User:Ytfig11/sandbox

Background
Interest in this topic stems from the fact that Minnesota has one of the greatest achievement gaps between white students and African American students in the nation. The wide gap in Minnesota is caused by the fact that white students in the state score significantly greater than the national average on standardized tests, while African Americans in the state score below the national average. Substantial research needs to be completed before an achievement gap of this size, which at certain points can be anywhere from a 20 to 30% difference in test proficiency, can be closed. The policy that would close, if not aid to closing to the gap will be a very complex policy, one that takes into account the numerous factors that are behind the causes of such a gap. It would also need to be a policy that is somehow not discriminatory, but yet focuses on greater gains for students who are lagging behind in the achievement spectrum.

A large number of the articles reviewed analyzed the economic causes of differentiated achievement. Okpala, Okpala, and Smith's (2004) article studies the inverse relationship between the percentage of students on free/reduced lunch in a school and the effects it can have on the percentage of students who are proficient in mathematics. They were able to demonstrate evidence proving that the greater number of students on free and reduced lunch, means that fewer students in the school will be proficient in mathematics. This disproportionately effects African American student more than white students because of their increased likelihood of being in the free/reduced lunch program.

Economic Effects
A second article that focused on poverty was by Myers, Kim, and Mandala. The key difference about this article from the previous one mentioned was that the independent variable in this study was the gap between African American and white students determined by the mean scores on the Minnesota Basic Standards Test. Unlike the previous study, there was weak significant between school poverty (percent of students on free/reduced lunch) and test scores, further proving Myesr's theory that the race effects - unexplained portions of the racial gap in test scores that cannot be attributed to racial differences in characteristics of students, schools, neighborhoods, or home environment - plays a more significant role in test scores. This opens the door for further research to determine whether race effects truly are a unidentified cause to student achievement, because right now is it just speculation.

Much of the reading I have already done have outlined great research and have given me great ideas as to the direction I want to take my personal project. In a paper titled “The effect of School Poverty on Racial Gaps in Test Scores: The Case of the Minnesota Basic Skills Test”, they focused on school poverty as opposed to the poverty level of the students as a determinant of the achievement gap and the success rate of students in the school. This motivated me to do additional search to determine the amount of dollars per student each school received from the state and include it as a variable in my data set. Another literature that helped me add additional variables to my data set was titled “What are the Long-Term Effects of Small Classes on the Achievement Gap? Evidence from the Lasting Benefits Study”. Once again, what I appreciated about this study was this it broaden my scope of variables and potential causes of the achievement gap. I’ve now decided to add student-teacher ratios to my dataset to determine whether schools with small classes have a more positive effect on test scores than schools with normal-higher student-teacher ratios.

Another economical cause that is seen as affecting student achievement is the local allotment and spending of schools. Condron and Roscigno (2003) focused their study on how the politics of allocation, specifically, how local government allots school in neighborhoods who are more politically involved greater portions of funding. Once again, this negatively effects African American students who typically attend schools in urban districts with constituents who are less likely to be politically engaged, and more likely for their schools to be short changed when it comes to funding. The article stated that schools with higher levels of low-income students, spend an average of $790/per pupil less than schools with lower levels of low-income students. With about 383 students, that is roughly $302,570 less that urban schools aren't able to spend on instruction.