Factors Influencing Deep Learning in Tourism Consumer Behavior Courses: A Study Based on Constructivism and Reciprocal Determinism

Abstract

The research aims to clarify the influencing factors of deep learning among students and improve their level of deep learning in tourism consumer behavior courses. The study takes questionnaire survey and statistical analysis methods to investigate and analyze the influencing factors of deep learning status among students in the tourism consumer behavior course. Based on constructivist theory, reciprocal determinism, and student participation theory, regression model assumptions and model variable selection are made. There were significant differences in the deep learning engagement among students of the Tourism Consumer Behavior course based on their gender and employment status as student cadres. Students' self-efficacy perception, interest in learning the course, and satisfaction level in the individual dimension had a significant positive impact on their deep learning status. The study innovatively conducts an internal logical analysis of students' deep learning states and their driving factors based on constructivist theory, reciprocal determinism, and student participation theory. Based on the actual situation of students in the tourism consumer behavior course, this research explores the driving factors of deep learning for undergraduate students in higher education institutions.