Ed Data Analysis of Educational

Ed Data Analysis of Educational Data Improving education is a consistent and common if not an eternal and universal goal for teachers, administrators, and policy makers, despite abundant disagreement about how best to achieve the desired improvements and indeed what the improvements themselves should be. One way to help not only achieve this goal but to determine what needs to be improved and what methods are or aren't working to achieve to bring about these improvements is through the analysis of quantitative data.

While there are limits to the usefulness of this type of data, when it comes to measuring progress and identifying gaps in performance there are few better ways to make any such determinations. For this reason, quantitative test data from a particular institution is presented below, analyzed, and recommendations for improvements are made. The data that was collected for this brief research and analysis is simply an overview of proficiency levels for Utica Junior High School as they compare to state proficiency levels.

Analyzing this data provides a cursory understanding of how Utica Junior High is performing for its students, with the state proficiency numbers helping to determine how consistent that performance is with general expectations. This data consists of simple percentages of students proficient in various areas of study -- reading and mathematics for seventh graders, and reading, mathematics, and science for eight graders, with "proficiency" determined by standardized tests built to measure pre-determined proficiency levels desired for each grade level (Ohio Dept. Of Education, 2012).

Thus, the higher the percentage the more successful the students/school, and major gaps between school and state levels indicate areas of real concern. The data is analyzed through a very simple and straightforward numeric comparison, as this is the only level of analysis that the data allows for.

Total numbers of students in Utica Junior High for seventh and eight grades, the number of students actually tested for proficiency levels, the state student population at each grade level and numbers tested, and for truly accurate analysis a host of other demographic information would need to be taken into account (Giddens, 2006). Given the information actually provided, it would not only be practically impossible but statistically meaningless to perform real manipulation and analysis of the data.

Even so, some very useful information can be gleaned form a simple side-by-side comparison of the school's proficiency percentages with overall state percentages, and in a simple assessment of the absolute value of the data points.

Interestingly, a proportionally higher number of students in seventh grade at Utica Junior High showed grade-level proficiency in both reading and mathematics, while eighth graders at the school were proportionally slightly less likely to have tested as proficient than students in the state at large in two of the areas in which they were tested -- reading and.