Data SGP is a package within the R statistical software environment for performing student growth percentile analyses and percentile growth projections/trajectories using large scale longitudinal education assessment data. It utilizes quantitativeile regression to create student growth trajectories and projections that show how much progress students must make in order to reach future achievement targets/goals. SGP provides a more realistic picture of what it will take for a student to reach proficiency by outlining the percentage of students who need to make certain types of gains in order to be successful.
SGP also provides an effective performance measure that demonstrates how well a school or district is making progress towards its goals. It focuses on the improvement of all students and not just the lowest performers. This can help to provide more targeted support to struggling students, while ensuring that high performers do not get lost in the shuffle. SGP can be used to assess the impact of accelerated programs on low and middle performing students.
For data to be useful, it must be accurate, reliable and accessible. Data governance is the set of policies and processes that ensure this happens. It involves ensuring that the people and systems that use data know what they are doing with it, are accountable for delivering on their promises and that all stakeholders have their needs met. It includes everything from the technology that stores and manages data to the procedures that govern who can access what information and how it is used.
Having the right tools is crucial to data sgp success. In addition to being able to store and process massive amounts of data, these tools must be easy to use and accessible to non-technical staff. Data governance also helps to reduce the risk of data breaches by establishing clear guidelines on how data can be used, who has access and the security controls that must be in place.
The SGP project’s first goal is to assemble or generate multi-proxy sedimentary geochemical data for every Paleozoic epoch and roughly equivalent Neoproterozoic time slice. This is a massive task that will require the collaboration of many researchers in several countries. The SGP community is currently working towards this goal, and the first results are expected to be released in late 2016.
To run SGP analyses you will need a computer that has the R software installed. It is free to download for Window, OSX and Linux. You will also need a database server, such as MySQL or PostgreSQL, to host the data you are analysing. Lastly, you will need to be familiar with the process of data preparation for running SGP analyses. Not following the proper steps can lead to misleading or inaccurate analysis results.
SGP is a relatively new field and there are still a number of challenges. The most significant is that it requires a huge amount of data to perform an accurate analysis, and this data must be carefully prepared and stored for use. This can be challenging for organizations who do not have the resources or experience to tackle this task.