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Entrepreneurship is a process of learning. The entrepreneurial learning process incorporates a cumulative series of multifaceted entrepreneurial experiences, which generally involve the development of new insights and behaviours. This study aimed to determine whether entrepreneurial experience has an influence on the preferred learning styles of students. The study also investigated the appropriateness of the Reduced Kolb Learning Style Inventory as a measuring instrument.

The study was conducted on 586 male and 690 female students from South Africa (n = 1042) and Norway (n = 244). The Reduced Kolb Learning Style Inventory, making use of principal correspondence analysis, was used to determine the preferred learning styles, while the students' level of entrepreneurial experience was captured by items addressing prior entrepreneurial experience.

The analysis revealed a simpler measure of students' preferred learning styles, comprising a total of 12 items with three items per learning style. The study revealed that the preferred learning style was more important for students who had entrepreneurial experience than for those with less entrepreneurial experience. If students with entrepreneurial experience have stronger concerns for how they learn, it contributes to the understanding of the content of entrepreneurial learning.

A modified Reduced Kolb Learning Style Inventory resulted in a concise instrument measuring students' preferred learning style in adherence to Kolb's work and evidenced its usefulness. This study contributes to a field that has been under-researched, related to the association between students' past and current entrepreneurial experience and their learning style preference, and aims to bridge the two research fields. This research explores these links and points to how these insights could inform entrepreneurship education.

The purpose of this paper is to examine the use, construct, and pervasiveness of learning styles theory. Whilst extant literature has provided educational theorists with a temporal landscape for promoting or critiquing the surfeit of “models” and “diagnostic tools”, there has been little empirical research evidence undertaken on the adoption and adaptation of learning styles in the e-Learning environment, especially in respect of personalised learning environments (PLEs). In this respect, evidence identifies that the more thoroughly instructors understand the differences in learning styles, the better chance they have of meeting the diverse learning needs of their learners.

The paper provides a critical review of the development of learning styles inventories and instruments of learning styles. It focuses specifically on the reliability, validity, and rubrics behind these models. A positivist stance was adopted, using a structured case study methodology with learners as the main unit of analysis. This was undertaken to statistically explore and confirm the validity and reliability of a Diagnostic Questionnaire (DQ).

A new Diagnostic Learning Styles Questionnaire was developed based upon the amalgamation of three existing models of learning styles (Kolb; Honey and Mumford; and Felder and Silverman). Research findings identified four principal learning styles categories (A, B, C, D). These are supported by Cronbach's α results ranging from 0.57 to 0.80 for the learning styles within the DQ, which provides new insight into these relationships.

This research suggests that improved construct validity can be achieved if relationships are fully understood. However, research findings need to be countered by extending the embedded case study presented in this paper to include other case studies for comparison (within this context). Further research is also needed on examining learner traits in more detail with a wider data set.

The DQ can be used to explore different approaches to use in learning environments. Specifically, it allows training providers to understand the nuances and dependencies associated with learner styles, behaviour, learner effectiveness, and motivation.

This paper uncovers new understanding on the learning process and how this links to pedagogy and learning styles. It presents a mechanism for embedding a DQ into a PLEs.