Self-efficacy as a Mediator Between AI-dialogic Scaffolding, Language Anxiety, and Speaking Confidence in Saudi EFL Context

Abstract

Obstacles remain in the form of inconsistent outcomes of AI applications in English as a foreign language (EFL) speaking instruction, particularly in Saudi contexts, where language anxiety and a sense of insecurity prevent learners from becoming more empowered through technological exposure. In this study, a mediator variable, self-efficacy, was postulated in the interaction between AI dialogic scaffolding, language anxiety, and speaking confidence. The current research employed a quantitative cross-sectional design, with data analyzed using partial least squares structural equation modelling (PLS-SEM) among 243 Saudi students studying at EFL universities. The findings established that AI-dialogic scaffolding had positive effects on speaking confidence and self-efficacy, and negative effects on language anxiety were very high. These relationships were partially mediated by self-efficacy, which is a critical psychological mediator. The results present a new model that incorporates technological and affective factors, offering meaningful theoretical and practical implications for the creation of AI-based language-learning contexts that facilitate psychological stability and skills acquisition. The originality of this research lies in empirically verifying complex mediating pathways in the context of Saudi EFL and extending the models of direct effects that most other researchers have previously explored. This study offers a rational framework that combines technological, cognitive, and affective features, thus contributing to the theoretical knowledge of both applied linguistics and educational technology. It extends beyond the examination of immediate impacts and shapes models of how scaffolding procedures align with the wavy paths through which they exert their influence. The studies suggest using an evidence-based approach in the Saudi context, and researchers should focus on enhancing self-efficacy to break anxiety and lack of self-confidence. Finally, the study illuminates that the true potential of AI in ed-tech is not just its ability to copy an interaction; rather, its capacity to be organized in a way that instills psychological strength and confidence in the messages it delivers. Thus, the study provides a distinct path for the evolution of a better, more holistic, and learner-focused digital language-learning environment.