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1
•
•
•
•
2
Internships
Final Year
Capstone
projects
Engineering
Laboratories/
workshops
Lectures
Tutorials
Authentic
Off campus
Learning
3
1. Jing Ma and Jeffrey V. Nickerson (2006), Hands-on, Simulated and Remote
Laboratories: A comparative literature review, ACM Computing Surveys, Vol. 38, No 3, article 7
2. Tor A. Fjeldly and Michael S. Shur (2003), Lab on the Web, Wiley-Interscience,
ISBN: 0-471-41375-5
4
In retrospect,
Need to focus on self-directed learning,
More time for self-reflection
Peer collaboration and empowerment
5
6
Intended Learning Outcomes
Synthesize and design LabVIEW software programming for industrial
applications, to solve practical problems in the real world. This is through
mini- group projects.
Examine different sensors’ characteristics through experiments.
Explain the principles of operations of various types of sensors such as
temperature, pressure, force, light, acceleration and others.
Design and develop PC-based software using graphical programming
LabVIEW for testing and performing basic data acquisition.
Describe and demonstrate basic LabVIEW software programming design
pattern
List and identify the various software components of what Virtual
Instruments in National Instruments LabVIEW software are.
Declarative Knowledge
Functional Knowledge
7
Anderson, L.W. & Krathwohl, D.R. (2001). A taxonomy for learning,
Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational
Objectives. New York: Addison Wesley Longman
Type of
Laboratory
setup
Physical
investigation of
engineering
phenomena
(with real data)
Accessibility
(24/7)
Authenticity
Repeatability
of experiments
(unlimited
access)
Students’
engagement
Hands-on
Lab
√ × √ × √
Simulated
Lab
× √ × √ ×
Remote-
access Lab
√ √ √ √ √
1. Jing Ma and Jeffrey V. Nickerson (2006), Hands-on, Simulated and Remote Laboratories:
A comparative literature review, ACM Computing Surveys, Vol. 38, No 3, article 7.
8
9
Tele-operating
10
Allow students full flexibility to
gain access to experiential learning
11
Remote Access Data Acquisition
DEMO Here
12
Phase 2
(duration:4 weeks)
Blended approach
Experiential learning
(Mid-term Quiz)
Experiential learning
Mini Project design
(Term-end
assessment)
Frequency of Lectures
(Decline)
Frequency of Lectures
(Low)
Phase 3
(duration:5 weeks)
Peer-learning, e-collaboration,
Experiential and empowering
students learning , practical
hands-on (tactile)
Learning the
fundamentals
Declarative Knowledge
Functional Knowledge
Phase 1
(duration:4 weeks)
Frequency of Lectures
(High)
•
•
13
TPACK Model
14
15
1. Jing Ma and Jeffrey V. Nickerson (2006), Hands-on, Simulated and Remote
Laboratories: A comparative literature review, ACM Computing Surveys, Vol.
38, No 3, article 7.
2. E.D. Lindsay, M.C. Good, (2005). Effects of Laboratory Access Modes Upon
Learning Outcomes, IEEE Transactions on Education, 48(4),, 619-631.
3. D.J. Magin, and S. Kanapathipillai(2000), Engineering students’
understanding of the role of experimentation, European Journal of
Engineering Education, 25(4), 351-358.
4. Anderson, L.W. & Krathwohl, D.R. (2001). A taxonomy for learning,
Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational
Objectives. New York: Addison Wesley Longman
16

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Infusing Digital Technologies for an Engineering Laboratory

  • 1. 1
  • 4. 1. Jing Ma and Jeffrey V. Nickerson (2006), Hands-on, Simulated and Remote Laboratories: A comparative literature review, ACM Computing Surveys, Vol. 38, No 3, article 7 2. Tor A. Fjeldly and Michael S. Shur (2003), Lab on the Web, Wiley-Interscience, ISBN: 0-471-41375-5 4
  • 5. In retrospect, Need to focus on self-directed learning, More time for self-reflection Peer collaboration and empowerment 5
  • 6. 6
  • 7. Intended Learning Outcomes Synthesize and design LabVIEW software programming for industrial applications, to solve practical problems in the real world. This is through mini- group projects. Examine different sensors’ characteristics through experiments. Explain the principles of operations of various types of sensors such as temperature, pressure, force, light, acceleration and others. Design and develop PC-based software using graphical programming LabVIEW for testing and performing basic data acquisition. Describe and demonstrate basic LabVIEW software programming design pattern List and identify the various software components of what Virtual Instruments in National Instruments LabVIEW software are. Declarative Knowledge Functional Knowledge 7 Anderson, L.W. & Krathwohl, D.R. (2001). A taxonomy for learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: Addison Wesley Longman
  • 8. Type of Laboratory setup Physical investigation of engineering phenomena (with real data) Accessibility (24/7) Authenticity Repeatability of experiments (unlimited access) Students’ engagement Hands-on Lab √ × √ × √ Simulated Lab × √ × √ × Remote- access Lab √ √ √ √ √ 1. Jing Ma and Jeffrey V. Nickerson (2006), Hands-on, Simulated and Remote Laboratories: A comparative literature review, ACM Computing Surveys, Vol. 38, No 3, article 7. 8
  • 10. 10 Allow students full flexibility to gain access to experiential learning
  • 11. 11 Remote Access Data Acquisition DEMO Here
  • 12. 12 Phase 2 (duration:4 weeks) Blended approach Experiential learning (Mid-term Quiz) Experiential learning Mini Project design (Term-end assessment) Frequency of Lectures (Decline) Frequency of Lectures (Low) Phase 3 (duration:5 weeks) Peer-learning, e-collaboration, Experiential and empowering students learning , practical hands-on (tactile) Learning the fundamentals Declarative Knowledge Functional Knowledge Phase 1 (duration:4 weeks) Frequency of Lectures (High)
  • 15. 15 1. Jing Ma and Jeffrey V. Nickerson (2006), Hands-on, Simulated and Remote Laboratories: A comparative literature review, ACM Computing Surveys, Vol. 38, No 3, article 7. 2. E.D. Lindsay, M.C. Good, (2005). Effects of Laboratory Access Modes Upon Learning Outcomes, IEEE Transactions on Education, 48(4),, 619-631. 3. D.J. Magin, and S. Kanapathipillai(2000), Engineering students’ understanding of the role of experimentation, European Journal of Engineering Education, 25(4), 351-358. 4. Anderson, L.W. & Krathwohl, D.R. (2001). A taxonomy for learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: Addison Wesley Longman
  • 16. 16