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To Be Or Not To Be Revisiting An Analytical Method Using Demographic Data To Predict Asee Student Chapter Viability

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Conference

2006 Annual Conference & Exposition

Location

Chicago, Illinois

Publication Date

June 18, 2006

Start Date

June 18, 2006

End Date

June 21, 2006

ISSN

2153-5965

Conference Session

Graduate Student Experiences

Tagged Division

Graduate Studies

Page Count

8

Page Numbers

11.1342.1 - 11.1342.8

DOI

10.18260/1-2--436

Permanent URL

https://peer.asee.org/436

Download Count

326

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Paper Authors

biography

Carol Mullenax Tulane University

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Carol Mullenax is finishing up a Doctorate in Biomedical Engineering at Tulane University while also employed by Bastion Technologies as a project manager on the NASA Non-Exercise Physiological Countermeasures Project in Houston, Texas.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

To Be or Not To Be – Revisiting an Analytical Method Using Demographic Data to Predict ASEE Student Chapter Viability

Introduction/purpose: American Society for Engineering Education (ASEE) student chapters have formed at several universities in recent years. The original paper developed an analytical method to predict ASEE student chapter viability from environmental conditions at an institution. The goal of this paper was to revisit the output of the original equation using current demographic and student chapter information, and determine if the given analysis is still applicable.

Materials/methods: In the original study, a regression equation was generated which related university demographic data to successful student chapter metrics.1 Data were gathered for the academic year 2004-2005 based on the ASEE college profiles and direct inquiry of current chapter officers and the ASEE membership office. Comparison was made between original and current outcomes.

Demographic data were updated for the original candidate schools and for all schools listed as having an ASEE student chapter on the ASEE website.2-19 Categories included student population and composition, average residency, student funding type, and number of competing campus professional organizations. Chapter-specific inputs were solicited from eleven universities with student chapters. Seven schools responded with data including the number of student members, number of meetings, number of events, number of event attendees, and number of attendees at the ASEE annual meeting (Figure 1).

Type Variable name Description Student STLOC number of local (not national) student members at the school Chapter STCONF number of student members attending the last ASEE annual conference MTGS number of student chapter meetings and events per year AVGATT average attendance at meetings/events AWARDS number of awards sponsored by the student chapter University TOTFAC total number of faculty in the school of engineering PCTFMEM percentage of engineering faculty members who are ASEE members GDTOT total number of engineering graduate students PCTGDFT percentage of engineering graduate students who are full-time students PCTPHD percentage of engineering graduate students who are PhD students PCTADMIT percentage of applicants who are admitted for graduate engineering study AVGRES average number of years a graduate student is at the school (calculated) PCTTA percentage of engineering graduate students supported by teaching assistantship CLUBS number of engineering professional clubs/organizations at the school STASEE number of national ASEE student members at the school

Figure 1: Regression variable names and descriptions

Mullenax, C. (2006, June), To Be Or Not To Be Revisiting An Analytical Method Using Demographic Data To Predict Asee Student Chapter Viability Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--436

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