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Effectiveness of Computer Assisted Laboratory Instructions:Learning Outcomes Analysis

Abdulrasool, Salah Mahdi, Mishra, Rakesh, Fieldhouse, John D., Ward, Steve and McComish, John (2007) Effectiveness of Computer Assisted Laboratory Instructions:Learning Outcomes Analysis. International Journal of Learning, 14 (8). pp. 197-209. ISSN 1447-9494

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Abstract

This study investigates the impact of computer assisted instructions on learning effectiveness in computer aided design and manufacturing modules which are integral to mechanical engineering related courses. These courses require learners to understand and know the basics of design and manufacturing processes as well as use specialist software and CNC machines. Use of computer assisted instructions enables learner to grasp complex information in an easier way because of the embedded visual element in such instructions. To quantify the effect of integration of computers in traditional teaching three groups of students were exposed to different teaching methodologies as given below.
1.Traditional classroom lecturing and laboratory work in classroom.
2.Traditional teaching with supervised exposure to available computer simulation.
3.Traditional teaching with un-supervised exposure to available computer simulation.
At the end of teaching learning process these students has been evaluated for their proficiency in CAD/CAM/CNC applications. The learning outcomes the students have been measured using blooms taxonomy in knowledge, comprehension, application, analysis, synthesis and evaluation cognition levels. The analysis of the data indicates that groups exposed to computer assisted instructions performed better than the group taught using traditional teaching method. Further supervised exposure to computer simulations gave better results as compared to unsupervised exposure to computers.
Keywords: Computer Technology, Numerical Control Machine, Computer Aided Drawing, Computer Aided Manufacturing
(CAD/CAM/CNC)

Item Type: Article
Additional Information: © Common Ground, Salah Mahdi Abdulrasool, Rakesh Mishra, John Fieldhouse, Steve Ward, John McComish 2007
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Pedagogical Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
School of Computing and Engineering > High-Performance Intelligent Computing > High Performance Computing Research Group
Related URLs:
Depositing User: Salah Al Hamad
Date Deposited: 24 May 2010 11:24
Last Modified: 10 Dec 2010 11:39
URI: http://eprints.hud.ac.uk/id/eprint/7687

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