Data sgp is a set of student assessment score data containing the scores that students were given on various tests throughout their education. This set of data can be analyzed to create a profile of each individual student and help identify the areas in which students need improvement. Data sgp also provides the ability to predict student performance in future years using the results from past tests. This information is useful to schools and districts looking to improve their education system.
The SGP package allows for many different ways to conduct SGP analyses. While the lower level functions studentGrowthPercentiles and studentGrowthProjections can be used to analyze a single file, the higher level wrapper functions prepareSGP and updateSGP make it much easier to run these analyses for multiple files. Typically, these steps are conducted simultaneously in operational SGP analyses. For a more comprehensive description of these steps, please consult the SGP Data Analysis Vignette.
When creating a SGP analysis with the prepareSGP function, it is important to decide whether or not you will use WIDE or LONG data formats. In general, the lower level functions will use WIDE data, while the higher level wrapper functions will utilize LONG data. For most operational analyses, it is likely that you will want to use LONG data as the longer format has numerous preparation and storage benefits over WIDE data.
Choosing which columns to include in the sgpData dataset is another important decision that needs to be made prior to running SGP analyses. The first column, ID, provides the unique student identifier. The next 5 columns, GRADE_2013, GRADE_2014, GRADE_2015, and GRADE_2016 provide the grade level associated with each student’s assessment scores. The last five columns, SS_2013, SS_2014, SS_2015, and SS_2016 provide the scale scores associated with each student’s assessments.
In addition to the sgpData dataset, there is also a sgpData_LONG data set that contains all of these data elements in one file. This dataset is particularly helpful when conducting long-term SGP analyses. In this case, the sgpData_LONG dataset is used to construct the studentGrowthPercentiles and studentsGrowthProjections datasets that are then utilized by the higher level wrapper functions.
To make the most of the sgpData dataset, it is recommended that you read the vignette on SGP Data Analysis to understand the syntax and semantics of the file. Once you have a grasp on this, you can use the prepareSGP function to quickly build your own SGP dataset. This will save you time and allow you to focus on analyzing the actual results of your SGP analyses. This will give you the best chance to find a pattern or trend that may be present in your data. It will also help you to identify any anomalies or unusual patterns that may arise within your data set. By identifying these anomalies, you can take action to correct any problems before they become serious. This will help your SGP analyses to be as accurate as possible and ensure the highest levels of performance for your educational institution.