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
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
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