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Data Collection Methodology

Data Collection Methodology- Physical Education and Academic Achievement

Method

The method we have decided to use is a quantitative data analysis based on documents. We will collect document data from high schools in low income areas within the 5 boroughs. The documents will include the physical education minutes’ students receive weekly and their standardized test scores in both reading and math.

The reason why we decided to use this method is because in a study conducted by Snelling et al. (2015) they collected data from 120 elementary schools’ in urban areas within Washington DC. The data collected included the number of minutes allocated toward physical education and students scores on a math standardized test. The aim of Snelling et al. (2015) study was to understand the relationship between the amount of time spent in PE and math proficiency at the elementary school level. This is relevant to the study were proposing because we want to understand how physical education at the high school level affects student’s academic achievement. The reason for why we want to collect data regarding PE minutes and standardized test scores in math and reading at the high school level, is because in Snelling et al. (2015) study they collected this data from elementary schools and only looked at math standardized test scores. Along with this, though researchers have sought to find the connection between PE and academic achievement by collecting data from grades 3-11 they did not compare physical education minutes to standardized test scores. Rather, their data included standardized fitness measures (FITNESSGRAM) and reading/math standardized test scores (Van, Kedler, Kohl, Ranjit & Perry, 2011).

Population and Sample

Our population of interest is high schools in low income areas within the 5 boroughs. To select our sample, we have decided that we will randomly select 3 high schools from low income areas within each borough in NYC (3 from Brooklyn, 3 from Manhattan, 3 from Staten island, 3 from Queens, and 3 from the Bronx) totaling to 15 schools. The way we decided which areas were low income in NYC was by looking at data regarding the median household income in each borough. Within these 15 schools we will collect students standardized test scores in math and reading from grades 9th -12th to compare it to the number of physical education minutes reported weekly.

Data Collecting Procedures

The quantitative data that we will be collecting are the number of minutes’ students are exposed to PE and standardized test scores. The reason we will be collecting this data is to test whether or not there is a correlation between academic achievement (test scores) and physical education (minutes allowed in gym classes) among high school students from low income neighborhoods. We will gain access to this data by asking the schools for documents that report this information.

The variables that we are interested in are standardized test scores and PE minutes. We are interested in these variables, as we want to find out if the amount of time allocated toward PE has an affect on students standardized test scores. The independent variable is the amount of PE minutes and the dependent variable is the standardized test scores. In our particular research project there are mediating as well as moderating variables that are present such as age, gender, and race. Such factors may influence the results and are variables that we may consider in later research, however for the purpose of our particular research question we are not going to focus on these variables.

Reliability

When doing our analysis, we will check that the standardized test scores (math and reading) and the number of PE minutes are accurate. We will do this by having another team check our numerical data and run the test for us again.

References

Snelling, A. M., Belson, S. I., Watts, E., George, S., Van Dyke, H., Malloy, E., & Kalicki, M. (2015). Translating school health research to policy. School outcomes related to the health environment and changes in mathematics achievement. Appetite, 93, 91-95.

Van, D. P., Kelder, S. H., Kohl III, H. W., Ranjit, N., & Perry, C. L. (2011). Associations of physical fitness and academic performance among schoolchildren. Journal of School Health, 81(12), 733-740.

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