"THE RELATIONSHIPS OF EFL TEACHER STUDENTS’ AI LITERACY, AI PERCEPTIONS, AI-INDUCED EMOTIONS AND INTENTIONAL USE FOR TEACHING ENGLISH"

Abstract

"As the incorporation of Artificial Intelligence (AI) into modern educational settings has increased, determining the influence of various factors on the decision of pre-service teachers to implement AI has become a critical concern. Using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM), the research proposes a conceptualization of a structural model that clarifies the complex connections between AI literacy, AI perceptions, particularly perceived usefulness (PU) and perceived ease of use (PEOU), AI-induced emotions (enjoyment and anger), and pre service EFL teachers’ behavioral intention to use AI in future teaching scenarios. With a quantitative research design, 208 students from three universities in a region of Vietnam were used as the participants for data collection. The results suggest that AI literacy plays an important role that defines both PU and PEOU, which means that the more aware the educators are of AI, the better they can cognitively evaluate its applicability and utility. It was also found that PEOU enhances PU, thus confirming the importance of usability in determining perceived value. In addition, PU is also a determinant of emotional reactions to AI through enhanced enjoyment and diminished anger, while there is no direct effect of PEOU on emotional responses. The strongest emotional contributor to behavioral intention is enjoyment. In addition to this, AI literacy impacts BI directly and indirectly through cognitive and emotional mediators. By combining the Technology Acceptance Model (TAM) and Appraisal Theory, this research emphasizes the importance of developing comprehensive AI literacy and generating positive emotional experiences in teacher education programs to support sustainable AI adoption."