2018Journal of Further and Higher EducationRequires access

Exploring the relationship between students’ learning styles and learning outcome in engineering laboratory education

Jessica Li, Seung‐hyun Han, Shengli Fu

Open publisher page 34 citations

Abstract

It is a commonly accepted notion that people take different approaches in learning. Although attention has been given to learning styles as one of the determinants of learning performance, there is are limitations to the inferential approach to understanding the impact of learning styles on learning outcomes. The purpose of this study is to investigate the impact of learning preference on student learning outcome in engineering labs. The findings of this paper contribute to the existing literature in two ways. This study describes the typology of participants’ learning styles, confirming some results from similar research. Additionally, it examines the impact of learning styles, using the Visual, Aural, Read/Write and Kinesthetic (VARK) inventory as indicators of students’ learning outcomes, and how the findings confirm or contradict prior research results in important ways. Further, this study includes demographic information to investigate the influence on learning outcome. Discussions of the results from both analyses will contribute to an academic understanding of the critical success factors of the learning process and their practical application in laboratory learning.

About this research paper

What this paper is about

It is a commonly accepted notion that people take different approaches in learning. Although attention has been given to learning styles as one of the determinants of learning performance, there is are limitations to the inferential approach to understanding the impact of learning styles on learning outcomes. The purpose of this study is to investigate the impact of learning preference on student learning outcome in engineering labs. The findings of this paper contribute to the existing literature in two ways. This study describes the typology of participants’ learning styles, confirming some results from similar research. Additionally, it examines the impact of learning styles, using the Visual, Aural, Read/Write and Kinesthetic (VARK) inventory as indicators of students’ learning outcomes, and how the findings confirm or contradict prior research results in important ways. Further, this study includes demographic information to investigate the influence on learning outcome. Discussions of the results from both analyses will contribute to an academic understanding of the critical success factors of the learning process and their practical application in laboratory learning.

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OpenAlex reports 34 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

It is a commonly accepted notion that people take different approaches in learning. Although attention has been given to learning styles as one of the determinants of learning performance, there is are limitations to the inferential approach to understanding the impact of learning styles on learning outcomes. The purpose of this study is to investigate the impact of learning preference on student learning outcome in engineering labs. The findings of this paper contribute to the existing literature in two ways. This study describes the typology of participants’ learning styles, confirming some results from similar research. Additionally, it examines the impact of learning styles, using the Visual, Aural, Read/Write and Kinesthetic (VARK) inventory as indicators of students’ learning outcomes, and how the findings confirm or contradict prior research results in important ways. Further, this study includes demographic information to investigate the influence on learning outcome. Discussions of the results from both analyses will contribute to an academic understanding of the critical success factors of the learning process and their practical application in laboratory learning.

Key concepts: Learning styles, Kinesthetic learning, Psychology, Typology, Experiential learning, Learning sciences, Outcome (game theory), Active learning (machine learning)

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