Predicting quality of English language teaching through augmented reality competencies and TPACK model components among Kuwaiti undergraduates

<b>Background: </b>Augmented reality is among the emerging technologies that hold greater potential in the context of foreign language learning. No research has been done to date to investigate pre-service teachers’ competencies in augmented reality and their association with quality of teaching English and technological and pedagogical content knowledge (TPACK) model components in the state of Kuwait.<br /> <b>Aim: </b>This study aimed to assess the utility of using augmented reality competencies and English as a foreign language (EFL) TPACK model components to predict the quality of English language teaching of pre-service undergraduates.<br /> <b>Method: </b>A total of 317 students enrolled in college of education at Kuwait university were recruited and responded to three online questionnaires measuring EFL TPACK, teachers’ augmented reality competencies, and quality of teaching English skills (QELT).<br /> <b>Results: </b>Results indicated a significant positive association among all variables at 0.01 level. Teacher’s augmented reality competencies (TARC), TPACK, technological knowledge (TK), and technological content knowledge (TCK) were significant predictors of QELT. One-way ANOVA revealed that there was no significant effect of gender on the TARC, TPACK, TK, TCK, and QELT. The cut-off-criteria of the mean scores indicated that all participants strongly believe that they acquire the essential competencies of augmented reality in EFL classrooms and possess a high level of proficiency in TPACK. Descriptive statistics showed that more than (70%) of pre-service teachers selected “strongly agree” and “agree”, 13% or less selected “strongly disagree” and “disagree” while 26% or less selected “neutral” response. Linear regression analysis revealed that TARC, TPACK, TK, and TCK were significant predictors of QELT.