Extra Credit Analysis of Undergraduate Engineering Students

Tushar Ojha; Don Hush

Download Paper | Permalink

Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: DSA Technical Session 3
Tagged Topics: Diversity and Data Science & Analytics Constituent Committee (DSA)
Page Count: 17
DOI: 10.18260/1-2--47448
Permanent URL: https://peer.asee.org/47448
Download Count: 66

Paper Authors

biography

Tushar Ojha University of New Mexico

visit author page

Tushar Ojha is a graduate (PhD) student in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). His work is focused on researching and developing data-driven methods for analyzing and predicting outcomes in the higher education space. He works as a Data Scientist for the Institute of Design & Innovation (IDI), UNM.

visit author page

biography

Don Hush University of New Mexico

visit author page

Dr. Hush has worked as a technical staff member at Sandia National Laboratories, a tenure-track professor in the ECE department at the University of New Mexico, a staff scientist at Los Alamos National Laboratories, and is currently a Research Professor in the ECE department at the University of New Mexico. He has a technical background in Machine Learning, Signal Processing, Theoretical Computer Science, Pattern Recognition, and Computer Vision. He is the coauthor of a 2009 text entitled "Digital Signal Analysis with Matlab" and is the author of over 100 peer-reviewed scientific publications.

visit author page

Download Paper | Permalink

Abstract

At US universities, a large number of degree-seeking undergraduate students graduate with a higher number of credit hours than is required for graduation, thereby accumulating "extra" credits. We present a detailed analysis of the extra credit usage pattern of undergraduate engineering students at a large public flagship university using custom analytical tools. Although it is unclear that all extra credits are unwanted or avoidable, they can cause increased time-to-graduation, increased cost of education, delayed entry into the workforce, lower graduation rates, etc., and are thus often believed to be undesirable. However, there is a dearth of studies that seek to explain the credit hour usage pattern of university students. The paucity of studies can be attributed to the use of inflexible and/or opaque commercial degree audit tools at universities, which curtails the possible scope of analytics on degree audit data. Consequently, such studies are generally limited to comparing overall credit numbers such as the total credits earned by the student, the credits required by the student’s specific degree program at graduation, etc., and do not consider the usability of individual credits towards the degree program requirements. In this paper, we employ a credit-tree framework for analyzing the extra credit accumulation patterns. A custom-built specialized audit tool was used to assign student credits to one of three categories: "unusable" credits that do not match any degree requirement, "excess" credits that can be removed without changing the requirement satisfaction, and "applied" credits that contribute to requirement satisfaction without excess. It is quite obvious that this facilitates credit analysis at the course and degree requirement level, which is key to studying the factors affecting credit efficiency. We pursue the following bifold objective: understanding the composition of extra credits in terms of its constituents, i.e., unusable and excess credits, and revealing the factors influencing extra credits. We present an extensive analysis into the widely perceived factors responsible for extra credit accumulation such as transfer credit loss, program (major) change, hidden (prerequisite) requirements, repeated classes, remedial classes, financial incentives (to maintain scholarship), leisure classes, etc. As a conclusion to our analysis, we present a comparison of engineering school results to that of campus-wide results to uncover similarities (or dissimilarities) in extra credit accumulation patterns. The results reveal that although engineering and campus-wide students accumulate a similar number of extra credits, their composition is different. We would like to note that the methods used in this analysis, although applied to the data from a specific university, are generally useful for credit hour analysis.

Citation
Format

Ojha, T., & Hush, D. (2024, June), Extra Credit Analysis of Undergraduate Engineering Students Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47448

TY  - CPAPER
AB  - At US universities, a large number of degree-seeking undergraduate students graduate with a higher number of credit hours than is required for graduation, thereby accumulating &quot;extra&quot; credits. We present a detailed analysis of the extra credit usage pattern of undergraduate engineering students at a large public flagship university using custom analytical tools. Although it is unclear that all extra credits are unwanted or avoidable, they can cause increased time-to-graduation, increased cost of education, delayed entry into the workforce, lower graduation rates, etc., and are thus often believed to be undesirable. However, there is a dearth of studies that seek to explain the credit hour usage pattern of university students. The paucity of studies can be attributed to the use of inflexible and/or opaque commercial degree audit tools at universities, which curtails the possible scope of analytics on degree audit data. Consequently, such studies are generally limited to comparing overall credit numbers such as the total credits earned by the student, the credits required by the student’s specific degree program at graduation, etc., and do not consider the usability of individual credits towards the degree program requirements. In this paper, we employ a credit-tree framework for analyzing the extra credit accumulation patterns. A custom-built specialized audit tool was used to assign student credits to one of three categories: &quot;unusable&quot; credits that do not match any degree requirement, &quot;excess&quot; credits that can be removed without changing the requirement satisfaction, and &quot;applied&quot; credits that contribute to requirement satisfaction without excess. It is quite obvious that this facilitates credit analysis at the course and degree requirement level, which is key to studying the factors affecting credit efficiency. We pursue the following bifold objective: understanding the composition of extra credits in terms of its constituents, i.e., unusable and excess credits, and revealing the factors influencing extra credits. We present an extensive analysis into the widely perceived factors responsible for extra credit accumulation such as transfer credit loss, program (major) change, hidden (prerequisite) requirements, repeated classes, remedial classes, financial incentives (to maintain scholarship), leisure classes, etc. As a conclusion to our analysis, we present a comparison of engineering school results to that of campus-wide results to uncover similarities (or dissimilarities) in extra credit accumulation patterns. The results reveal that although engineering and campus-wide students accumulate a similar number of extra credits, their composition is different. We would like to note that the methods used in this analysis, although applied to the data from a specific university, are generally useful for credit hour analysis.

AU  - Tushar Ojha
AU  - Don Hush
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Extra Credit Analysis of Undergraduate Engineering Students
UR  - https://peer.asee.org/47448
DO  - 10.18260/1-2--47448
ER  -