09/28/2010 - 12:00am

In the latest ranking by National Research Council (NRC) of The National Academies, the Mathematics Department at UCI was ranked among a pool of 127 mathematics programs in the country. The two overall ranking based on two different methods are:

Regression based, 20-52;

Survey based, 11-34.

The report also provided the rankings of the following categories:

Research, 4-16;

Student Outcomes, 105-120;

Diversity, 60-90.

The numbers provided in each rating reflects the range between the 5th and the 95th percentile of our ranking.

During the last NRC ranking in 1995, the UCI Mathematics Department was ranked 63rd out of 139 programs. The program was also listed as one of the five most improved mathematics departments in the country at that time. In 2007, UCI Math was ranked #5 by the Chronicle of Higher Education's Faculty Scholarly Productivity Index. This upward trend is again confirmed by the current NRC ranking that places our department near the top 10 in the country in research category. As for the overall ranking, by taking the midpoint of the Survey based ranking, one naturally concludes that the Mathematics Department is at about 23rd in the country, and the Regression based at about 36th. Both methods indicated a substantial improvement from the 1995 ranking.

For a short explanation of the rankings, regression based method (R-ranking) extracts weights from a set of raters by their rating of actual programs (with known identity) using regression. Survey based method (S-ranking) gets weights by surveying directly faculty representative from all participating programs on how each would assign weights to the variables. Comparing these two methods, R-ranking is based on a relatively small samples of faculty, implicitly has a reputational component, and is more affected by the size of a program. On the other hand, S-ranking has no reputation effect and reflects normative judgement by faculty of the components of perceived quality. Undoubtedly, the current Research and Survey based results reflects relatively young, small and fast improving program more objectively and will have an upward effect on the Regression based outcome on the next set of NRC data. For complete data and details of these methodologies please go to http://www.nap.edu/rdp.