Learning styles, teaching methods, and student performance in industrial engineering at a University of Technology

Abstract

Student success and throughput rates remain a challenge at South African higher education institutions (Strydom, Mentz and Kuh, 2010) and the results in Industrial Engineering at the Durban University of Technology are no exception. Statistics released by the Department of Management Information Systems at this university in November 2012 on the graduation rates of students registered for the National Diploma: Industrial Engineering from 2009 to 2011 bear testimony to this, as the average graduation rate is between 10% and 21%. This research study investigated the learning styles, teaching methods and student performance in Industrial Engineering at a selected university of technology in South Africa by examining the preferred learning styles of students, and lecturers’ preferred teaching styles at various levels. The Felder and Silverman Model (1988) which was specifically designed to capture significant differences in learning styles amongst engineering students, was employed as the framework for the study.

Using a mixed-methods research approach, the target population for the study was the 200 students registered for the National Diploma: Industrial Engineering at the Durban University of Technology in 2013. The lecturers were identified through convenience sampling. The sample comprised five lecturers and 150 students. The participants were recruited by sending letters to inform them about the study and its purpose. Student participation was completely voluntary. The data was collected through questionnaires, and semi-structured interviews. The study used the ILS Questionnaire developed by Felder and Solomon to assess the four scales of leaning style preference among engineering students. The questionnaire was adapted to include some demographic information such as race and gender. After the lecturers were interviewed, direct observation took place in the class room in order to determine their teaching style. The researcher ensured validity of the data through triangulation and tested the reliability of the ILS questionnaire by running a pilot study. In order for the questionnaire to be reliable, the results should be the same on both occasions. The Statistical Package for the Social Sciences was used to analyse the data from the ILS questionnaire and the data from the interviews were analysed using NVivo™ software.

After the learning styles and teaching styles were identified, the quasi experiment was used to determine if changes in the lecturers’ teaching methods had any influence on the students’ learning styles and performance. It was found that this was indeed the case. In some instances such as Engineering Work Study 1, changes in the teaching method had a positive effect on student performance, but in modules such as Costing 2 and Production Engineering 2, the changes negatively impacted student performance. The study therefore confirmed that teaching styles and learning styles influence student performance. This knowledge could be used by lecturers to familiarise themselves with their students’ learning styles and to match their teaching to these learning styles in a manner that benefits all students. Students also need to be aware of their preferred learning styles and to be guided on how to use these to improve their performance in each of their modules.