Abstract:

Higher education institutions are encouraging their students to acquire knowledge and skills related to artificial intelligence (AI) to prepare them for the future, given the growing demand for AI technology. The concept of utility value, which is associated with positive learning outcomes, is often employed to motivate engagement in professional courses, such as those focused on acquiring AI-related knowledge and skills. This study highlights the need for specific tools to enhance the utility value of acquiring AI-related knowledge and skills, as well as the significance of value beliefs in students’ pursuit of knowledge and skills associated with AI. To evaluate the theoretical and practical significance of acquiring knowledge and skills in AI, this study proposes the development and validation of a measure to assess the utility value of AI. The research aims to divide the measurement development process into four stages: item generation, scale purification, validity testing, and norm establishment. The procedures for conceptualizing the survey, creating measurement items, collecting data, and validating the measure are outlined. The study thoroughly tests the reliability, convergent validity, discriminant validity, content validity, criterion-related validity, and nomological validity of the constructs and their relationships. This study also examines the correlation between learning satisfaction and learning persistence with assessments of the utility value of AI. Understanding the utility value of AI for students can enhance the acquisition of AI-related knowledge and skills. This insight can also assist education policymakers and instructors in identifying the implications for developing AI learning activities aimed at achieving the goal of training AI talent.

Keywords:

Higher education, Artificial intelligence, Utility value, Scale development.