SJSU Annual Program Assessment Form
Academic Year 2013-2014
Department: Industrial & Systems Engineering
Program: Industrial & systems Engineering
College: Engineering
Website: http://ise.sjsu.edu/
- Check here if your website addresses the University Learning Goals.
Program Accreditation (if any): None
Contact Person and Email: Minnie H. Patel Minnie.patel@sjsu.edu
Date of Report: March 1, 2014
Part A
1. List of Program Learning Outcomes (PLOs)
The student outcomes of the master’s degree in ISE are:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Student will be able to function effectively and provide leadership within an organization.
Student will be able to facilitate and participate in teams.
Student will be able to understand organizational processes and behaviors.
Student will have knowledge of methodological and computational skills with which to operate
effectively
Student will be able to collect, analyze, and interpret data
Student will be able to approach unstructured problems and synthesize and design solutions for
this problem
Student will be able to evaluate the impact of these solutions in the broader context of the
organization and society
Student will be able to effectively present and sell solutions in the form of written, oral and
electronic media
Student will be able to accomplish life-long growth within the field of profession of ISE
6. Able to approach and solve
unstructured problems
7. Evaluate the impact of
solutions in broader context
8. Effectively present and sell
solutions
9. Life-long growth within the
ISE field
used to create or interpret the map.>
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Social and Global Responsibilities
Applied Knowledge
X
Intellectual Skills
Broad Integrative knowledge
PLO/ULG
1. Function effectively and
provide leadership
2. Facilitate and participate in
teams
3. Understand organizational
processes and behaviors
4. Knowledge of methodological
and computational skills
5. Collect, analyze, and interpret
data
Specialized knowledge
2. Map of PLOs to University Learning Goals (ULGs)
X
X
X
X
X
X
X
ocess
3. Alignment – Matrix of PLOs to Courses
Matrix mapping of course topics to Program Learning Outcomes
Table 3.2 – ISE Program – Outcome Mapping Matrix
Outcome Mapping Matrix – 2010/11
Program
Outcome:
1
2
3
4
5
6
X
X
X
X
7
8
9
Required Courses (Engineering Core)
ISE 130
ISE 140
X
X
X
X
X
X
X
ISE 167
X
X
X
X
X
X
X
X
X
X
ISE 200
X
ISE 230
X
X
ISE 235
X
X
X
X
X
X
X
X
X
X
Specialty Area 1 : Production and Quality Assurance (Four out of Six Courses)
ISE 202
X
X
ISE 241
X
X
X
X
X
X
X
X
X
X
X
ISE 245
X
X
X
X
ISE 250
X
X
X
X
X
X
X
X
X
ISE 251
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
ISE 265
Specialty Area 2: Supply Chain Engineering (Four out of Seven Courses)
ISE 245
X
X
X
X
X
X
X
X
X
X
X
X
X
REQUIRED
ISE 241
X
REQUIRED
ISE 247
X
X
X
Program
Outcome:
1
2
3
4
5
6
7
8
9
ISE 250
X
X
X
X
X
X
X
X
X
ISE 251
X
X
X
X
X
X
X
X
X
ISE 265
X
X
X
X
X
X
X
ISE 270
X
X
X
X
X
X
Specialty Area 3: System and Information and Modeling (Four out of Six Courses)
ISE 222
X
ISE 241
X
ISE 242
X
X
X
X
X
ISE 245
X
X
X
ISE 265
X
X
X
ISE 270
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Specialty Area 4: Human Factors (Four out of Six Courses)
ISE 210
X
X
X
X
X
X
X
REQUIRED
ISE 202
X
X
X
ISE 212
X
X
X
X
X
X
ISE 215
X
X
X
X
X
X
ISE 217
X
X
X
X
X
X
ISE 219
X
X
X
X
X
X
X
X
Specialty Area 5: Service Systems Engineering (Four out of Six Courses)
ISE 242
X
X
X
X
X
X
X
X
X
X
REQUIRED
BUS 297D
REQUIRED
Program
Outcome:
1
ISE 265
ISE 250
X
2
3
4
5
6
X
X
X
X
X
X
X
X
X
X
ISE 222
X
ISE 270
X
X
X
7
X
8
9
X
X
X
X
X
X
X
X
X
X
Capstone Courses
ISE 298
X
X
X
X
X
X
X
X
X
ISE 299
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
ISE 245
X
X
X
X
X
X
X
ISE 247
X
X
X
X
X
X
X
Elective Courses
ISE 202
ISE 251
X
+ Skill level 1 or 2 in Bloom’s Taxonomy ++
 Skills relevant but not presently assessed
Skill level 3 or 4 in Bloom’s Taxonomy
X
+++
Skill level 5 or 6 in Bloom’s Taxonomy
The Outcome Mapping Matrix in Table 3.2 above indicates across the ISE curriculum, each outcome
is addressed many times at all levels of Bloom’s Taxonomy. The table also points out the
contributions of the Engineering Core and Technical Writing course to the achievement of Student
Outcomes
4. Planning – Assessment Schedule
We assess all the program learning outcomes every two years. The first time these outcomes were
assessed was in Fall 2012 and then in Spring 2013. Our assessment cycle for program learning
outcomes is two-year long, with the first year consisting of collection and analysis of data and the
second year of the cycle consisting of implementation of the recommendations based on the
analysis results obtained from the previous year of the cycle.
Performance measure: 80% of the students score 80% or above.
Table 4.1 Program Learning Outcome Assessment Schedule
Performance
MS-ISE Outcome
Course
Criteria
1
2
3
4
5
Function
effectively and
provide
leadership within
organization.
Facilitate and
participate in
teams.
Understand
organizational
processes and
behaviors.
Collect, analyze,
and interpret
data.
Approach
unstructured
problems and
synthesize and
Spring
Fall
Develop a lean solution for
an organization to improve
productivity
ISE251
Develop a DMAIC solution
ISE 250
X
Assessment from team
members
of
student
participation
on
final
project
ISE250
X
Assessment from team
members
of
student
participation
on
final
project
ISE 202
X
Perform a DMAIC study for
an organization
ISE 250
X
Supply
chain
analysis
business operations
ISE 245
Collect necessary financial
data and analyze them to
assess profitability, financial
position, and cash flow
generation
ISE 200
Acquire statistical models
and techniques developed
for assuring quality of
enterprise products and
operations.
ISE235
X
Formulate a quantitative
problem
in
existing
frameworks.
ISE230
X
X
X
X
design solutions
for these
problems.
6
Evaluate the
impact of these
solutions in the
broader context
of organization
and society.
Formulate and analyze a
problem using a fault tree
diagram
ISE235
Evaluation of investment
alternatives using financial
and non-financial factors
ISE200
Evaluation of impact of
supply chain on society and
environment
ISE 245
X
X
X
7
Effectively
present and sell
solutions in the
form of written,
oral and
electronic data.
Develop a solution for a
complex ISE problem
ISE 298
X
8
Operate the
organization
effectively and
efficiently by
applying
knowledge and
computational
skills acquired in
the program.
Acquire
mathematical
models and techniques
developed for optimizing
efficiency of enterprise
operations.
ISE230
X
Acquire statistical models
and techniques developed
for assuring quality of
enterprise products and
operations.
ISE235
X
Explain why a particular
methodology works.
ISE230
X
9
Accomplish lifelong growth
within the
X
field/profession
of ISE.
Explain
how
statistical
process control works
ISE235
X
Solve Complex ISE problems
ISE 298
X
X
5. Student Experience
The PLOs are posted on the ISE webpage. Here is the link http://ise.sjsu.edu/content/bs-ise-studentoutcomes. The students’ feedback is considered in defining and improving program objectives via
alumni survey. The program learning outcomes are then revised accordingly since they map to
program objectives. Thus students’ feedback is considered indirectly.
Part B
6. Graduation Rates for Total, Non URM and URM students (per program and degree)
First-time Freshmen: 6
Year Graduation Rates
Academic Programs
Industrial/Syst.Engineering
New UG Transfers: 3 Year
Graduation Rates
Fall 2007 Cohort
Grads : 3 Year
Graduation Rates
Fall 2010 Cohort
Fall 2010 Cohort
Entering
% Grad
Entering
% Grad
Entering
% Grad
Total
2
50.0%
12
25.0%
50
64.0%
URM
1
0.0%
8
37.5%
3
33.3%
Non-URM
0
0.0%
3
0.0%
23
43.5%
Other
1
100.0%
1
0.0%
24
87.5%
7. Headcounts of program majors and new students (per program and degree)
Fall 2013
New Students
Industrial/Syst Engineering
Degree
Cont. Students
Total
1st Fr.
UG Transf
New Creds
1st Grads
UGs
Creds
Grads
UGs
Creds
Grads
Total
8
11
0
56
101
0
108
120
0
164
BS
8
11
0
0
101
0
0
120
0
0
MS
0
0
0
56
0
0
108
0
0
164
8. SFR and average section size (per program)
Fall 2013
Course Prefix
Course Level
ISE - Industrial/Syst Engineer
Total
Student to
Average
Faculty Ratio Headcount per
(SFR)
Section
31.0
30.1
Upper Division
37.4
41.9
Graduate Division
25.3
21.3
9. Percentage of tenured/tenure-track instructional faculty (per department)
Fall 2013
Industrial & Systems Engineering
% Tenured/Prob
Tenured
49.5%
2.885
Probationary Temp Lecturer
2.941
0
Part C
10. Closing the Loop/Recommended Actions
The following actions have been implemented in Fall 2013
1. In Fall 2013, failure rate calculations were emphasized and explained clearly in ISE 235.
Statistical process control was explained and number of homework problems to improve
students’ skills in interpretation and construction were presented in the class.
2. In Fall 2013, more time was spent on explaining utility theory in ISE 230. Also, an embedded
Markov chain approach to queuing theory was explained in terms of how and why it works.
3. In Fall 2013, many integer programming formulations were discussed to clear doubts of the
students regarding the subject matter and methodologies to solve these problems were
explained to help student learn the material in ISE 230.
11. Assessment Data
Table 11.1 summarizes the data collected and assessment tool used
Performance measure: 80% of the students scored 80% or above.
Table 11.1 Data collected and Assessment Methods Used (Fall 2012 and Spring 2013)
Data Collected in Fall 2012 and Spring 2013
MS-ISE Outcome
Performance
Criteria
Course
Assessment
Method
Instructor
1
Function
effectively and
provide
leadership within
organization.
Develop a lean solution for
an organization to improve
productivity
ISE251
Final Project
100% of the
students scored
80% or above
on Final Project
2
Form, facilitate,
lead, and
coordinate and
participate in
teams.
Assessment from team
members
of
student
participation
on
final
project
ISE250
Final Project
93% of the
students rated
4 or above on a
scale of 1 to 5
(1 poor to 5
excellent)
on
participation
3
Understand
organizational
processes and
behaviors.
Perform a DMAIC study for
an organization
ISE 250
Green
Belt
Certification
100% of the
students scored
80% or above
4
Collect, analyze,
and interpret
data.
Collect necessary financial
data and analyze them to
assess profitability, financial
position, and cash flow
generation
ISE 200
Case Study 1
98% of the
students scored
80% or above
Acquire statistical models
and techniques developed
for assuring quality of
enterprise products and
operations.
ISE235
Test #2 Q1 on
Statistical
Process
Control (SPC)
84.9% of the
students scored
80% or above
on Q1, Test 2
ISE235
Test #2 Q2 on
Statistical
Process
Control (SPC)
83% of the
students scored
80% or above
on Q2, Test 2
ISE235
Test #3 Q5 on
failure
rate
estimation
62.7% of the
students scored
80% or above
on Q5, Test 3
ISE230
Test #1 Q4 on
formulation of
a problem as
an
integer
program
70.5% of the
students scored
80% or above
on Q4, Test 1
ISE230
Test #2 Q3 on
formulation of
a problem as a
Markov Chain
and
a
Queueing
System
88.4% of the
students scored
80% or above
on Q3, Test 2
ISE235
Test #3 Q1 on
reliability
82.4% of the
students scored
5
Approach
unstructured
problems and
synthesize and
design solutions
for these
problems.
Formulate a quantitative
problem
in
existing
frameworks.
block diagram
80% or above
on Q1, Test 3
ISE235
Test #3 Q2 on
fault
tree
diagram and
analysis
86.3% of the
students scored
80% or above
on Q2, Test 3
6
Evaluate the
impact of these
solutions in the
broader context
of organization
and society.
Evaluation of investment
alternatives using financial
and non-financial factors
ISE200
Case study 2
98% of the
students scored
80% or above
on a case study
7
Effectively
present and sell
solutions in the
form of written,
oral and
electronic data.
Develop a solution for a
complex ISE problem
ISE 298
Final Project
100% of the
students scored
a passing grade
8
Operate the
organization
effectively and
efficiently by
applying
knowledge and
computational
skills acquired in
the program.
Acquire
mathematical
models and techniques
developed for optimizing
efficiency of enterprise
operations.
ISE230
Test #1 Q6 on
Integer
Programming
75% of the
students scored
80% or above
on Q6, Test 1
ISE230
Test #2 Q1 on
Utility Theory
74.4% of the
students scored
80% or above
on Q1, Test 2
ISE235
Test #2 Q1 on
Statistical
Process
Control (SPC)
84.9% of the
students scored
80% or above
on Q1, Test 2
ISE235
Test #2 Q2 on
Statistical
83% of the
students scored
Acquire statistical models
and techniques developed
for assuring quality of
enterprise products and
operations.
9
Accomplish lifelong growth
within the
field/profession
of ISE.
Process
Control (SPC)
80% or above
on Q2, Test 2
ISE235
Test #2 Q4 on
Acceptance
Sampling
100% of the
students scored
80% or above
on Q4, Test 2
ISE235
Test #2 Q5 on
Acceptance
Sampling
84.9% of the
students scored
80% or above
on Q5, Test 2
ISE235
Test #3 Q3 on
reliability
calculation
76.5% of the
students scored
80% or above
on Q3, Test 3
ISE235
Test #3 Q4 on
fault
tree
analysis
84.3% of the
students scored
80% or above
on Q4, Test 3
Explain why a particular
methodology works.
ISE230
Test #2 Q6 on
why
the
Embedded
Markov Chain
approach to
Queueing
Theory work?
37.2% of the
students scored
80% or above
on Q6, Test #2
Explain
why
statistical
process control tools work
ISE235
Test #2 Q7 on
Statistical
Process
Control
49.1% of the
students scored
80% or above
on Q7, Test #2
Develop a solution for a
complex ISE problem
ISE 298
Final Project
100% of the
students scored
a passing grade
12. Analysis
Referring to Table 11.1, it is clear that the student learning outcomes 4, 5, 8, and 9 are partially
achieved in terms of some of their performance criteria were not achieved at the desired level,
whereas the program learning outcome i was not achieved. Bothe performance criteria were not
achieved for program outcome 9. However, in ISE 298 course, the students work on new systems
and learn new areas of the industrial and systems engineering discipline. The students do get
passing grade in the final projects where they solve complex problems often involving new scenarios
and adapting methodologies learned in the classes. In this sense, students are successful in life-long
growth within the industrial and systems engineering field. Most of the projects are undertaken by
the students during their college practical training while working with their employers in analyzing
and solving problems they currently face. Often students work on lean six sigma and supply chain
analysis projects.
13. Proposed changes and goals (if any)
For assessing program learning outcome 2, a performance criterion was added in spring 2014 and it
will be assessed using ISE 202 course. This course is a very popular elective course of the program.
The department faculty felt that this course should be included in the assessment matrix.
For assessment of program learning outcome 3, we added ISE 245 course in spring 2014 since a
number of students gets jobs in this course subject matter area and is important and popular course
in the program.
For assessment of program learning outcome 6, we added ISE 245 course in spring 2014 since a
number of students gets jobs in this course subject matter area and is important and popular course
in the program.
The above listed program criteria will be assessed in the next cycle staring fall 2014.