OAITI was contracted by the Queen Rania Foundation to clean-up, restructure, and visualize survey data on Teaching Outcomes taken in 2018. QRF plans to conduct several iterations of this survey, and accordingly, our work was to ensure that the process of performing these data manipulation routines was as seamless and well-documented as possible, to ensure that the code generalizes to future survey iterations.


The data was provided in SPSS (.sav) format, along with a data dictionary indicating the possible choices for every survey question, and the desired plot type output for every question. At the specified levels of aggregation, we wrote a routine which automatically read in the data, converted the columns as needed, and outputted a format suitable for presentation and display in a web application. We utilized a large suite of tidyverse functions in order to accomplish this.


With the data reading and manipulation complete, our methodology involved structuring the data and displaying it in such a way that this work would generalize to future surveys. At a high level, we:

  1. Performed the data manipulation routines described above
  2. Created a web application using Shiny to display the results
  3. Sub-divided the application into question themes based on QRF’s input
  4. Displayed the appropriate plot type in each application theme tab
  5. Provided download buttons for both the processed data, as well as the plot itself
  6. Gave recommendations on hosting and deployment of the final application


QRF was able to see and visualize patterns in the survey data in a way that was not as practical with the raw SPSS data. Because the Shiny application we built requires no R programming knowledge to operate, a much larger universe of programmers now have access to analyze the results and provide recommendations to improve the education system and teaching experience in Jordan.

Social Benefit

One of OAITI’s primary objectives is to provide education and mentorship, particularly in the areas of data science and statistics. This application helps achieve that goal in two manners. The first is that we provided training to individuals on the QRF team in order to continue to use R and open data principles for data analysis. The second is that the application itself is a way to assess education and teaching outcomes, and hence directly furthers the mission of our organization. Ensuring that as many interested parties as possible are able to derive insights from the results of this teaching survey will help to make certain that the survey has a lasting impact on Jordan’s education system, and education systems worldwide.


Application link coming soon!