ASEE EDGE Graphic Explorer: Underrepresented Minority Women Engineering Tenure-track/Tenured Faculty
Explore, visualize, and download graphics of the number of underepresented minority women tenure-track/tenured
faculty in engineering according to race/ethnicity by region, institution type, Carnegie class,
discipline and rank. Data published by
Funded through Engineering Deans Gender Equity Initiative.
Touch bars for more information and click the
on top of graph to download plot
ASEE EDGE Data Explorer: Underrepresented Minority Women Engineering Tenure-track/Tenured Faculty
Explore, select, and download data of the number of underepresented minority women
tenure-track/tenured faculty in engineering according to race/ethnicity by region, institution type, Carnegie class, discipline and rank. Data published by
Funded through Engineering Deans Gender Equity initiative.
More detailed information on how to use this web application.
Further explanation on the data of underepresented minority women tenure-track/tenured positions in engineering
as well the Profiles methodology can be found
This website mainly allows to explore and visualize data of the number of underrepresented minority women tenure-track/tenured positions in engineering based on these indicators: region,
institution type (doctoral/master's/bachelor's) and Carnegie class (r1/r2,m1/m2 etc.) and ASEE disciplines. This purpose is to address the Engineering Deans Gender Equity initiative goal which is to reduce barriers to effective recruitment, retention, and advancement of underrepresented minority women and white women tenure-track/tenured positions in engineering.
Explore, view and download data in this section.Select variables of interest in the
tab panel to display data in the
tab panel. Data can be download in these formats (csv, excel, pdf).
It can also be copied and printed from the site.
Explore, visualize and download data and graph of interest in this section.This section graphically displays the percentage of women tenure-track/tenured positions in engineering.
Each tab represent each variable to explore the data in an interactive way. Variables of exploration are region, ASEE Discipline,
institution type and Carnegie Class.
App was Developed by Angela Erdiaw-Kwasie Data Analyst II, ASEE IRA.
Methodology for Profiles for Engineering and Engineering Technology Colleges
ASEE’s data collection for the Profiles for Engineering and Engineering Technology Colleges survey begins
in the fall of each year and concludes at the end of January. During this time period, participating institutions entered their data on ASEE’s web-based survey instrument.
After the completion of the data collection, ASEE staff verify the entered data using a web-based data verification process. In the spring, ASEE institutes quality control procedures,
which include comparing data to that entered in previous years and contacting schools about questionable data.
Although ASEE has made every effort to ensure that the information is correct, each institution is ultimately responsible for the accuracy of its data.
Totals are compiled based on discipline rather than department or degree program.
This method allows us to track broader trends.
For more exact views of each school’s department and degree data, please refer to the individual
web profiles for each institution located at
Engineering Profiles Descriptions
Visit this page About the Data to get a detailed description of data ASEE collects as well
as explanations to the terminology used in the data
Developed by Angela Erdiaw-Kwasie, Data Analyst II, ASEE IRA.