Graduation Year

2016

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Adult, Career and Higher Education

Major Professor

Waynne B. James, Ed.D.

Committee Member

William H. Young, Ed.D.

Committee Member

Jeffrey Kromrey, Ph.D.

Committee Member

Cihan Cobanoglu, Ph.D.

Keywords

MBTI, Personality, Introduction to Hospitality, Online, Face-to-face

Abstract

The purpose of this study was to explore the relationship between learning styles and the choice of learning environment for Hospitality and Tourism undergraduate students. An anonymous two-part survey was sent to the instructors of Introduction to Hospitality and Tourism Management courses (both online and face-to-face) in four schools in the state of Florida. The survey was designed to gather information related to the following three research questions related to MBTI profiles for undergraduate students in attempt to identify differences between students enrolled in online classes and those in face-to-face classes. In order to determine the probability of predicting course choice behavior of undergraduate Hospitality and Tourism students, the following factors were controlled in this research: age; gender; enrollment status; employment status; university; whether they had taken an online course previously in high school, college, or other places; how many online courses they previously took; and who helped them select the delivery mode of their courses.

There were 323 usable responses, which included a majority of the most common types as ESTJ. When the differences between online and face-to-face course students were analyzed through chi-square tests, the results showed significant differences between two groups for all four profiles. Overall, the most common profile for face-to-face students was ESTJ, while the most common profile for online students were ISTP. In order to examine the unique contribution of learning styles on Hospitality and Tourism students’ course choice, a hierarchical logistic regression model was used. The results of the model indicated that only profile one (P1) and profile four (P4) were significant predictors among the four profiles, along with the total number of online courses previously taken.

The conclusions suggested that by looking at P1, P4, and toc1, with a 95% confidence level, the probability of students choosing face-to-face classes can be predicted if the students are extrovert, judging, and previously had taken less than five online courses. If learning styles can be determined ahead of time, students can choose appropriate courses, instructors can develop teaching strategies that will match students’ desirable learning styles, and the number of face-to-face and online courses can be adjusted in each program to offer an appropriate number of courses each semester.

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