Presentation Plan
Introduction Literature review Paper objectives Problem statement Quality function deployment Application of QFD for designing
statistics course Conclusion and further research
Introduction
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
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
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
Problem Statement
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
QFD uses matrices to help organization satisfy customer requirements
The Most important matrix is the house of quality (HOQ) that consists of several sub-matrices
Other matrices are the process planning matrix and the design concept evaluation
External and Internal Customers
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 syllabusSub-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 Available
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 Level 1
Level 2
Level 3
Level 4
Average grade in Perquisites (G)
G>B G=C G < C B G and G >C
Levels Education Years of Experience
Communication Skills
Level 1 Ph.D 10 E
Level 2 Ph.D 10 VG
Level 3 Ph.D 10 G
Level 4 Ph.D 5 and < 10 E
Level 5 Ph.D 5 and < 10 VG
Level 6 Ph.D 5 and < 10 G
Level 7 Ph.D < 5 E
Level 8 Ph.D < 5 VG
Level 9 Ph.D 10 G
Level 10 MS. 10 E
Level 11 MS. 10 VG
Level 12 MS. 10 G
Level 13 MS. 5 and < 10 E
Level 14 MS. 5 and < 10 VG
Level 15 MS. 5 and < 10 G
Level 16 MS. < 5 E
Level 17 MS. < 5 VG
Level 18 MS. < 5 G
Level 19 MS. < 5 E
Level 20 MS. < 5 VG
Table 4 Faculty levels
Table 5 Levels of teaching methodsSub-requirement Level 1 Level 2 Level 3 Level 4 Level 5
1. Clear Presentation Available Available Available Available Available
2. Excellent Notes 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 Level 1 Level 2 Level 3 Level 4
1. Class Size (CS) CS ≤ 20 20 <CS ≤ 30 30< CS ≤ 40 CS > 40
Syllabus Pre-
requisite Stud. Prep.
Class size
Faculty Current practice
Customer Requirements
Ratin
g
Row#
Desc
riptiv
e St
atist
ics
Ba
sics o
f Sta
tistic
s
Rand
om V
ariab
les
Sam
pling
Dist
ribut
ion
Es
timati
on
Test
of hy
pothe
sis
Stat
istic
al Pa
ckag
e us
e
Calcu
lus an
d coll
ege
algeb
ra
Colle
ge a
lgebr
a
Gaine
d gra
des i
n the
pre
-re
quisi
tes
Stud
y hab
it
Ph.D
in st
atisti
cs or
relat
ed
fields
Ma
ny ye
ars o
f exp
erien
ce
Exce
llent
comm
unica
tion s
kills
Poor
Good
Exce
llent
9 1 O O 7 2 O O O O O O 3 3 O O O O 6 4 O O O O
Comp
any R
espo
nse
1. Summarization of Data 2. Estimation of parameters 3. Test of Hypothesis 4. Distribution identification 5. Knowledge of Statistical software 7 5 O O
8 6 O 9 7 8 8 O 8 9 8 1
0 O O O O O O
1. Knowledgeable faculty 2. Communication and excellent notes 3. Solve homework problems 4. Small size class 5. Simple and clearly organized
textbook& examples 6. Statistical software use 8 1
1 O St
uden
t Res
pons
e
7 9 9 9 8 7 6 7.6 7 5 4.8 5 4 7 8
Design Concepts
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.
Requirements
Design concepts
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 size level
1 2 3 4 1 2 3 4 1 2 4
Table 8 Course design concepts
Source of Requirements
Concept Requirements
Con
cept
11
C
urre
nt P
ract
ice
Con
cept
1
Con
cept
2
Con
cept
3
Con
cept
4
Con
cept
5
Con
cept
6
Con
cept
7
Con
cept
8
Con
cept
9
Con
cept
10
Companies
Syllabus + S - - - + S - - -
Student preparation
+ + + S + + + S + +
Perquisites S - - S - - S - - S Faculty S - - - - - - - - -
Students and
Teaching Methods
S - - - - S - - - -
faculty Class size + + + S + + + S + + + 3 2 2 0 2 3 2 0 2 2
Totals S 3 1 0 3 0 1 2 2 0 1
- 0 3 4 3 4 2 2 4 4 3
Table 9 Design concepts evaluation
Conclusion and Further Research
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.
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.
Conclusion and Further Research