Learning Styles Towards Entrepreneurship Learning Outcomes and Career Development: A Structural Equation Model Analysis

Abstract

Learning styles play an important role in improving entrepreneurial learning outcomes and career development. Information processing and understanding of a theory will be well absorbed with the application of the right learning style. This research was conducted to determine the extent of the influence of the application of learning styles on the learning outcomes of entrepreneurship and career development of electronic engineering students. The number of students selected as many as 212 people with the cluster random sampling method. Data was collected through a questionnaire using a Likert scale. Testing of learning style variables using Explanatory Factor Analysis (EFA) and seeing the validity of the indicators of each variable using Confirmatory Factor Analysis (CFA). Testing of latent hypotension between variables was carried out using SEM. The results showed that outer loading, Cronbach alpha, composite reliability, AVE were valid and reliable. This means that the instrument used is valid and reliable. There is a positive relationship between structural predictor models; learning style affects the learning outcomes of entrepreneurship and career development. There is a mediating influence of entrepreneurial learning outcomes on the relationship between learning styles and career development. To achieve optimal entrepreneurship learning outcomes and career development, it is necessary to apply the right learning style. Keywords: Learning Style, Entrepreneurship Learning Outcomes, Equation Model Analysis

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“…Therefore, in order to examine the structure that is being utilized, the parameters of a certain tangent point are analyzed for the exact purpose of accomplishing this particular target. According to Husin (2022) and Dolinting and Pang (2022), the following criteria should be satisfied: (a) the loading of manifest variables (MV) should be greater than 0.50; (b) the average variance extracted (AVE) should be greater than 0.5; (c) the reliability of items per construct should be greater than 0.5; and (d) Cronbach's alpha (A) should be greater than 0.70. The Breusch-Pagan test has been used to determine whether or not heteroscedasticity is present in the observations, as well as to confirm that heteroscedasticity is not present in the findings of the data.…”