Training

“Analysis of education performance indicators in Microsoft Excel” screencast series

The ReSEP “Analysis of education performance indicators in Microsoft Excel” screencast series is a short training series consisting of 6 screecasts orgininally created as part of ReSEP’s “Course on Education Indicators” workshop presented to the Department of Basic Education (DBE). The respective videos can be viewed below.

1. A Basic Introduction to Annual National Assessment (ANA) Indicators

In this screencast, we focus on grade 3 numeracy performance within classrooms using individual-level data on two schools from the 2010 Verification ANA.  We look at how to manually calculate average numeracy scores across individuals and how to create new variables and performance indicators.  Then we intoduce pivot tables as a useful alternative to manually calculating summary performance measures and show how the various features of Excel’s pivot table function can further be used to calculate disagregated summary performance indicators.

2. School-level Indicators on Grade 3 Numeracy Performance  – Part I

In the second screencast of this series, we focus on grade 3 numeracy performance across schools using school-level data on all 812 schools included in 2010 Verification ANA. In part I, we take a look at how one can use Excel’s pivot table function to calculate minimum, average, and maximum grade 3 numeracy performance levels by school qunitile and how this information can easily be illustrated graphically using the Pivot Chart function.  We also use the Report Filter to identify the weakest-perform school in the data. Finally, we use Pivot tables once more to compare the quality of assessment practices across school quintiles and provinces by comparting the average grade 3 numeracy mark awarded by teachers and the average grade 3 numeracy mark awarded by the HSRC .

2. School-level Indicators on Grade 3 Numeracy Performance  – Part II

Part II of the second screencast in the series continues with the analysis of grade 3 numeracy performance at the school level using the data from 2010 Verification ANA.  However, the focus now shifts away from calculating single summary measures such as mimumim, mean, and maximum performance levels and turns to looking at entire distibutions of performance.  Specifically, we take a look at how Excel’s Pivot table function can be used in combination with the AnalysisToolpak add-in to construct histogram data with which one can graphically illustrate average grade 3 numeracy performance distributions for all schools and for the schools within a specific quintile.

3. A Basic Introduction to SACMEQ in Excel

In screencast 3, we use the grade 6 data from the South African section of the SACMEQ 3 data. Pivot tables are used to calculate measures of pre-school attendance by quintiles, average reading and math scores by gender and text book acces by quintile and province.

4. A Basic Introduction to Graphing in Excel

Screencast 4 explains how to use graphs in Exel to extract meaning from data. Using the same SACMEQ 3 data we show how one goes about selecting which graph type is most approropriate for the data you have.

5. Analysing Matric Pass Rates

Screencast 5 introduces the Matric 2010 data. In this screencast we use pivot tables to compare the matric pass rates between both school quintiles and provinces. We also illustrate how these tables can be graphed.

6. Comparing SBA and Exam Marks

In the final screencast in this series, we use the same Matric data as in screencast 5 to compare the School Based Assessment (SBA) and Matric Exam marks. We go on to investigate whether these measures deviate more in rich or poor schools and whether this is a larger problem in certain provinces. In our analysis make use of density curves (“glorified histograms”) as well as summary statistics.