Uploaded March 2025 | Updated September 2026, 2 weeks ago
#ShinyConf #ShinyConf2024
Abstract: In this session, we provide some examples of RShiny applications that have made a positive impact in the higher education sector. Specifically, we highlight ways our office, the Office of Institutional Analytics at Indiana University, has been using RShiny to support advanced analytics for improving student outcomes. For example, one RShiny application facilitates the creation of matched comparison groups to evaluate and improve campus programs and instruction – users upload a csv file, select variables to create a matched comparison group, set parameters to define the matching process, and download a resulting matched dataset that can be used for program and course evaluation analyses on campus. Another RShiny application assists campus stakeholders with selecting peer institutions - administrative staff select variables to identify similar institutions and set weights for those variables to reflect the importance of each variable in terms of defining peers for their institution. The application then computes a distance score based on those selections and presents a list of the most similar institutions to users. These examples provide powerful opportunities to imbed analytics into the decision-making process around student success.
____________________________
Join us this year! Sign up for ShinyConf 2025 here: go.appsilon.com/register-shinyconf2025
#ShinyConf #ShinyConf2024
Abstract: In this session, we provide some examples of RShiny applications that have made a positive impact in the higher education sector. Specifically, we highlight ways our office, the Office of Institutional Analytics at Indiana University, has been using RShiny to support advanced analytics for improving student outcomes. For example, one RShiny application facilitates the creation of matched comparison groups to evaluate and improve campus programs and instruction – users upload a csv file, select variables to create a matched comparison group, set parameters to define the matching process, and download a resulting matched dataset that can be used for program and course evaluation analyses on campus. Another RShiny application assists campus stakeholders with selecting peer institutions - administrative staff select variables to identify similar institutions and set weights for those variables to reflect the importance of each variable in terms of defining peers for their institution. The application then computes a distance score based on those selections and presents a list of the most similar institutions to users. These examples provide powerful opportunities to imbed analytics into the decision-making process around student success.
____________________________
Join us this year! Sign up for ShinyConf 2025 here: go.appsilon.com/register-shinyconf2025
