
SJSU Annual Program Assessment Form
Academic Year 2013-2014
Department: Computer Science
Program: BS in Computer Science (BSCS) and MS in Computer Science(MSCS)
College: Science
Website: http://cs.sjsu.edu/
x Check here if your website addresses the University Learning Goals.
http://www.sjsu.edu/cs/assessment/bscs/ugoal/
Program Accreditation (if any): ABET accredited
Contact Person and Email: Chris Tseng, chris.tseng@sjsu.edu
Date of Report: May 31, 2014
Part A
1. List of Program Learning Outcomes (PLOs)
List of PLOs for BSCS
(a) An ability to apply knowledge of computing and mathematics to solve problems
(b) An ability to analyze a problem, and identify and define the computing requirements appropriate
to its solution
(c) An ability to design, implement, and evaluate a computer-based system, process, component, or
program to meet desired needs
(d) An ability to function effectively on teams to accomplish a common goal
(e) An understanding of professional, ethical, legal, security and social issues and responsibilities
(f) An ability to communicate effectively with a range of audiences
(g) An ability to analyze the local and global impact of computing on individuals, organizations, and
society
(h) Recognition of the need for and an ability to engage in continuing professional development
(i) An ability to use current techniques, skills, and tools necessary for computing practice
(j) An ability to apply mathematical foundations, algorithmic principles, and computer science
theory in the modeling and design of computer-based systems in a way that demonstrates
comprehension of the tradeoffs involved in design choices
(k) An ability to apply design and development principles in the construction of software systems of
varying complexity
List of PLOs for MSCS:
http://www.sjsu.edu/cs/assessment/mscs/objectives/index.html
Outcomes
Upon graduation a student should have acquired:
MSCS.OC1
Breadth of knowledge in computer science
MSCS.OC2
Depth of knowledge in an advanced topic in computer science
MSCS.OC3
Technical communication skills
Decision on PLO content
The department faculty proposed and approved the standard PLOs recommended by ABET.
Criteria for assessing levels of mastery
Each PLO is assessed by a set of related courses. Each course is designed to achieve a set of
performance indicators. Each performance indicator supports progress towards one or more PLOs.
A set of rubrics is established for the assessment of each performance indicator. Each rubric
consists of 3 achievement levels. Thus, a set of rubrics defines the criteria for assessing levels of
mastery of each PLO.
2. Map of PLOs to University Learning Goals (ULGs)
PLO/ULG
Specialized
Knowledge
BSCS PLOs to ULGs map
Broad Integrative Intellectual
Knowledge
Skills
Applied
Knowledge
(a)
X
X
(b)
(c)
(d)
X
X
X
X
X
(e)
X
Social and Global
Responsibilities
X
(f)
(g)
X
(h)
(i)
(j)
(k)
X
X
X
X
X
X
X
X
X
X
X
PLO/ULG
Specialized
Knowledge
Broad Integrative
Knowledge
MSCS.OC1
Intellectual
Skills
Applied
Knowledge
X
MSCS.OC2
MSCS.OC3
Social and Global
Responsibilities
X
X
X
X
X
MSCS PLOs to ULGs map
3. Alignment – Matrix of PLOs to Courses
BSCS Outcomes
Courses
Support Courses
Math
(a)
1
Physics
1
Science
1
(b)
1
(c)
CS 100W
(d)
2
Phil 134
(f)
(g)
3
3
1
C
2
(h)
(i)
(j)
(k)
1
3
A
2
D
1
2
1
E
1
2
1
R
1
2
2
S
1
2
2
1
V
CS 46A
1
2
2
1
1
1
1
1
1
1
CS 46B
1
1
1
1
1
1
CS 146
3
2
2
2
3
2
CS 151
2
3
3
2
2
3
CS 47
1
1
1
1
1
CS 49C/J
1
1
1
1
1
CS 147
2
2
2
2
2
CS 149
2
2
2
2
2
2
CS 152
2
3
3
2
2
3
CS 154
3
2
2
3
CS 160
3
3
3
3
3
3
DEEP
3
3
3
3
3
3
GE Courses
Required CS Courses
(e)
3
3
3
3
1
4 Electives
CS X
E
E
E
E
E
E
Matrix of PLOs to Courses in BSCS
1: Indicating Beginner level, 2: Intermediate level, 3: Advanced level
x: not assessed in this report
4. Planning – Assessment Schedule
Course
CS 100W
CS 146
CS 151
CS 160
Course
OC1
OC2
OC3
S12
F12
S13
X
Assessment Semester
F13
S14
F14
X
S15
X
X
X
F12
X
X
S16
X
X
X
BSCS Assessment Schedule
S12
F15
Assessment Semester
F13
S14
F14
X
X
X
MSCS Assessment Schedule
S13
X
S15
F15
X
S16
X
5. Student Experience
University Learning Goal for BS and MS can be found under the following website:
http://www.sjsu.edu/cs/assessment/bscs/ugoal/
BSCS PLOs and ULGs are posted at the website:
http://www.sjsu.edu/cs/assessment/bscs/outcomes/
http://www.sjsu.edu/cs/assessment/bscs/ugoal/matrix/
PLOs are included in syllabi
Annual alumni survey is used to provide feedback to PLOs for the consideration of enhancements
MSCS PLOs are ULGs are posted at the website:
http://www.sjsu.edu/cs/assessment/mscs/objectives/index.html
MCSC Outcomes:
Upon graduation a student should have acquired:
MSCS.OC1
E
Breadth of knowledge in computer science
MSCS.OC2
Depth of knowledge in an advanced topic in computer science
MSCS.OC3
Technical communication skills
Part B
6. Graduation Rates for Total, Non URM and URM students (per program and degree)
The following table summarizes the graduate rate based on 6 years of data for those who started in Fall
2007.
6 Yr
All
URM
Total
42.2%
0.0%
First-time Freshmen
Non-URM
42.5%
6 Yr
Total
All
URM
Non-URM
55.8%
66.7%
63.6%
Transfers
7. Headcounts of program majors and new students (per program and degree)
Headcount of majors by major and concentration in recent semesters is as summarized below.
Headcount
Fall 2013
Spring 2014
F
M
Total
F
M
Total
Computer
4
48
52
0
1
1
Science
Total
4
48
52
0
1
1
The number of students entering the program under Applied, Admitted, and Enrolled for recent
semesters is summarized below.
Headcount
Fall 2013
Applied
Admitted
Enrolled
Indicator
Indicator
Indicator
First-time Freshman
741
425
51
New Undergraduate
410
125
44
Transfer
First-time Graduate
872
114
52
Total
2,023
664
147
Headcount
Spring 2014
Applied
Admitted
Enrolled
First-time Freshman
New Undergraduate Transfer
First-time Graduate
Total
Indicator
18
140
527
685
Indicator
4
74
120
198
Indicator
1
41
76
118
Our enrollment trend shows a matching demand for our major as tied to the hi-tech industry economy.
After the decline in the last few years during the economic down turn, both our undergraduate and
graduate enrollment have been holding steady or improving. This is evidenced by the enrollment trend
figures as shown below.
60
90
60
40
30
20
0
0
Fall
2009
Fall
2010
Fall
2011
Fall
2012
Fall
2009
Fall
2013
First-time Freshman Fall 2009 – 2013
Fall
2010
Fall
2011
Fall
2012
Fall
2013
New Undergraduate Transfer Fall 2009 – 2013
200
60
150
40
100
20
50
0
Fall
2009
Fall
2010
Fall
2011
Fall
2012
0
Fall
2013
Fall
2009
First-time Graduate Fall 2009 – 2013
Fall
2010
Fall
2011
Fall
2012
Fall
2013
Total headcount Fall 2009 – 2013
The enrolled Full Time Equivalent Graduate (MSCS) Students in recent years is as shown below.
Graduates
(MSCS)
Fall 2009
96.75
Fall 2010
103.67
Fall 2011
70.92
Fall 2012
75.08
120.00
90.00
60.00
30.00
0.00
Fall 2009 Fall 2010 Fall 2011 Fall 2012 Fall 2013
Fall 2013
76.50
8. SFR and average section size (per program)
SFR
Fall 2013
Lower Division
46.0
Upper Division
24.6
Graduate Division 8.8
Total
21.1
Student to Faculty Ratio (SFR)
Average Section Size
Lower Division
Upper Division
Graduate Division
All Level
Average section sizes
Fall 2013
54.6
23.5
6.9
19.6
The SFR and average headcount of our program as compared to other departments in the same college
and that in College of Engineering are summarized in the 2 tables below.
Department
Lower Division
Upper Division
Graduate Total
CS
46
24.6
8.8
54.8
CMPE
23.1
25.8
46.2
95.1
ENGR (college)
26.6
16.4
15.2
58.2
EE
45.4
22.9
31.5
99.8
Student to Faculty Ratio (SFR) as compared with other departments and college
Student College
Lower Division
Upper Division Graduate Total
CS
54.6
23.5
6.9
85
CMPE
45.2
31.2
33.5
109.9
ENGR
51.8
21.8
13.7
87.3
EE
39.4
37.8
32
109.2
Average headcount as compared with other departments and college
9. Percentage of tenured/tenure-track instructional faculty (per department)
The percentage of tenured/tenure-track instructional faculty in Fall 2013 is 64% and in Spring 2014
is 57%
FTEF
2013/2014
Fall 2013
Spring 2014
Avg
Tenured
10.5 (56%)
8.7(47%)
9.6 (52%)
Probationary
1.5(8%)
1.8 (10%)
1.7(10%)
Temp Lecturer
6.7(36%)
8.1 (43%)
7.4 (38%)
Total
18.6
18.7
18.6
Part C
Closing the Loop/Recommended Actions
Outcomes a, b, and j were re-assessed in Spring 2013 to determine if changes recommended by earlier
OARs were effective.
Closing the Loop: Outcome b
Outcome b states that graduates should have the ability to analyze a problem, and identify and define
the computing requirements appropriate to its solution. According to the assessment matrix in section 3,
this outcome is enabled by several courses at various levels. CS151, Object-Oriented Design, enables the
outcome at the advanced level and is assessed every two years.
The enablement was assessed in the Fall 2012 semester. The Fall 2012 OAR (Outcome Assessment
Report) raised concerns over the percentage of students who performed below the satisfactory level on
both indicators (26.6% for indicator 1 and 33.3% for indicator 2).
The OAR concurred with the analysis and recommendations made by the CS 151 course coordinator
(who is also the instructor) in the corresponding CAR. The course coordinator proposed more practice
selecting patterns without a list of choices.
The recommended pedagogical changes were made and the enablement was reassessed in the Spring
2013 semester. The Spring 2013 OAR indicates that the percentage of students performing below the
satisfactory level in both indicators has dropped to 13%.
Closing the Loop: Outcomes a and j
According to the assessment matrix in section 3, these outcomes are enabled by several courses at
various levels. CS146, Algorithms and Data Structures, enables both outcomes at the advanced level and
is assessed every two years.
Both enablements were assessed in the Spring 2012 semester. The Spring 2012 OAR (Outcome
Assessment Report) raised several concerns:
The report concurred with the analyses and recommendations made by the course coordinator in the
corresponding CAR. The recommended pedagogical changes were made and the enablement was
reassessed in the Spring 2013 semester.
10. Assessment Data
Each of PLO is assessed by one upper division course. Each of these assessed courses defines a set
of Course Learning Objectives (CLOs) or performance indicators. A set of rubrics is established for
the assessment of each CLO. According to the assessment schedule in Section 4, the course
instructor generates a Course Assessment Report (CAR). The rubrics, the associated CLOs and PLOs
are presented in CARs. The data presented in CARs for each course are used to produce the
Outcome Assessment Report (OAR) every two years. The OARs collectively address achievement of
PLOs and also recommend actions. The CARs generated for the latest assessment cycle are attached
as appendices.
11. Analysis
Based on the data and summary of the CARs, all 11 PLOs have been achieved. As shown in Section
10, the majority of the actions recommended during last assessment cycle have been implemented.
The changes proposed during the last assessment cycle are listed in Section 13. These proposed
changes will be evaluated and prioritized for the implementation in the coming academic year.
12. Proposed changes and goals (if any)
In order to enhance students to achieve PLOs and improve the assessment process, changes have
been proposed at the course level. The changes were summarized as follows.
In the assessment of Outcome J in CS 146, Performance Indicator 2 was proposed to be changed
from "Given pseudocode of two algorithms (eg. sort), describe most suitable data structure to use"
to "Given pseudocode of two algorithms (eg. sort), analyze which is more efficient." This change was
made by consensus among the instructors and Course Coordinator of CS 146, as well as the
Assessment Coordinator, who all believe that the original statement was confusing, and the new
statement makes much better sense.