Stimpson, M. T. (2023, June), Engineering Program Matriculation: Timing and Graduation  Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43345

\bibitem{asee_peer_43345}
  Stimpson, M. T. (2023, June), \emph{Engineering Program Matriculation: Timing and Graduation}
  Paper presented at 2023 ASEE Annual Conference \& Exposition, Baltimore , Maryland.
  10.18260/1-2--43345

Matthew T. Stimpson.  "Engineering Program Matriculation: Timing and Graduation".  2023 ASEE Annual Conference & Exposition, Baltimore , Maryland, 2023, June.  ASEE Conferences, 2023.  https://peer.asee.org/43345 Internet.  20 May, 2024

\bibitem{asee_peer_43345}
  Matthew T. Stimpson.
  "Engineering Program Matriculation: Timing and Graduation".
  \emph{2023 ASEE Annual Conference \& Exposition, Baltimore , Maryland, 2023, June}.
  ASEE Conferences, 2023.
  https://peer.asee.org/43345 Internet.  20 May, 2024

@INPROCEEDINGS{asee_peer_43345
author = "Matthew T. Stimpson"
title = "Engineering Program Matriculation: Timing and Graduation"
booktitle = "2023 ASEE Annual Conference \& Exposition"
year = "2023"
month = "June"
address = "Baltimore , Maryland"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/43345}
number = {10.18260/1-2--43345}
}

TY  - CPAPER
AB  - This is a working paper where we examine the role of timing of matriculation into a degree granting engineering program as it relates to persistence to degree completion, while controlling for academic background and student demographic characteristics.  Degree completion in engineering remains a concern with approximately 50% of engineering students never completing a bachelor’s degree in engineering.  

Using multilevel modeling, we construct a repeated measures analysis where we conceive of a student’s probability of graduating with an engineering degree within six-years as a function of four possible program entry points plus academic performance in calculus, physics, and chemistry (measured as a weighted average across the classes and notated as MathSci below); cumulative GPA at time of application for matriculation; gender; and race/ethnicity.  To simplify the model tested, we compare majority to minority students.   

We will model the data at level 1 as:

η_ti=π_0i+π_1i (attempt1)+π_2i (attempt2)+π_3i (attempt3)+π_4i (attempt4)+e_ti

And at level 2:

π_0i=β_00+β_01 (MathSci_GPA)+β_02 (CUM_GPA)+β_03 (Gender)+β_04 (URM)+r_0i,

π_1i=β_10+β_11 (MathSci_GPA)+β_12 (CUM_GPA)+β_13 (Gender)+β_14 (URM)+r_1i,

π_2i=β_20+β_21 (MathSci_GPA)+β_22 (CUM_GPA)+β_23 (Gender)+β_24 (URM)+r_2i,

π_3i=β_30+β_31 (MathSci_GPA)+β_32 (CUM_GPA)+β_33 (Gender)+β_34 (URM)+r_3i,

and 

π_4i=β_40+β_41 (MathSci_GPA)+β_42 (CUM_GPA)+β_43 (Gender)+β_44 (URM)+r_4i 

where η_ti equals the probability of graduating with an engineering degree within six-years for matriculation attempt t for person i. 

This study has implications for both research and practice.  From a research perspective, and in addition to the value of the findings in general, the use of multilevel modeling presents a unique approach to the study of matriculation into engineering degree granting programs.  Our work will demonstrate how researchers can use multilevel modeling to study other engineering education concerns that are multivariate in nature.  

Meanwhile, our work will help practitioners understand how early or delayed entry into degree granting engineering programs may influence student degree completion.  Administrators managing increased demand for certain engineering disciplines can use the results of our study to inform their matriculation policies. 


AU  - Matthew T. Stimpson
CY  - Baltimore , Maryland
DA  - 2023/06/25
PB  - ASEE Conferences
TI  - Engineering Program Matriculation: Timing and Graduation
UR  - https://peer.asee.org/43345
DO  - 10.18260/1-2--43345
ER  -