ADVANCE Institutional Data Using Institutional Data to Create Institutional Change.

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Presentation transcript:

ADVANCE Institutional Data Using Institutional Data to Create Institutional Change

ADVANCE Cooperative Agreement (10/10/2001) “Awardee will maintain a uniform database of quantitative indicators of activity and progress. NSF will provide general guidelines for the collection of data in order to provide coordination across ADVANCE Institutional Transformation projects and to establish the basis for evaluation of the ADVANCE program.”

Outline Alice Hogan, NSF: History of data requirement, indicator choice Janet Malley, University of Michigan: Example(s) of using indicators to effect institutional change Virginia Valian, CUNY-Hunter College: Challenges of collecting some indicators Lisa Frehill, New Mexico State University: Possibilities for standardization across institutions Jennifer Sheridan, University of Wisconsin- Madison: Discussion and wrap-up

Summary: ADVANCE site experience with indicators Positive experiences of using indicators to create institutional change Data collection challenges Standardization

Using indicators to create institutional change Process of collecting the data itself Communication tool used to highlight problems with real data across the institution Strong relationships with “data keepers” Improve institutional reporting capacities, e.g., Centralize collection and reporting of data Create a standardized letter of offer/aid in collection of start- up data Improve individual-level accounting of space allocation Make aware that “someone is watching” Fixing errors in the databases

Using indicators to create institutional change # and % of women in S&E Highlight low numbers of women of color in ADVANCE departments Low numbers of women full professors led to development of programs aimed at the promotion from associate to full process Breakdown by unit assists program in identifying areas of greatest need

Using indicators to create institutional change Attrition by gender Highlights very large difference made when one woman leaves compared to one man—due to low numbers Changes in retention practices # of women S&E faculty in endowed/named chairs More active searching for women chairs More publicity around nominating women, education efforts

Using indicators to create institutional change # and % of women S&Es in administrative positions New nomination procedure Salary of S&E faculty by gender

Using indicators to create institutional change Evaluation of ADVANCE initiatives # and % women faculty Attrition by gender # and % women in administrative positions Salary of S&E faculty by gender Tenure promotion outcomes Space allocation by gender Startup packages by gender

Using indicators to create institutional change Additional suggested indicators “New Hire Report” (Proportion of new hires who are women) Space quality indicators Race/ethnicity/nationality Recruitment statistics—gender composition of short lists, offers

Challenges of Data Collection Easiest indicators # and % women faculty in S&E by dept./dept. and rank # of women in S&E in non-tenure-track positions # and % of women S&Es in administrative positions # of women S&E faculty in endowed/named chairs

Challenges of Data Collection More difficult, but gathered primarily from centralized data sources Tenure promotion outcomes by gender Years in rank by gender Time at institution by gender Attrition by gender Salary of S&E faculty by gender

Challenges of Data Collection Most difficult # and % of women S&E faculty on promotion and tenure committees Space allocation of S&E faculty by gender Start-up packages of newly hired S&E faculty by gender

Challenges of Data Collection Time and expense of gathering data But, once procedures in place, great benefits School-level data more challenging because cooperation of more people is involved Requests for individual-level data for making personal cases of inequity Dismissed by some due to low Ns Confidentiality issues for some indicators

Standardization Across Institutions ADVANCE sites felt all of the indicators would be valuable to standardize across institutions if possible # and % of women faculty in S&E Tenure promotion outcomes Attrition by gender # and % of women in non-tenure-track positions # and % of women in administrative positions

Standardization Across Institutions Most indicators would be easy to adjust collection to fit into a standardized reporting structure Space allocation, start-up are the exceptions