Data, Methods, & Ethics

I gathered quantitative, archival data from greatschools.org and schoolmatters.com, both websites that profile schools throughout the country. I felt this type of data was most appropriate because I wanted to demonstrate correlation between various variables. My main focus was to see how our education system is affected by policy, so I thought public high schools would be the best sample. However, my sample is still a non-representative sample because it only consists of public high schools, rather than grade schools, middle schools and universities; it is also a non-representative sample because it only consists of public high schools in the bay area, rather than schools throughout the nation.

I initially decided on possible candidates based on the reputations of high schools throughout the Bay Area. I wanted 3 exceptional schools that demonstrate very high student achievement, 3 average schools that demonstrated pretty good student achievement, and 3 "bad" schools that represented less than desirable student achievement. The “bad” schools are, in actuality, schools with average test scores and dropout rates that are much lower than the national average, therefore I would not consider them schools that are actually failing.  Due to the fact that I don't see them as actually bad schools, and to use mroe neutral terms, these schools will be ranked as "less than desirable" schools.  The schools’ statuses were initially determined by the schools reputations, since I am from the Bay Area and have heard of all of these high schools. I then went on schoolmatters.org and compared their dropout rates and test scores to confirm that the schools had been placed in the appropriate categories.  After choosing the 9 schools I would be studying, I collected the following information on them:

• Percentage of Standardized Test Scores that received a proficient or higher in both math and reading
• District Capital Expenditures: the amount of money spent on instructional materials and maintentance, per student, by district

I also went on schoolmatters.com and looked at what technological programs were offered. The Art programs offered included Computer Arts, Video/Film Production, and Photography. I considered Photography a technological program because of the use of a camera. “Other Special Programs” offered included Radio/video/multimedia, Science and Technology, and Yearbook. I considered Yearbook a technological program because of the use of the camera, as well as the computer skills that are involved in editing yearbook pages and creating the layout. Lastly, the only technological Vocational program was Technology.   When organizing the data collected, this is the table I came up with.

School	Ranking	Dropout Rates	Reading Scores	Math  Scores	Capital Expenditures	Programs Offered
Miramonte	exceptional	0.30%	98.00%	99.00%	$2,316	7
Mission San Jose	exceptional	0.20%	98.00%	99.00%	$1,554	6
Monte Vista	exceptional	0.10%	99.00%	99.00%	$3,896	6
Mountain View	pretty good	0.60%	90.20%	91.40%	$775	7
Dublin	pretty good	0.80%	91.00%	91.00%	$3,522	6
Castro Valley	pretty good	0.90%	95.00%	93.00%	$2,481	6
Hayward	less than desirable	2.70%	75.00%	73.00%	$262	5
San Lorenzo	less than desirable	1.90%	69.00%	68.00%	$318	5
Mount Eden	less than desirable	4.40%	77.00%	76.00%	$262	3

I chose each of these factors because the goal is to see how funding, student achievement, and access to technology are all interrelated. The capital expenditures is used as the funding component; the standardized test scores and dropout rates are both used as the student achievement components, and the programs offered are used as the access to technology component. While there are certainly many other details that could be considered to assess the same thing, there are the ones that were more readily available to me.  I did not need to interview anybody or conduct a survey to receive this information; it is open to the public via various websites.  Therefore, confidentiality and ethics were not an issue in this data collection process.