Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era

Abstract

The advancement of technology, especially the development and application of artificial intelligence, has deeply affected the education sector and brought opportunities for pedagogical adaptation. Intelligent tutoring systems, a major application of artificial intelligence in education, have drawn extensive concerns. However, in reality, the penetration rate of intelligent tutoring systems and the enthusiasm of faculty to use are still relatively low. This research examined the determinants of the willingness of faculty to use intelligent tutoring systems. Innovation diffusion theory was the theoretical basis of this research and it was adapted by incorporating perceived trust and experience. To gather data, a cross‐sectional questionnaire survey was performed and structural equation modeling was employed to analyze the data. The findings indicated that relative advantage, compatibility, perceived trust and experience are the contributing determinants of the willingness of faculty to use intelligent tutoring systems, while complexity has no significant effect. Meanwhile, complexity is significantly negatively affected by experience and compatibility. Relative advantage is significantly positively affected by perceived trust but not by complexity. Based on the research findings, relevant recommendations for encouraging faculty to use intelligent tutoring systems were proposed.

Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory

“…However, students' real WTA classroom applications of AI have been ignored in education (Chai et al, 2020). Wang et al (2020) proposed that AI technology applied in education should focus on the willingness of students, which is beneficial to make it effective. Lee (2019) also emphasized that the factors affecting students' willingness should be explored from the perspective of student-oriented learning.…”

Consumer Adoption of Artificial Intelligence: A Review of Theories and Antecedents

“…Other wellknown theories in technology adoption literature have been less often explored to understand the specific context of AI adoption. For example, very few studies have examined AI adoption using theories like the innovation of diffusion theory [64], uncertainty reduction theory [51], expectation-confirmation model [53], and uses & gratification theory [65]. A study used attribution theory to show that customers' attributions of service enhancements positively affect the intention to use and recommend service robots.…”

“…It has also been defined as the extent to which consumers perceive robots as reliable and credible [9]. Some researchers found that this variable has a direct positive effect on adoption intention [9], [28], [39], [48], [52], [63], [64]. Others found that trust affects perceived usefulness and perceived ease of use, affecting behavioural intention [34], [49].…”

Investigating the Influencing Factors of Teachers’ Information and Communications Technology-Integrated Teaching Behaviors toward “Learner-Centered” Reform Using Structural Equation Modeling

“…Scholars have examined the influencing factors of teacher ICT-integrated teaching behaviors based on the diffusion of innovation, TAM, technological obstacles, and TPACK [4][5][6][7][8][9]. All studies involved some factors that influenced teacher ICT-integrated teaching behaviors, and these factors are classified into two aspects, individual and environment, which align with Bandura's social learning theory.…”

“…Thus, the influencing factors of ICT-integrated teaching behaviors have always been the focus of attention of researchers, and researchers have explored these factors from different angles. The diffusion of the innovation theory [4] proposed by Everett Rogers has been applied extensively to research on the influencing factors of teacher application of new technologies in teaching [5,6], as well as research on the development law of teaching reform and innovation [7]. In addition, the technology acceptance model (TAM) [8] is broadly used in the analysis of teacher willingness, attitude, and evaluation of using technology in teaching [9], and the technological pedagogical content knowledge (TPACK) 2 of 17 is a common framework to investigate the influencing factors of the development stage of teachers of ICT-integrated teaching [10].…”