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https://doi.org/10.18260/p.242...
Article . 2015 . Peer-reviewed
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Hybrid Learning Styles

Authors: Quintana M. Clark; Alejandra J. Magana;

Hybrid Learning Styles

Abstract

Hybrid Learning StylesThis study extends learning style theory by demonstrating statistical evidence that supports theexistence of hybridity in learning styles. The eventual application of a more refined learningstyle instrument may improve the quality of instruction, learning, and educational standards byincluding personalized instructions that appeal to broader audiences. Refined learning styleindicators may also increase an individual’s knowledge of how they learn and improve theirability to learn material they previously felt was too difficult. Such attributes may eventuallyhelp to reduce the STEM achievement gap.Over the last 30 years there has been a slow and steady call for teaching and learning to embracea more personalized pedagogy that addresses an individual’s learning styles. This call reflects thelarge number of American students that fail to reach adequate levels of proficiency in K-12education. The problem is much worse for the areas of STEM, where few high school studentsgo on to obtain a degree in a STEM discipline. It is widely thought that personalized learning canbe improved by identifying an individual’s learning styles.Several models that predict an individual’s preferred learning style have been developed over thelast three decades. One of the more recent and prominent learning style indictors is the KolbLearning Style Inventory (KLSI), which is based on neuroscience and identifies nine discretelearning styles. Thousands of individuals have been tested with KLSI. However, what has notbeen studied is the possible continuum that might exist between the nine discrete learning styles.Therefore, the research question we address in this study is: Can an individual possess a hybridlearning style, which is comprised of a distribution of two or more of Kolb’s discrete learningstyles? In this study, a new survey was developed to collect learning-ability data from a sample of 185university students studying technology. The data was analyzed using algorithms that wespecifically designed to identify ...

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
bronze