Prediction of Iranian EFL Learners’ Learning Approaches Through Their Teachers’ Narrative Intelligence and Teaching Styles: A Structural Equation Modelling Analysis

Abstract

It goes without saying that there are many influential factors affecting the success of any learning experience, and teachers are definitely among the significant factors influencing the process of teaching and learning. In this respect, the present study sought to investigate the prediction of Iranian English as a Foreign Language (EFL) learners' learning approaches through their teachers' narrative intelligence and teaching styles. The participants comprised 50 high school teachers along with 400 students in Birjand, South Khorasan, Iran. The necessary data were obtained through Narrative Intelligence Scale, Teaching Style Inventory, and Study Process Questionnaire. The Structural Equation Modeling (SEM) analysis demonstrated that teachers' teaching style had a direct and meaningful effect on learners' deep (β = .31; p= .04) and surface (β = .18; p= .04) learning approaches. Whereas the teachers' narrative intelligence only had a direct and meaningful effect on deep learning approach (β= .006; p= .03) and out of the subscales of narrative intelligence, only narration with a positive effect (β= .28; p= .04) was the best predictor of deep learning approach. Among the five types of teaching styles, the facilitator style with a positive effect (β = .37; p= .001) and the formal authority style with a negative effect (β = -.22; p= .01) were the best predictors of deep learning approach. Besides, the expert style with a negative effect (β =-.14; p= .02) and the formal authority style with a positive effect (β= .16; p= .008) were defined as the best predictors of surface learning approach.