Composition of Learning Styles and Its Influence on Students in Transportation Engineering Courses

Students learn in different ways and a mismatch between students learning preferences and the teaching style of the instructor could lead to poor performances in the classroom. Among the learning preferences, two have been commonly identified for describing how students gather and process information during the learning process: the Experiential Learning Theory (ELT), usually referred as Kolb’s theory, and the Visual-Auditory-Kinesthetic (VAK) framework. A study at the University of Puerto Rico at Mayagüez collected information from students registered in two courses related to Transportation Engineering. In addition, student behavior and performance data at one of the courses considered the study was analyzed in order to identify if learning preferences have an influence on these two variables. The results of the study indicated that Kinesthetic students tend to have lower attendance records when compared to Visual and Auditory students. A significant relationship between learning styles and students grades was not found. The only variable that was found to be significant on students’ grades was score of homework assignments.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABG20 Transportation Education and Training. Alternate title: Composition of Learning Styles and Their Influence on Students in Transportation Engineering Courses.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Román, Edgardo M
    • Cruzado, Ivette
  • Conference:
  • Date: 2014

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 12p
  • Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01518606
  • Record Type: Publication
  • Report/Paper Numbers: 14-3990
  • Files: PRP, TRIS, TRB, ATRI
  • Created Date: Mar 20 2014 1:39PM