Valle, C., & Leonard, J. D. (2014, June), Predicting Time to Graduation in Engineering by Student Behavior and Gender  Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--22930

\bibitem{asee_peer_22930}
  Valle, C., \& Leonard, J. D. (2014, June), \emph{Predicting Time to Graduation in Engineering by Student Behavior and Gender}
  Paper presented at 2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana.
  10.18260/1-2--22930

Christine Valle and John D. Leonard II.  "Predicting Time to Graduation in Engineering by Student Behavior and Gender".  2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana, 2014, June.  ASEE Conferences, 2014.  https://peer.asee.org/22930 Internet.  14 Dec, 2024

\bibitem{asee_peer_22930}
  Christine Valle and John D. Leonard II.
  "Predicting Time to Graduation in Engineering by Student Behavior and Gender".
  \emph{2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana, 2014, June}.
  ASEE Conferences, 2014.
  https://peer.asee.org/22930 Internet.  14 Dec, 2024

@INPROCEEDINGS{asee_peer_22930
author = "Christine Valle and John D. Leonard II"
title = "Predicting Time to Graduation in Engineering by Student Behavior and Gender"
booktitle = "2014 ASEE Annual Conference \& Exposition"
year = "2014"
month = "June"
address = "Indianapolis, Indiana"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/22930}
number = {10.18260/1-2--22930}
}

TY  - CPAPER
AB  - Predicting Time to Graduation in Engineering by Student Behavior and                               GenderThis study looks at retention and graduation patterns in engineering by gender, seekingspecifically to understand why students tend to take longer than the advertised 4 years tograduate, and focusing on one institution only. While much attention has been given inthe past to the issues of retention of women and under-represented minorities inengineering, most analyses use data collected at multiple institutions (thus blendingtogether results coming from vastly different campus cultures) and tend to focus on theexperiences of those who graduate versus those who never do. In this work, we focus onwhy the students who do graduate take much longer than what is routinely advertised.This study follows in the footsteps of previous work, and provides a formulaic model forpredicting time to graduation of engineering students, by gender and by “type ofbehavior” while enrolled at school. That is, we seek to take into account both goodreasons for delaying graduation (such as spending a semester in a co-op or internship)and negative reasons (such as failing classes) – and provide an estimate for the delaybased on each experience. The hope is that this model helps inform the discussions inour institution’s upper administration and state legislature regarding time to graduation.Our state, like many, is currently under pressure to reduce it to satisfy various local, cityand state stakeholders.
AU  - Christine Valle
AU  - John D. Leonard II
CY  - Indianapolis, Indiana
DA  - 2014/06/15
PB  - ASEE Conferences
TI  - Predicting Time to Graduation in Engineering by Student Behavior and Gender
UR  - https://peer.asee.org/22930
DO  - 10.18260/1-2--22930
ER  -