Creating a Novel Approach to Examine How King Saud University’s Arts College Students Utilize AI Programs

One of the cutting-edge ideas that is essential to improving students’ behavioral intention for using artificial intelligence (AI) and attitude toward it (ATAI) at higher education institutions is artificial intelligence learning. Artificial intelligence education is not widely available in Saudi Arabian universities. The study’s goal is to ascertain how perceptions of assessment quality, perceived risk, price value, artificial intelligence anxiety, educational quality, and perceived AI intelligence affect attitudes toward and perceived usefulness of employing artificial intelligence. When attempting to encourage the use of artificial intelligence (AI) in higher education, take into account factors such as perceived utility, attitude toward AI, behavioral intention to use, user happiness, and general mindset regarding AI. Additionally considered is the mediating function that behavioral intention and user pleasure have when utilizing artificial intelligence (USAI). A survey of Saudi universities was conducted in order to meet the study’s goal. 183 questionnaires were distributed around the universities to collect student data. Partial least squares (PLS) analysis and structural equation modeling were utilized to examine the data once it was gathered. User satisfaction in using artificial intelligence is the most crucial element in promoting student adoption of AI in higher education (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.646$ </tex-math></inline-formula>, t-value = 10.402). Perceived usefulness of using artificial intelligence (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.309$ </tex-math></inline-formula>, t-value = 4.240; <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.275$ </tex-math></inline-formula>, t-value = 2.194; and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.473$ </tex-math></inline-formula>, t-value = 7.619, respectively) and attitude toward artificial intelligence (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.285$ </tex-math></inline-formula>, t-value = 2.584; and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.151$ </tex-math></inline-formula>, t-value = 2.453, respectively) are significant factors in transferring the positive effects of behavioral intention to use and user satisfaction in using artificial intelligence. A crucial part of communicating the positive impacts of AI adoption in higher education is also played by user satisfaction (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.646$ </tex-math></inline-formula>, t-value = 10.402, respectively) and behavioral intention to use AI (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta = 0.174$ </tex-math></inline-formula>, t-value = 2.817, respectively)”. We can better comprehend Saudi undergraduates’ motivation to use artificial intelligence (AI) for learning in higher education thanks to this study, which combines the TAM model and UTAUT theory. Future research in educational environments can make use of this theoretical framework. Furthermore, this study provides educators and educational institutions with some recommendations on how to motivate students to use AI to achieve better outcomes.