Welcome to the SciCast Group Project Site
Spring 2014 - SEOR Capstone

The importance of the ability to accurately forecast outcomes of key issues in science and technology should be obvious to the majority of individuals. What is not as obvious is how one would accomplish this feat. SciCast was designed for this purpose. SciCast is a research project, which according to its website, is “run by George Mason University and sponsored by the U.S. Government to forecast the outcomes of key issues in science and technology.” The concept of SciCast is built around the notion that information collected from many informed individuals is often better at forecasting an outcome than that same information collected from a handful of experts in the subject. This concept is often referred to as crowd sourcing.

Click on the link at the top of the page or the link below if you would like to learn more about the SciCast. We recommend taking the time to register and start contributing your knowledge to forecasting key issues in Science and Technology.


The goal of our project was to investigate how specific changes to the SciCast website effected user forecasting. As mentioned, the forecasts made by registered users are the foundation of SciCast. The SciCast sponsors were investigating making changes to the initial screen that users see when visiting the site and wanted to know if those changes would increase the number of visits that resulted in users registering for a new account. In order to aid the SciCast team, our group set-up an A/B test to collect quantitative data to determine if there was any difference in new user registrations between the original design and the proposed design. In addition to our A/B test, our group performed a Focus Group Study to collect qualitative data on “why” visitors to the SciCast interacted with the site as they did.

Our efforts resulted in the following observations which were presented to the SciCast team:

1) Adding “trending” questions to the SciCast Splash Page will result in a reduction in user bounce rates and increase user interaction with the site

2) Providing recommended questions to users will help increase user forecasts, however it needs to be ensured that the recommended questions are highly visible to the users

3) A/B testing is strong technique that can be used to ensure that proposed changes to the SciCast site will have the intended consequences on user behavior

For more details on our project, including our initial proposal and full technical report, please select the Project Files link at the top of the page or click the below link.

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Kevin Connor | Andrew Kreeger | Neil Wood