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A Diagnostic study on the teaching and learning styles in engineering education

Alseddiqi, Mohamed and Mishra, Rakesh (2010) A Diagnostic study on the teaching and learning styles in engineering education. In: Future Technologies in Computing and Engineering: Proceedings of Computing and Engineering Annual Researchers' Conference 2010: CEARC’10. University of Huddersfield, Huddersfield, pp. 105-109. ISBN 9781862180932

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      Abstract

      This paper presents the results from a study undertaken to analyse the teaching and learning
      effectiveness in engineering education courses, specifically for Technical and Vocational Education (TVE) system in Bahrain. Teaching and learning diagnostic assessment tools were developed for both TVE teachers in electrical and electronic engineering and a pilot group of TVE students. The purpose was to examine the existing approaches of teaching and learning practised in TVE educational environments. The analysis indicated that TVE teachers applied limited methods of teaching and learning. However, the TVE students had widely varying learning preferences, as they are more motivated by the experiential learning approach used by the teachers.

      Item Type: Book Chapter
      Uncontrolled Keywords: Teaching and Learning, Experiential Learning, Engineering Education,
      Subjects: L Education > L Education (General)
      T Technology > T Technology (General)
      T Technology > TA Engineering (General). Civil engineering (General)
      Schools: School of Computing and Engineering
      School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC)
      School of Computing and Engineering > Diagnostic Engineering Research Centre
      School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
      School of Computing and Engineering > Informatics Research Group
      School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
      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 > Energy, Emissions and the Environment Research Group
      School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
      Related URLs:
      Depositing User: Sharon Beastall
      Date Deposited: 13 Jan 2011 12:10
      Last Modified: 13 Jan 2011 12:10
      URI: http://eprints.hud.ac.uk/id/eprint/9320

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