Transcript Best Practices Conference - The University of Texas at San Antonio

Best Practices Conference
A Repeatable and Reproducible Approach for
Improving Retention and Graduation Rates of
Underrepresented Minorities and Women in EE
Southern Methodist University
February 28-29, 2008
Dallas, TX
Rolando Quintana & Mehdi Shadaram
University of Texas at San Antonio
Shaping the Technology of Tomorrow
Objectives of the Project
1. Increase the number of Hispanics, with an
emphasis on Hispanic females in the
Electrical Engineering workforce
2. Increase the undergraduate retention rate of
Hispanic EE students (supports objective 1)
3. Increase the number of Hispanic students
entering the EE discipline with active
recruiting strategies (supports objective 1).
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TETC Grant (A Holistic Approach)
H.S.
100
EGR 1303
70
EE 2513
53
Gatekeeper
CQI Feedback:
Grade
Student Evaluation
Faculty Evaluation
Advisory Board Evaluation
EE 2423
39
STA 3533
Key Course
Retention Feedback by Strata:
Gender
Ethnicity
32
EE 4813
Employer Survey
Advisory Board Survey
Faculty Survey
Performance on Rubrics
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Strategies
• Pre-College Activities
Science and Math Teachers
Students
Counselors
• “Just in Time Math” Course
• Key Courses
EE 1323 – Intro to EE profession
EE 4813 – Senior Design Project
• Gatekeeper Courses
EE 2423 Network Analysis
EE 2513 Logic Design
STA 3533 Probabilities and Statistics
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Strategies
•
Gate Keeper Course Intervention
–
–
•
Freshman Intervention
–
–
–
–
•
Pre-semester Workshop for Peer Facilitators
Visual Pedagogy
First and Second Semester Freshman EE
Classes and Laboratories
Visual Pedagogy
Filed Trips
Research Experience
Pre-College Activities
–
–
–
–
Teachers Workshop
Offering Double Credit Classes
EE Students Presentations in HS's (Senior
Projects)
Summer Research Camps
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Internet Structure
• a packet passes through many networks!
USA
local
ISP
Tier 3
ISP
Tier-2 ISP
local
ISP
local
ISP
local
ISP
Tier-2 ISP
Tier 1 ISP
Tier 1 ISP
Tier-2 ISP
local
local
ISP
ISP
NAP
Tier 1 ISP
Tier-2 ISP
local
ISP
Tier-2 ISP
local
ISP
China
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Using Bits to Store Samples: Quantization
Some common sampling rates for sound:
Human speech: 10,000 samples per
second
CD’s: 44,100 samples per second
Low quality audio: Less than 6,0008,000 samples per second
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Binomial Distribution (STA 3533)
• Binomial Distribution: A Bernoulli trial can result in a success with
probability p and a failure with probability q = 1 - p. Then the
probability distribution of the binomial random variable X, the
number of successes in n independent trials, is
 n  x n x
b (x; n, p) =   p q ,
 x
x = 0, 1, 2, . . . , n.
• Note that when n = 3 and p = 1/4 (as in the previous problem), the
probability distribution of X, the number of defectives, may be
written as
x = 0, 1, 2, 3.
x
1   3  1   3

b x;3,        

4   x  4   4 
3 x
,
Windows
Media A udio/Video fi
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Summer Activities for HS Students
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Summer 2007 Interns
120+ area HS
students applied for
participating in
research
laboratories in the
College of
Engineering
60 students were
selected
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Summer 2007 HS Students Survey
• 30 Seniors, 25 Juniors, and 5 Sophomores
• 75% Female, 77% Underrepresented
• After Summer, 90% of all showed interest in
engineering/science
• Before Summer, 65% showed interest in
engineering, after summer 83%
• 83% of HS graduates applied to at least one
college, majority got accepted
• UTSA was in the list of 80% of participants
Interested in Engineering/Science
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Teachers Workshop
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(Example) A Digital Image
• Matrix: An array of numbers
A
=
14 12
5
7
0
1
6
5
4
3
11 10
3 rows and
4 columns
• Elements: A(i,j) , i and j are integers
i denotes the Row index and j denotes the
Column index
– Examples: A(2,3) = 6, A(1,4) = 7, A(3,4) = 10
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Manipulation of a Digital Image
Brightness Mapping
k = 50
k = -50
B(i,j) = A(i,j) + k
k = constant
(expressed as a table)
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Manipulation of a Digital Image
Contrast Mapping
s>1
s<1
s > 1 and k < 0
s < 1 and k > 0
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Example: Contrast and Brightness
Higher
contrast
with lower
brightness
Higher
contrast
• Formula: B(i,j) = s • A(i,j) + k
• This is easy to do!
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Current Activities
• CPS-UTSA-SAISD Agreement (06-07)
Sam Houston HS
• CPS-UTSA-SAISD (Sam Houston HS)NEISD (Roosevelt HS)-ECISD (East
Central HS) 2007-2008
• PREP Program
• MOU with John Jay Science and
Engineering Academy
• MOU with NEISD T-STEM Program
• Alamo Texas Educators Association
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Results
Data for Students Taking the Old STA 3533 (Before Fall 2006)
Class Average
Pass Rates (“C” or better)
Mean
STDEV
EE 4653 Digital Comm.
72.3%
24.8
71%
EE 4613 Comm. Sys
70.6%
23.1
74%
Data for Students Taking the Revised Visual Pedagogy-Based STA 3533
(Fall 2006 and beyond)
Class Average
Pass Rates (“C” or better)
Mean
STDEV
EE 4653 Digital Comm.
78.6%
17.3
84%
EE 4613 Comm. Sys
79.1%
15.8
86%
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Results: Retention Rates
• Fall 2004 Cohort
First Year CoE
CE
60.0%
EE
55.6%
ME
59.4%
• Fall 2005 Cohort
First Year CoE
CE
57.8%
EE
64.5%
ME
60%
Second Year CoE
48.0%
25.9%
36.2%
First Year Overall
73.3%
79.0%
65.6%
Shaping the Technology of Tomorrow
Results: BS Degrees Confirmed
AY
06-07
CE
42
EE
98
ME
56
Total
196
05-06
04-05
03-04
02-03
01-02
00-01
48
30
29
23
33
38
65
83
80
61
47
46
51
49
46
39
33
21
164
162
155
123
113
105
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The Biggest Challenges
• Disseminating Information to area
schools
• Getting faculty to participate (mainly
during Summer)
• Getting approvals
• Data collection
• Motivating students
• Identifying the right instructor
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QUESTIONS?
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