The primary goal is to determine if increasing financial expenditure on teacher salaries actually leads to measurable improvements in student achievement as measured by PISA scores.
Which scientific methodology is applied?
The author uses a quantitative approach, specifically time series graph analysis and the calculation of Pearson correlation coefficients.
What is covered in the main body of the text?
The main body reviews existing literature on education production functions, details the statistical methodology, presents data analysis, and discusses implications for policymakers.
Which keywords characterize this paper?
Key terms include Education, Teacher Salary, PISA, Production Function, Input-Based Policy, and Cost-Benefit Analysis.
How does the author define input-based policy?
The author defines it as policies focusing on changing educational inputs, such as reducing class sizes or increasing overall teacher salaries, to improve school quality.
What is the author's final conclusion regarding educational policy?
The author concludes that because no statistical relation was found between teacher salary and student performance, policymakers should pivot toward output-based incentives to ensure a higher return on educational investments.
- Quote paper
- Xiaole Fan (Author), 2017, Is there a relation between the salary of teachers and the performance of students?, Munich, GRIN Verlag, https://www.grin.com/document/377630
