Anderson.GIS assignment 1

Ina Anderson Intro GIS- Assignment 9/18/09 Examining Regional Science Attainment and School- Teacher Resources Using GIS Mark C Hogrebe, Lydia Kyei-Blankson, Li Zou; Washington University in St Louis Education and Urban Society, Volume 40 Number 5, July 2008, 570-589 © 2008 Corwin Press, Inc Purpose This is a complex study that attempts to show the relationship between the attainment of science proficiency of 3rd and 10th grade students in the greater St Louis region with a wide number of school, teacher and student variables The researchers hoped to demonstrate how the broad effects of school factors and teacher characteristics impacted student achievement in science Previous findings on this type of research conducted around the country to date have yielded mixed results, making it important for St Louis to attempt its own analysis Findings from this research could assist in making education policy decisions where the relationships of certain variables on student achievement are clear The study contains both a statistical analysis and a GIS component First, a statistical analysis was conducted to investigate the relationship of science attainment of students in a number of school districts in the St Louis region with school variables of enrollment, percentage of students receiving free/reduced lunch, instructional expenditures per student, teacher/pupil ratio, and teacher variables of percentage with master’s degrees, salary, and years of experience Second, GIS was used to produce spatial and geographic representations of the relationships between the school, teacher and science attainment variables and St Louis area school districts This presents a geospatial picture of “how educational data are distributed across the region and shows district variation in student science attainment in relationship to where school and teacher resources are located”(Hogrebe et al 2008, 570) Data Data for this study was gathered between 2000-2005 Data on science attainment was obtained from the 30 public school districts with the highest concentration of school age children based on the 2000 census The districts are located in St Louis City and St Louis, St Charles and Jefferson counties, Missouri The indicator of student attainment was the percentage of students attaining proficient or advance level scores in science as assessed by the Missouri Assessment Program (MAP) for the rd and 10th grade levels The researchers calculated the median test score to summarize each district’s percentage of proficient/advance students on the science MAP Data on teacher and school indicators were obtained from the Missouri department of Education website in 2005 Methodology The researchers used Pearson correlation analysis to determine the strength of the relationship between the selected school and teacher resources and the percentage of proficient/advanced students in science To demonstrate the variation in science attainment across the school districts as it related to the selected school and teacher factors, the data was presented spatially and geographically using GIS Only variables with significant relationships to percentage of proficient/advanced students were used to create GIS maps Maps were then created to display both the Correlation of Instructional Expenditures and Free/Reduced Lunch With Percentage of Proficient/Advanced Students as well as Correlation of Teacher Variables With Percentage of Proficient/Advanced Students To display the Correlation of Instructional Expenditures and Free/Reduced Lunch With Percentage of Proficient/Advanced Students, the researchers created a series of maps (Figures and 3) To indicate the percentage of proficient /advanced science attainment across districts the researchers used the summary percentages for each district and divided the percentages into lower, middle and upper thirds, assigning each level a varying shade of gray or black on the map This created the background against which the variables were shown They created one map for 3rd grade and one for 10th grade The first variable, instructional expenditures per student, was also divided into thirds and coded with an icon This layer was added to the background to create the maps in Figure When juxtaposed with the proficiency data, it is easy to see the relationship between the expenditure per student with the percentage of science attainment geographically across districts The same process was repeated with Figure 3, this time adding the variable of percentage of free/ reduced lunch students, divided into three levels and coded with an icon, then added to the separate rd and 10th grade maps with the proficiency percentages in the background In Figure 4, the researchers displayed geographically the Correlation of Teacher Variables With Percentage of Proficient/Advanced Students To create these maps, similar shades were used to designate the science proficiency of students across districts in the three categories lower, middle and upper thirds Three teacher variables (percentage of teacher’s with masters, teacher experience and teacher salary) where then represented together as a three- bar graph This was a neat way of displaying what would be three separate layers in one layer, within one icon The left bar is for percentage of teachers with master’s degrees, the middle bar for teacher experience, and the right bar for teacher salary The height of the bars corresponds to the position in the variable’s distribution, with a low bar indicating the district was in the lower third of all districts on this variable, and the converse for the high bars This icon was then layered over the background map to show the effects of these teacher variables geographically across districts against student proficiency Results The results presented in this study (far too many to discuss in the context of this report) were mixed as to the magnitude and consistency of the findings across variables in relationship to student achievement The researchers point out that this is consistent with their literature review of past studies of this type The statistical results did show that one of the school variables (instructional expenditure/student) and two of the teacher variables (years of experience and salary) had significant relationships with 10th-grade percentage of proficient/advanced students, although not at the 3rdgrade level At the 10th grade level, a greater percentage of proficient/advanced students in science was associated with higher instructional expenditures per student, lower percentage participation in the free/reduced lunch program, teachers with more years of experience, higher salaries, and greater percentage with master’s degrees (Hogrebe et al, 2008, 18) The maps created for the study, however, show geographic relationships that could still be of importance to education decision makers have great implications in terms of geographic equity in funding, distribution of teachers with certain skills and student’s educational attainment There relationships are more easily apparent visually in map form than in tables If nothing else, the visual patterns can spark questions or eliminate previous assumptions that might help inform educational policy and reform I would like to see further study about how and why proficiency drops drastically between the 3rd and 10th grade in all districts, and what the variables are that could effect this drop This is essentially a non-spatial question, but could be answered spatially by comparing regions and resources as the authors have done in the present study, and adding a time factor, along with other potential variables that effect achievement over time, such as mobility, truancy and other social factors In conclusion, what I liked most about this study is that it uses GIS to take a large, complex series of statistical variables and condense them into simple, visual icons presented spatially and geographically, allowing for comparisons that would be difficult to see and comprehend in tables This is particularly useful for social science, placing the ‘numbers’ into a more useful context familiar to those who actually work in the districts studied QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture  ... and salary) had significant relationships with 10 th-grade percentage of proficient/advanced students, although not at the 3rdgrade level At the 10 th grade level, a greater percentage of proficient/advanced... background against which the variables were shown They created one map for 3rd grade and one for 10 th grade The first variable, instructional expenditures per student, was also divided into thirds... lunch students, divided into three levels and coded with an icon, then added to the separate rd and 10 th grade maps with the proficiency percentages in the background In Figure 4, the researchers