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While the term big data has become a buzzword in science, business and modern life it refers to datasets that are too large for traditional information management applications. In comparison the data sgp research that we are working on is relatively small. This is why we sometimes refer to it as medium data.
The goal of our work is to assemble unprecedented amounts of information about the student population in a way that will allow us to answer important scientific questions. To do this we use a relatively straightforward, custom relational database. While the size of this database is substantial compared to previous studies it is still considerably smaller than the data set that would be required for an analysis of global Facebook interactions.
Our goal is to make this data available in a form that is easy for teachers and parents to understand. To do this we present the results in percentile terms which are familiar to most educators and parents. We also include links to more detailed descriptions of our methods and interpretations. The goal is to allow teachers and parents to better support the growth of their students.
In the future, we plan to expand our efforts to collect more diverse types of data and provide more sophisticated analyses. In particular, we want to explore the potential of using additional sources of data, such as administrative records, standardized tests and college admissions data. We are also interested in comparing the effects of various policies and interventions on student growth.
A new generation of software is enabling researchers to quickly and easily analyze large datasets. This software is called “Spatial Generalized Linear Models” (SGPLM), and it can help identify patterns and trends in student performance data that might be overlooked by more traditional analysis techniques. In addition, SGPLM can be used to detect outliers and identify anomalies in the data.
The SGPLM algorithm has the potential to transform how we do research by allowing us to discover patterns in large datasets that are otherwise difficult to see. This will lead to better interventions and improved educational outcomes for our nation’s students. We hope that this tool will become the standard for measuring student achievement in the United States and beyond. This is an exciting time for research in education. We are at the forefront of a revolution that will transform our understanding of students and their learning. We look forward to your contributions to this effort. We need your ideas, your enthusiasm and your help to make this dream a reality.