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Attribute Assessment Implementation – ME 4R03
Saeid Habibi
2
Course Objective
The purpose of this course is to introduce the following:
• Characterization of systems by Modeling• Analysis by looking at system performance and
response in frequency and time domains• Design of controllers for LINEAR single input single
output systems.
3
Attributes• CEAB has defined 12 Graduate Attributes– example of an Attribute:
“A knowledge base for engineering”– McMaster has added a 13th attribute on
sustainability.• Each attribute has a number of ‘indicators’
associated with it.– Example of an indicator for the attribute
‘knowledge base for engineering’:“Competence in engineering fundamentals”
• We need to measure ‘indicators’
4
AttributesMcMaster has adopted 13 Graduate Attributes• Knowledge base for engineering• Problem analysis• Investigation• Design• Use of engineering tools• Individual and team work• Communication• Professionalism• Impact of engineering on society and environment• Ethics and equity• Economics and project management• Life-long learning• Sustainability
5
Attributes to be Measured in ME4R03McMaster has adopted 13 Graduate Attributes• Knowledge base for engineering 4R03 -2011/2012• Problem analysis• Investigation 4R03- 2012/2013• Design 4R03- 2012/2013• Use of engineering tools• Individual and team work• Communication• Professionalism• Impact of engineering on society and environment• Ethics and equity• Economics and project management• Life-long learning• Sustainability
6
ME 4R03 Indicators(we are measuring learning outcomes that relate to the ‘indicators’)• Knowledge base for engineering 4R03 -2011/2012
– Competence in Mathematics– Competence in Engineering Fundamentals – Competence in Specialized Engineering Knowledge
• Investigation– Able to recognize and discuss applicable theory knowledge base– Capable of selecting appropriate model and methods and identify assumption
constraints.
• Design– Recognizes and follows an engineering design process– Recognizes and follows engineering design principles– Obtains experience with open-ended problems– Able to determine and include appropriate health and safety considerations– Ability to undertake a major engineering design project and produce a unique
solution, individually or as a member of a team
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Design ProcessClassical Control
Physical System
Mathematical Model
Implementation& Tuning
Design Analysis
January
February
March
Exams:• Mathematical modeling
– Midterm 1
• Analysis:– Midterm 2
• Design & Implementation– Final – All Material
8
Marking Scheme
Course Requirements: Requirement % of Final Mark DateMidterm 1 (20 %): End of JanuaryMidterm 2 (20 %): End of February
Final Test (60 %): April
Assignments
• Large sample of questions and answers posted on the Avenue to Learn for self study and assessment
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Knowledge Base in Engineering
Physical System
Mathematical Model
January• Knowledge base for engineering
1. Competence in Mathematics2. Competence in Engineering Fundamentals 3. Competence in Specialized Engineering Knowledge
• Student work used for measurement:• Midterm 1• Midterm 2• Final exam
• Assessment through rubrics Analysis
February
10
Course Topics
1. Course Introduction 2. Modeling in the Frequency Domain 3. State Space Representations 4. Time Response 5. Reduction of Multiple Subsystems 6. Stability 7. Steady State Errors 8. Root Locus Techniques 9. Design Via Root Locus 10.Frequency Response Techniques 11.Design Via Frequency Response
11
Course Topics
1. Course Introduction 2. Modeling in the Frequency Domain 3. State Space Representations 4. Time Response 5. Reduction of Multiple Subsystems 6. Stability 7. Steady State Errors 8. Root Locus Techniques 9. Design Via Root Locus 10.Frequency Response Techniques 11.Design Via Frequency Response
Knowledge Base in Engineering
12
Course Topics
1. Course Introduction 2. Modeling in the Frequency Domain 3. State Space Representations 4. Time Response 5. Reduction of Multiple Subsystems 6. Stability 7. Steady State Errors 8. Root Locus Techniques 9. Design Via Root Locus 10. Frequency Response Techniques 11. Design Via Frequency Response
Knowledge Base in Engineering
• Knowledge base for engineering1. Competence in Mathematics2. Competence in Engineering
Fundamentals 3. Competence in Specialized
Engineering Knowledge
Rubrics
Rubric – Competence in Mathematics
Topic Below Expectations
Marginal MeetsExpectations
ExceedsExpectations
#1: Review of Laplace Transform
(Q1 – Midterm 1)
- Does not understand Laplace transformation
- Understands the properties of Laplace transformation
- Can develop transfer functions models
- Can apply partial fraction decomposition and apply the inverse Laplace transform
- Understands the concept of linearity and relate it to transfer functions and initial conditions
- Can understand and related frequency response to Laplace variable
#2: Complex Numbers(Q1.a - Final)
(Q4 – Midterm 2)
- Does not understand complex numbers
- Can evaluate magnitude and angle of vectors in s-plane
- Can apply complex number theory for tracing movement of poles given change of gain
- Can understand and use conformal mapping
Rubric – Competence in Engineering Fundamentals
Topic Below Expectations
Marginal MeetsExpectations
ExceedsExpectations
#1: Modeling(Q1 to 4 - midterm 1)
- Cannot apply differential equations for modeling
- Can model systems using ODEs
- Can apply Laplace transformation to these equations
- Understand mathematical and physical definition of linear systems
- Can develop transfer functions models for linear systems
- Can represent models in state space form
- Can use block diagrams or signal flow graph to deal with complex systems and simplify them to final form
- Can deal with non-linear systems
Rubric –Competence in Specialized Engineering Knowledge Topic Below
ExpectationsMarginal Meets
ExpectationsExceeds
Expectations
#1: Introduction to Feedback Control
Systems (not measured)
- Does not understand the difference between closed and open loop control
- Does not understand the basic instrumentation requirements
- Understands the elements in a closed loop control loop
- Can explain the math. basis for block diagram representation
- Can explain the math. basis for block diagram representation
- Can develop complex block diagram representations
#2: Frequency Domain Analysis
(Q3 - Final)
- Does not understand frequency response
- Can analyze frequency response
- Using Bode plots
- Can relate frequency response to stability
- Can understand safety margins
- Can used gain and phase margins in design
#3: Time ResponseAnalysis
(Q3 & Q4 – Midterm 2)
- Does not understand time response
- Does not understand inverse Laplace transform
- Can generate time response
- Can relate time response to Transfer function type and order in particular type 0, 1st and 2nd order
- Can understand the influence of poles and zeros on time response
- Can translate requirements to pole/zero positions
- Can understand and apply the concept of dynamic significance and dominance
- Understands non-minimum phase systems
#4: Stability
(Q1 & Q2 – Midterm 2)
- Cannot relate pole position to stability
- Understand stability, marginal stability, and instability
- Can apply Routh Hurowitz to special cases and in design
- Understands Nyquist analysis
#5: Steady State Errors(not measured)
- Does not understand steady state error
- Can understand and calculate steady state error
- Can calculate steady state error for various types of system and states
- Can apply steady state error concept in design
#6: Root Locus Techniques
(Q1.a – Final)
- Does not understand root locus
- Understands the concept and knows the rules for obtaining root locus
- Can sketch root locus of simple systems
- Can apply all rules to complex non-minimum phase systems
Competence in Mathematics
Measurement
Measurement by Assessment
Topic Below Expectations
Marginal MeetsExpectations
ExceedsExpectations
#1: Review of Laplace Transform
(Q1 – Midterm 1)
- Does not understand Laplace transformation
- Understands the properties of Laplace transformation
- Can develop transfer functions models
- Can apply partial fraction decomposition and apply the inverse Laplace transform
- Understands the concept of linearity and relate it to transfer functions and initial conditions
- Can understand and related frequency response to Laplace variable
/// //// ////
//// //// //// //// //// ////
///
Competence in Mathematics
18
Topic # 1 Review of Laplace Transform Topic # 2 Complex Numbers
-10.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Below Expectations MarginalMeets Expectations Exceeds Expectations
Perc
enta
ge
Conclusions• Students do not have a good background in complex
numbers • More review lectures needed both for Laplace and
complex numbers
Topic # 1 Review of Laplace Transform Topic # 2 Complex Numbers-10.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Below Expectations MarginalMeets Expectations Exceeds Expectations
Perc
enta
ge
Competence in Engineering Fundamentals
Measurement
So what do we do with this data?
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Average of Attribute (Topic # 1Modeling):
Average for Attribute0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
Below Expectations MarginalMeets Expectations Exceeds Expectations
Perc
enta
ge
Conclusions
• The coverage and background are good
Overall Grade Distribution (MT 1) Topic # 1 Modeling0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
Below Expectations Marginal Meets Expectations Exceeds Expectations
Perc
enta
ge
Competence in Specialized Engineering Knowledge
Measurement
Competence in Specialized Engineering Knowledge
24
Topic # 2 Frequency Domain
Topic # 3 Time Response
Topic # 4 Stability Topic # 6 Root Locus0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
Below Expectations Marginal Meets Expectations Exceeds Expectations
Perc
enta
ge
Observations• More needed in frequency response and root locus
analysis• Root locus relies heavily on complex numbers• Stability and time response OK
Topic # 2 Fre-quency Domain
Topic # 3 Time Response
Topic # 4 Stability Topic # 6 Root Locus
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%
Below Expectations MarginalMeets Expectations Exceeds Expectations
Perc
enta
ge
Plan for next year
• Have 1 question specifically on Laplace, but probe more
• Add a lecture on complex numbers + example• Have a question on complex numbers• More time and emphasis on freq. and root
locus analysis – both in lecture time and exam• Have exam questions on Topic #1 (midterm 1)
and Topic #5
Suggestions
• Choose coarse grain selection of topics • Come up with the Rubrics right away• Carefully design your tests – come up with draft tests
(midterms/final) at the beginning of the course• Group and segment questions according to Rubric• Allow additional time for assessment (Approx. 1 day)• Incorporate attribute assessment into marking strategy • Mechanism needed to record the assessment process
Comments
• We all do it! But in an unstructured way!• Overall not a bad concept – allows an in-depth annual
review and self examination of course objectives • Enables root cause analysis• Can lead to continuous improvement of course contents• Not all attributes and indicators apply – problem simpler
than it appears• It will take a couple of iterations to get it right (2 or 3
offerings of the course)• Use Marilyn’s example – that is what I used to prepare
mine!!
Conclusions• It can be done• There may be many reasons why not to do it;
but two reasons why we must:– Our accreditation depends on it; and– It will improve our program.
• We have to implement in the next 2 year to be ready for the accreditation
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Documentation of Measurement Results• Need to write a short document summarizing
results. It should include:– Rubric used for measurement– Corresponding exam or test– Distributions for each learning outcome area – Identified areas for continuous improvement– Sample exam papers with performance in each area
(below expectations, marginal, …)– Suggestions for how to improve measurement
procedure (if any)• Need to identify a database where these
documents can be kept.