Presentation for MathWorks (www.mathworks.com) at World Engineering Education Forum 2014, Dubai. Education is challenging. It always was challenging, and it always will be challenging, but every generation of educators and society has to find answers specific to their era. This talk addresses some of the challenges in engineering education in the 21st century. Industry complains about the skills gap they face with graduates in engineering, for lack of project awareness, problem solving skills, applicable tool skills or applied science skills. Academia complains about students not bringing the necessary basic skills as engineering freshmen. Teachers complain about a lack of student engagement. Students complain about classes not engaging them and seeming irrelevant. When putting this chain of challenges – industry, academia, school, students – on its head and starting with the student engagement, one method getting attention is Project-Based Learning. Students educate themselves on concepts they need, with the teacher facilitating the learning experience. Applying theory in practical ways with tools that are used in industry gives students first-hand experience on industry relevant methods as well as the why behind theory. The talk shows examples of programming, modeling and simulation to gain insight into theory and application. Too often students and educators feel that topics throughout their education are not connected. Early on they lack understanding of the why they are learning something. Later they no longer see the connection of advanced theory to fundamental concepts. Reusing learning artifacts, skills and methods helps mapping out the story. Demonstrations illustrate how educators implement this re-use throughout teaching. Consequent reuse leads to Integrated Curriculum, where methods and skills in each year build on previous ones. Evaluations in integrated curriculum enabled programs show a higher retention of know-how. We all can make math, physics and engineering able to experience using simulation and hardware experiments. The tools and resources are there. Let's address our generation's engineering education challenges.

1. 1© 2014 The MathWorks, Inc.
Accelerating the Pace of Engineering Education
with Simulation, Hardware and Instrumentation
Dr. Joachim Schlosser
MathWorks
@schlosi

2. 2
Imagine…

3. 3
Use existing tools
in and on MATLAB with
hardware instead of
re-inventing the
wheel.

4. 4
[Why me]
Image Sources: Hochschule Augsburg, Technische Universität München, BMW AG, Wiki Commons (under LGPL), Berner & Mattner Systemtechnik GmbH, Audi AG, MathWorks

5. 5
Agenda

6. 6
Teachers

7. 7
STEM Skills Survey, UK
Are there enough skilled candidates from universities
to meet STEM employees’ requirements?
Short Answer: No.
mathworks.com/STEMskills

8. 8
Some Relevant Statistics
61% business leaders and
68% of academics believe it will take
more than 10 years to close
the gap.

9. 9
Some Relevant Statistics
52% of employers and 64% of
academics state that there isn’t
sufficient collaboration between
universities and industry.

10. 10
Some Relevant Statistics
63% of industry think they should
have a greater say in curriculum
but 46% of universities
welcome the industry intervention.

11. 12
University of Applied Sciences Augsburg
Students Develop and Simulate Advanced Robotic Control Systems
“When I teach C++, I show students a
program that simulates a swing. The C++
program is seven pages of code or more.
The MATLAB implementation is a single
page —about 50 lines of well-structured,
compact code that is easy to understand.”
Professor Georg Stark
University of Applied Sciences Augsburg
Link to user story
Professor Stark with students in the lab.

12. 14
Industry

13. 15
Anecdotal Evidence
“… particularly hard to recruit graduates
with the key skills required to make an
immediate impact as part of our
workforce …”
Senior Manager in Industry

14. 16
Anecdotal Evidence
“… This is leading to a ‘skills silo’ and
thinking in ‘one direction’…”
Senior Manager in Industry

15. 17
Skills Required by Employers
1. Abstraction and Big Picture Thinking
2. Solving Real-World Problems
3. Multi-Disciplinary Teams

16. 18
Supporting Curriculum Development

17. 19
Technische Universität München Uses Model-Based Design to Drive
Research, Problem-Based Learning, and Industry Collaboration
“Flight controls and flight system dynamics are
multidomain engineering disciplines. MathWorks
tools enable our students to build upon our
fundamental research to develop solutions that fly
in real aircraft. With Model-Based Design we can
close the gap between the theoretical foundation
and the practical application.”
Dr. Florian Holzapfel
Technische Universität München
Link to user story
Professor Holzapfel, research fellow Markus Hornauer,
and a student test flight control algorithms in the
Research Flight Simulator.

18. 21
25 years ago CAD disrupted construction.
Image Sources: customized030 on Flickr, License CC-BY-ND, Siemens PLM Software on Flickr, License CC-BY-ND

19. 22
Now Model-
Based Design &
Simulation
disrupt engineering.

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4 Practices of Early Verification

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Create and
simulatea high-
level system model
during
specification stage.
#1

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Image Sources: Peter Jackson on Flickr, License CC-BY
Dynamic behavior  System insight

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#2
Test from day one
with multidomain
simulation.

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Image Sources: eha1990 on Flickr, License CC-BY
vs.
Model
• wires
• steel
• code

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#3
Create virtual
test suites that
stress the system.

26. 29
Simulations
scale better.
Image Sources: torkildr on Flickr, License CC-BY-SA

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#4
Use the modeland test
suites as reference
design.

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INTEGRATION
IMPLEMENTATION
DESIGN
TEST&VERIFICATION
RESEARCH REQUIREMENTS
Environment Models
Mechanical
Control Algorithms
Electrical
Supervisory Logic
TEST
SYSTEM
Structured
Text
VHDL, VerilogC, C++
MCU DSP FPGA ASIC PLC
Start Testing on Day One

29. 33
Students

30. 34
Study Quality Monitor Germany 2013 – Asked students
 „Teachers present the subject matter as interesting and appealing
[in > ½ of all classes].“
 40%
 „The teacher is able to motivate the students for the subject matter.
[in > ½ of all classes].“
 30%
Source: DZHW – Studienqualitätsmonitor 2013

31. 35
MATLAB is part of the scientific infrastructure of
academic and research organizations

32. 36
As concert halls for orchestras,
MATLAB is part of the scientific infrastructure of
academic and research organizations
Photo: Maria Oik on Flickr, License CC-BY.

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MATLAB is neither the music,
nor the instrument,
nor the musician.
It is the space where a musician,
together with other musicians,
creates, refines, performs, shares
and enjoys music.
Jiuguang Wang on Flickr CC-BY-SA

34. 38
So, what should musicians be given?
 Enough seats
 The right instruments
 A standard notation in a standard system
 Seamless integration, interface, communication
 Easy access
 Education and training
© Copyright Steinway & Sons on Wikimedia Commons CC-BY-SA

35. 39
So, what should academics be given?
 Enough licenses
 The right toolboxes
 A standard language in a standard operating system
 Seamless integration, interface, communication
 Easy access
 Education and training

36. 40
Teaching Model-Based Design at Politecnico di Torino
“Using MATLAB, Simulink, Stateflow, and
Embedded Coder, students learn how to
manage the growing complexity of today’s
embedded systems by designing and
simulating an executable model; rigorously
validating, testing, and debugging it; and
generating code for an embedded target.”
Massimo Violante
Politecnico di Torino
Link to article
Stateflow state chart used to
implement control logic for a
simple parking assist system.

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What does LinkedIn tell us?

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Engagement

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Imagine…

40. 48
We're engineers – Let's engineer
our way out of this dilemma.

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Project-Based and Problem-Based Learning
Example: RWTH Aachen, EE

42. 50
Lecture Design
 Signal processing basics
 Mathematical methods
 Introduction of MATLAB
 Lectures: 90 min/week
 Tutorials: 90 min/week
 Small group exercises: 45 min/week
(Source: CDIO Conference 2014)

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 2 months into the 1st semester (December)
 8 days course program
 Organizational constraints
 Great student feedback
 Highest-rated class
Year
# students in
Electrical Eng
2010/11 399
2011/12 536
2012/13 358
2013/14 502

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Class Concept
Laboratory
Mathe-
matical
Methods
Practical
Engineering
MATLAB

45. 54
Robot Laboratory Schedule
Time slot Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8
Morning NXT
Sound
Sensor
Motors
Optical
Sensor
Ultrasonic
Sensor
Creative
Task
Creative
Task
Creative
Task
Afternoon
Bluetooth
+
Tactile
Sensor
Motors
Optical
Sensor
Ultrasonic
Sensor
Creative
Task
Creative
Task
Creative
Task
Final
presen-
tation

46. 55

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Active Learning (CDIO Standard 8) – Students Praise
Collaborative learning environment in
robotics lab class
Learning success
Increased motivation
Positive experiences
gained & shared

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Enhancement of Faculty Teaching Skills (CDIO Standard 10)
All institutes of
department involved
 dissemination of
teaching knowledge
and methods

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Enhancement of Faculty Teaching Skills (CDIO Standard 10)
Teachers rely on the fundamentals taught
 Disciplinary knowledge
 MATLAB know-how
 Teamwork skills

50. 59
Enhancement of Faculty Teaching Skills (CDIO Standard 10)
Student teaching
assistants required to
participate in a
teaching class to
advance their personal
teaching skills

51. 60
Student Engagement: Formula Student
(e.g. Formula Student Germany)
Click for video

52. 61
Reuse

53. 62
“There is no correlation between
experimenting and learning outcome, in general.” §
“Experimenting does improve learning outcome,
if supported by a didactic framework.” §
Not if, but how…
§ e.g. D. R. Sokoloff and R. K. Thornton, Using Interactive Lecture Demonstrations to Create an
Active Learning Environment. The Physics Teacher, September, 1997, Vol. 35, pp. 340-347.

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Experiments are time consuming.
1. Prep work (instructor)
2. Pre-experiment
3. Experiment
4. Post-experiment
5. Evaluation
The How’s
MATLAB & Simulink Very important
Immensely important
Typically over-emphasized

55. 64
Hardware connectivity
Symbolic Numeric
Optimization
Control System
Graphic, physical
Modeling
Simscape
StateFlow
Simulink
MATLAB
Simulink and Simscape blocks
MATLAB function
Publishing
Symbolic
Experiment implementation: the sky’s the limit
1
1
1
1
2
2
2
2

56. 65
The solution landscape: a matter of perspective
MATLAB (symbolic)
Simulink
Simscape
MATLAB (numeric)
Publishing
MATLAB and H/W
convert
convert
convert

57. 66
RLC series circuit: problem statement

58. 67
RLC series circuit: solution and analysis

59. 68
Hardware for
teaching and research
Support package only req’d Additional toolboxes req’d
Raspberry Pi
LEGO Mindstorms
NXT and EV3
Arduino
Samsung Galaxy, iPhone
Altera DE2-
115
Freescale Freedom
Digilent’s
Analog
Discovery
 Find hardware for your application
 … and request additional hardware
…plus many more…plus many more
Microsoft
Kinect
NI
CompactDAQ

60. 69
Integrate

61. 70
Move Programs off the Trade-Off Surface
TechnicalBreadth
Technical Depth
Feasible
Region
Current Programs
Desired
Extended Programs
Computational
Thinking &
Tools

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Example from Applied Science School in Aschaffenburg, DE
Course Plan
BSc Renewable Energy and Energy Management
Source: Joerg Sautter at MATLAB Expo Germany 2014

63. 72
Example from Applied Science School in Aschaffenburg, DE
BSc Renewable Energy and Energy Management
Source: Joerg Sautter at MATLAB Expo Germany 2014

64. 73
Example from Applied Science School in Aschaffenburg, DE
BSc Renewable Energy and Energy Management
Source: Joerg Sautter at MATLAB Expo Germany 2014

65. 74
Example from Applied Science School in Aschaffenburg, DE
BSc Renewable Energy and Energy Management
Source: Joerg Sautter at MATLAB Expo Germany 2014

66. 75
Michigan State University’s
MATLAB integrated Curriculum for Chemical Engineering
Before
After
Course using
MATLAB / Simulink
Student’s computational
problem-solving proficiency

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Share

68. 77
Resources to get you started
>> doc
MATLAB
Courseware
MATLAB Central
info/code hub

69. 78
Online experimenting: Cody Coursework Problem
Solution
Feedback
 Create MATLAB problem sets
 Grade based on test suites (automated!)
 Assess class progress
 Detect plagiarism and proctor exams
 Use 1300+ autograde-ready MATLAB
programming problems

70. 79
Create

71. 80
As concert halls for orchestras,
MATLAB is part of the scientific infrastructure of
academic and research organizations
Photo: Maria Oik on Flickr, License CC-BY.

72. 81
With whom in my department
will I create improvement
with MATLAB & Simulink in
both our classes?
mathworks.com/academia