Academic Paper, 2017
18 Pages, Grade: 10
2. Literature Review
5. Relevance of data
For decades, researchers argued the relations between educational inputs and students outcomes. Some researchers (Hanushek, 1989)argued there are positive relations between educational inputs and outcomes. Others (e.g. Hedges, et al., 1994) 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 method, 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.
The purpose of the article is analysing if teachers’ salary has correlation with students performance in upper secondary education schools in the United States, in order to find if variation of expenditure will cause variation of students performance.
The article will answer a question mentioned by many researchers: “does money matter (in education)”(e.g. Hedges, et al. 1994, p. 5). The question shows researchers’ exploration on the influence of changing inputs to outputs. Over decades, researchers have done various study on the correlation between inputs and outputs in education. Enormous literature support there is no correlation between inputs and outputs (Hedges, et al. 1994). Other
To appease the argues, I will conduct upper secondary school teachers’ salary as a part of inputs and utilise Programme International Students Assessment students which can be considered as student performance, which is outputs. Then, I will utilise Pearson correlation coefficient and a time series graph to identify if there are systematic relations between upper secondary school teachers’ salary and Programme International Students Assessment. I will explain the relevance of data to be used in analysis the relations between inputs and outputs in the following chapter.
At the end chapter, the article will also provide economic views on the topic and a guide for policymakers. Considering that governments’ expenditure is limited, if teachers’ salary doesn’t have an impact on students’ performance, a government can reduce the expenditure on teachers salary and increase the expenditure in other areas.
Various researchers consider (e.g. Monk, 1989) education production function as a tool to calculate productivity and rate of return in education while revealing the relationship between inputs and outputs. Researchers offer definition various of education production function. Monk (1989) provided different approaches of utilising production function in education, considered production function as the summary of technical relationships between inputs and outputs, and described it as “the maximum level of outcome possible from alternative combinations of inputs” (Monk, 1989, p.31), while Monk (1989) also suggested individuals could calculate the outcomes and assess the efficiency of provided inputs.
Johnson (1978) considered educational production function as a cost analysis technique. Her study indicated that education production function is the method that inputs, such as the number of courses offered, are combined to produce outputs, such as the number of earned credits.
Researchers illustrated different perspectives about the relationship between resources inputs and school outcomes. Hanushek (1989) found that some of the inputs have no correlation with outputs in the view of education production function, and the expenditures are not systematically related to students achievement. Hanushek (1989) drew one hundred and eightyseven studies of educational production function and utilised estimated expenditure parameter coefficients in his research.
Hanushek (1989) considered seven elements as educational inputs, including teacher/ pupil ratio, teacher education, teacher experience, teacher salary, expenditures/pupil, administrative inputs, and facilities. He mentioned the current institutional structure expenditures and the qualifications of teachers are not systematically related to students’ achievement and performance.
Hedges, Laine, and Greenwald’s study (1994) provide the evidence of the impact of educational inputs on student outcomes and illustrates systematic positive relations between educational inputs and students outcomes. Hedges and colleagues used “the sample population of studies initially identified by Hanushek (1989)” (Hedges, et al. 1994, p. 8) and found systematic positive relations between resources inputs and school outcomes. Although Hedges, Laine, and Greenwald (1994) were not arguing that increasing expenditures is the most efficiency way to improve educational achievement, they mentioned increasing expenditures and teachers experience will cause the increase of student outcomes.
Hedges and colleagues (1994) doubted the validity of Hanushek’s (1989,2003) analytic method and the validity of the conclusion. They argued the methodology, vote counting, that Hanushek (1989) utilised was unable to provide an indication of its magnitude. In the article, they utilised combined significance test to analyse the relations. The results show that almost every study in their analyse support that the positive relations exist between educational inputs and students outcomes. What’s more, they found that there are no negative relations between educational inputs and student outcomes by null hypothesis. Hedges and colleagues (1994) also found the p-value of every combination of inputs and outputs is not significant, which also suggests that the negative relations between educational inputs and students outcomes are not statistically reliable.
The conducting of educational production function can be considered as utilising costbenefit analysis in education. The output can be considered as the benefit while the input can be considered as the cost. Cost-benefit analysis is an important technique, considering education as an investment. Researchers hold similar perspectives on the cost-benefit analysis. Akinyemi (2013) argued that the cost-benefit analysis is a technique to evaluate the profitability of investment by comparing the magnitude of incurred costs, the expected benefits, and the uncertainty and risks of the investment.
In addition, various researchers mentioned perspectives of the function and definition of cost-benefit analysis. By the researchers’ articles, it’s reasonable to consider applying education production function as a cost-benefit analysis. Rothenberg’s (1975) research considered cost- benefit analysis as an apparatus for the purpose of achieving desirable directions from proposed actions. Levin (1983) mentioned utilising cost-benefit analysis provides ease of program comparison, considering that both inputs and outputs are measured in monetary units in cost- benefit analysis. Samuel (1990) considered the cost-benefit analysis as a technique to evaluate educational projects with the perspective that getting outcomes by using and allocating scarce resources.
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