Transcript Quality Control Tools

Quality Function Deployment for
Designing a Course
By
S. O. Duffuaa, U. Al-Turki and
M. Hawsawi
Presentation Plan
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Introduction
Literature review
Paper objectives
Problem statement
Quality function deployment
Application of QFD for designing
statistics course
Conclusion and further research
Introduction
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
Academic programs are one of the main
ingredient in quality of graduates
Programs are drastically affected by courses
design
Courses design is essential element for
building quality academic programs
Introduction
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Course design is usually made by intuition
and experience
Courses delivery is based on experience and
ad hoc consultation
Industry/employers are usually consulted in
programs design, but rarely in course design
Students input is rarely thought in the
process of course delivery
A need exist to systematize the process of
course design and delivery
Literature
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Literature will be confined to the design and
delivery of basic statistics courses
Molinero advocates teaching philosophical
and conceptual aspects of statistics to OR
and MS students
Hogg, Khamis provide suggestions on how
to teach a basic statistics course
Macnaughton outlines goals for an
introductory course
Literature

QFD has been used in designing ME
programs
Problem Statement
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Experience has shown in our department that
our students are having problems in
understanding and retaining the basic
probability and statistics concepts
The concepts in basic statistics are necessary
for them to succeed in advance level courses
These concept are essential for their success
as industrial engineers
Objectives

To enhance the design and delivery of a
basic statistics course with the following
aims:
 To meet industrial needs for basic
statistics
 To improve students learning and aid them
in retaining the probability and statistics
concepts
Approach


Use the methodology of quality function
deployment (QFD) to design and deliver this
basic course
QFD is a planning technique that is born in
Japan as a strategy for assuring that quality is
built into new processes. It helps
organization to take the voice of the
customer and factor their wants and needs
into organization product and process
planning
Quality Function Deployment
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QFD uses matrices to help organization
satisfy customer requirements
The Most important matrix is the house of
quality (HOQ) that consists of several submatrices
Other matrices are the process planning
matrix and the design concept evaluation
External and Internal Customers
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Employers/Organization are used as
external customers to specify their needs
Students are used as external customers to
determine delivery requirements
Faculty are used as designers for the course
technical requirements
Customer requirements

The employers/organizations have identified
the following topics are the most important
to them:
 Summarization of data
 Estimation of parameters
 Test of hypothesis
 Distribution identification
 Knowledge of statistics software
Students Technical Requirements
1. Knowledgeable and experienced faculty
members.
2. Communicate well and write excellent notes.
3. Faculty members who solve homework
problems and examples.
4. Small class size.
5. Textbook with simple language, clearly
organized, and contains many examples.
6. Statistical package use.
Technical Requirements
The following requirements are identified to be of
most importance by the faculty:
•
•
•
•
•
Syllabus
Student preparation
Faculty
Teaching methods
Class size
Table 1 levels of the syllabus
Sub-requirement
Level 1
Level 2
Level 3
Level 4
Level 5
1. Descriptive Statistics
Available
Available
Available
Available
Available
2. Basics of probability
Available
Available
Available
Available
Available
3. Random Variables
Available
Available
Available
Available
Available
4. Sampling Distribution
Available
Available
Not Available
Available
Available
5. Estimation
Available
Available
Available
Not Available
Available
6. Test of Hypothesis
Available
Available
Available
Available
Not Availab
7. Statistical Package Use
Available
Not Available
Available
Available
Available
Table 2 Levels of prerequisites
Sub-requirement
Level 1
Level 2
Level 3
1. Calculus
Available
Available
Not Available
2.College
Algebra
Available
Not Available
Not Available
Table 3 levels of grade in prerequisites
Sub-requirement
Average
grade
Perquisites (G)
in
Level
1
Level
2
Level
3
Level
4
G>B
G=C
G<C
B  G
and
G >C
Table 4 Faculty levels
Levels
Education
Level 1
Level 2
Level 3
Level 4
Level 5
Level 6
Level 7
Level 8
Level 9
Level 10
Level 11
Level 12
Level 13
Level 14
Level 15
Level 16
Level 17
Level 18
Level 19
Level 20
Ph.D
Ph.D
Ph.D
Ph.D
Ph.D
Ph.D
Ph.D
Ph.D
Ph.D
MS.
MS.
MS.
MS.
MS.
MS.
MS.
MS.
MS.
MS.
MS.
Years of
Experience
10
10
10
 5 and < 10
 5 and < 10
 5 and < 10
<5
<5
10
10
10
10
 5 and < 10
 5 and < 10
 5 and < 10
<5
<5
<5
<5
<5
Communication Skills
E
VG
G
E
VG
G
E
VG
G
E
VG
G
E
VG
G
E
VG
G
E
VG
Table 5 Levels of teaching methods
Sub-requirement
Level 1
1. Clear Presentation
Available
2. Excellent Notes
Level 2
Level 3
Level 4
Level 5
Available
Available
Available
Available
Available
Available
Available
Available
Available
3. Using of educational
notes
Available
Available
Not
Available
Available
Available
4. Relating Topics to
Real Life
Available
Available
Available
Not
Available
Available
5. Solving Examples
Available
Available
Available
Available
Not
Available
6.Assigning Homework
and Quizzes
Available
Available
Available
Not
Available
Available
7. Reporting Progress to
Students
Available
Not
Available
Available
Available
Available
Table 6 Level of class size
Sub-requirement
1. Class Size (CS)
Level 1
Level 2
Level 3
Level 4
CS ≤ 20
20 <CS ≤ 30
30< CS ≤ 40
CS > 40

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

 O
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9 9 8 7 6 7.6
7
5
4.8
5
4
8
O
O
O















O
O
O






7
Poor
Excellent










Excellent communication skills




O




O
Study habit




O


O

O
Gained grades in the prerequisites










College algebra









O
Calculus and college algebra
Many years of experience
Current practice









O

O



O




      
7 9
Faculty
Ph.D in statistics or related
fields
8
Class
size
 
O O
 
 
 
 
 
 
 
O O
O


O






Test of hypothesis
O

O
O






Statistical Package use

O
O


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



Estimation
1
2
3
4
5
6
7
8
9
1
0
1
1
Sampling Distribution
Basics of Statistics
9
7
3
6
7
8
9
8
8
8
Random Variables
Descriptive Statistics
Knowledgeable faculty
Communication and excellent notes
Solve homework problems
Small size class
Simple and clearly organized
textbook& examples
6. Statistical software use
Row#
1.
2.
3.
4.
5.
Rating
Company Response
Student Response
1.
2.
3.
4.
5.
Customer Requirements
Summarization of Data
Estimation of parameters
Test of Hypothesis
Distribution identification
Knowledge of Statistical software
Stud.
Prep.
Good
Prerequisite
Syllabus
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Design Concepts
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A design concept is a selection of a level
from the technical requirements to come up
with a design that best satisfies companies
and student’s requirements. As an example,
a design concept can have a first level
syllabus, second level student preparation,
third level of pre-requisite, sixth level of
faculty, first level of teaching method and a
second level of class size.
Table 8 Course design concepts
Design concepts
Requirements
1
2
3
4
5
6
7
8
9
10
11
*
Syllabus level
1
2
3
4
5
1
2
3
4
5
2
Student
preparation
level
1
2
3
4
1
2
3
4
1
2
4
Prerequisite
level
1
2
3
4
2
3
1
2
3
1
1
Faculty level
1
2
3
4
5
6
7
8
9
10
1
Teaching
methods level
1
2
3
4
5
1
2
3
4
5
1
Class
level
1
2
3
4
1
2
3
4
1
2
4
size
Concept 1
Concept 2
Concept 3
Concept 4
Concept 5
Concept 6
Concept 7
Concept 8
Concept 9
Concept 10
Source
of
Require
ments
Concept 11
Current Practice
Table 9 Design concepts evaluation
Syllabus
+
S
-
-
-
+
S
-
-
-
Student
preparation
Perquisites
Faculty
Teaching
Methods
Class size
+
S
+
+
+
S
+
+
+
S
+
+
S
S
S
-
-
S
-
-
S
S
-
-
-
S
-
+
3
3
0
+
2
1
3
+
2
0
4
S
0
3
3
+
2
0
4
+
3
1
2
+
2
2
2
S
0
2
4
+
2
0
4
+
2
1
3
Concept
Requirements
Companies
Students
and
faculty
Totals
-
Conclusion and Further Research
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QFD is an effective tool for designing and
delivering courses.
It matches customer requirements with
technical requirements.
The use of QFD provides a better
understanding of the course design process.
The new course design is a balanced one.
Conclusion and Further Research
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More work could be done to identify more
design concepts for evaluation.
AHP or a more sophisticated evaluation
process can be used to evaluate resulting
design concepts.
An awareness program must be launched
before applying QFD in process, product or
service design.
Thank you.
Any Questions
or Comments?