Title: Student profile of the incoming First Year Class of the College of Engineering at UPRM and their academic performance after their first year
1Student profile of the incoming First Year Class
of the College of Engineering at UPRM and their
academic performance after their first year
- Dr. David González Barreto
- Dr. Antonio A. González Quevedo
- Office of Institutional Research and Planning
- University of Puerto Rico at Mayagüez
- Presented at 2005 ASEE Annual Conference
- Portland, Oregon
- June 13, 2005
2Background Information for the College of
Engineering
- In 2003, the College of Engineering of the
University of Puerto Rico at Mayagüez had an
undergraduate enrollment of 4,476. This
enrollment places our college in the 13th
position of United States of America Engineering
Schools. - Texas AM ranked number 1 with 6,411 students
(ASEE Prism, Summer 2004). - Our college granted 680 bachelors degrees in
2001-2002, ranking number 1 in the degrees
granted to Hispanics. - The second spot belonged to Polytechnic
University of Puerto Rico with 305 degrees, and
the third to Florida International University
with 154 bachelors degrees awarded (ASEE Prism,
December 2003).
3Objectives
- Show the profile of incoming engineering freshmen
from 1990-2003 at the University of Puerto Rico
at Mayagüez - Admission index (AI)
- Type of high school
- Gender
- High school grade point average (GPA)
- College Board Scores in Aptitude and Achievement
Tests - A comparison between actual admission criteria
and suggested alternative criteria is also
presented. This longitudinal comparison is
carried out to evaluate proposed changes in
admission criteria in the future.
4Outline of the Presentation
- Profile of the Incoming First Year Engineering
Classes - Description of Admission Criteria
- Performance of the students after their First
Year in College - Suggested Admission Criteria
- Findings and Conclusions
- Bibliography
- Acknowledgements
5Profile Mean HS GPA by School Type
6Profile Mean Verbal Aptitude by Type of School
7Profile Mean Math Aptitude by Type of School
8Description of Admission Criteria
- The Admission Index (IGS) calculated for each
prospective freshmen and used by the University
of Puerto Rico system to decide who are admitted.
The admission index formula was changed by the
Board of Trustees for the incoming class of 1995 - The index includes three components the high
school grade point average, College Entrance
Examination Board (CEEB) score for Verbal
Aptitude (Spanish), CEEB score for Mathematical
Aptitude - The high school GPA has a weight of 50 of the
value of the admission index, while the
Mathematical and Verbal Aptitude each represent
25 of the AI.
9Mean AI by Type of School
10Average Admission Index per Year Engineering
11HS and 1st Year GPAs per Type of School
12Summary of Incoming Students Profile
- The average entering class of engineering is 761
students, of which 62 are male and 38 is female - Average high school grade point average is higher
for public schools students, 3.84/4.0 when
compared to private schools students who average
3.79/4.0. The average GPA has increased for the
14 years of study from 3.67 to 3.86. - Average first year grade point average is higher
for students coming from private schools. - Average CEEB scores have decreased for the
duration of this study with the exception of the
English Achievement component. - Average CEEB scores were higher for all six
components for private school students.
13Comparison with USA Trends1
- The percentage of institutions for which high
school GPA or rank is very important has
increased steadily since 1979 - The percentage of institutions for which high
school GPA or rank is the single most important
factor has decreased steadily - Admission test scores show a steady increase as a
very important factor has increased steadily - California has recently proposed that aptitude
test scores be replaced by achievement test
scores
1 Taken from, Trends in College Admission 2000,
by Hunter Breland, James Maxey, Renee Gernand,
Tammie Cumming and Catherine Trapani. Can be
downloaded from the AIR site.
14Prediction Models
- Models were based on predicting the first year
grade point average based on the high school
great point average, and the five CEEB scores - Model
- 1st Year GPA f(GPA, Verbal Aptitude,
Mathematical Aptitude, English Achievement,
Mathematical Achievement, Spanish Achievement)
e
15Prediction Models
16Prediction Models
17Best Subsets Methods College of Engineering
Vars R-Sq(adj) Mallows C-p G P A A P T _ V E R B A P T _ M A T E A C H _ I N G A C H _ M A T A C H _ E S P
1 11.5 1743.4 X
2 19.5 618.1 X X
3 21.6 324.2 X X X
4 22.8 165.9 X X X X
5 23.7 37.5 X X X X X
6 23.9 7 X X X X X X
Actual 20.8 438.0 X X X
18Summary of comparison of models
- The model with three variables that best predicts
1st year GPA contains the following variables
High school GPA, Mathematical Achievement and
English Achievement. - In general, the analysis suggests that more than
three variables should be used in order to
improve the prediction ability (Cp). - It is necessary to incorporate other additional
variables in the model since the percentage of
the variability explained by the models is low
(but comparable to similar studies). For example,
the number of credits in key courses (e.g science
and math) taken in high school could be a
variable to be considered.
19Bibliography
- ASEE. (2004). Prism. Databytes. Page 24.
Summer. - ASEE. (2004). Prism. Databytes. Page 19.
December. - MINITAB Release 14. (2004). Minitab Inc. State
College, PA. - Montgomery, Douglas C., Peck, Elizabeth A., and
Vining, Geoffrey G. (2003). Introduction to
Linear Regression Analysis. Wiley and Sons, New
York. - Pike, Gary R. and Saupe, Joseph L. (2002). Does
High School Matter? An Analysis of Three Methods
of Predicting First-Year Grades. Research in
Higher Education. 43(2), pp. 187-207. - Wilson, Kenneth M. (1983). A Review of Research
on the Prediction of Academic Performance after
the Freshman Year. College Board Report No. 83-2.
20Acknowledgements
- The authors want to acknowledge the effort by
Leo I. Vélez and Irmannette Torres from the
Office of Institutional Research and Planning of
the University of Puerto Rico at Mayagüez for
providing and validating the data used in this
study.
21Additional information
- Contact us at
- antonio_at_uprm.edu
- davidg_at_ece.uprm.edu
- Download this presentation at
- http//oiip.uprm.edu/pres.html