Abstract:

With the development of artificial intelligence (AI) techniques/products, AI-related knowledge/skills learning has become an important issue for business management education academics and practitioners. Understanding the predictors of business management students’ behavioral intention to learn AI-related knowledge/skills and subsequent learning behavior is critical to enabling business management instructors to develop effective ways to strengthen AI education. Given the limitation of existing self-report instrument, the purpose of this study is to develop and validate a generic instrument, an AI use self-efficacy scale, which captures an individual’s perceived self-efficacy of AI techniques/products use by using exploratory and confirmatory scale development approaches. Specifically, this study defines and develops the construct of the AI use self-efficacy and discusses the theoretical and practical applications of the scale. The procedures used to conceptualize the survey, create the measurement items, collect data, and validate the scale are described. By analyzing data obtained from a sample of 318 respondents, the reliability, convergent validity, discriminant validity, content validity, criterion-related validity, and nomological validity of the constructs and relationships are fully examined. Moreover, this study further deepens the preliminary conceptual model of AI knowledge/skills learning behavior and incorporates business management education research in the context of university education. The result shows that a positive correlation exists between individuals’ AI use self-efficacy scores and AI-related knowledge/skills learning behavior. The findings of this study will enhance our understanding of the relationship between business management students’ AI knowledge/skills learning behavior and AI education.

Keywords:

Artificial intelligence use self-efficacy, AI knowledge/skills learning, Scale development, Business management education