Teacher Challenges and Strategies in Implementing the Deep Learning Approach to Improve Speaking Skills in Narrative Inquiry

Abstract

Abstract    

This study aims to examine the application of the deep learning approach in learning speaking skills in the context of English as a Foreign Language (EFL), with a focus on teacher experiences, challenges, and strategies. This research is motivated by the need for more meaningful and student-centered speaking learning, where students not only understand the structure of language, but are also able to use it confidently in real communication. This study uses a qualitative approach with a narrative inquiry method to explore the experience of an English teacher at SMA Negeri 2 Pamekasan. Data were collected through a narrative framework and semi-structured interviews, then analyzed using thematic analysis. The results of the study show that the application of the deep learning approach in speaking learning is a complex and contextual process, involving cognitive, affective, and situational aspects. Three main themes were found in the study. First, meaningful speaking learning emphasizes the importance of real context, active engagement, and strengthening student confidence. Second, challenges in learning to speak include students' anxiety, limited learning time, and differences in ability levels in the classroom. Third, teacher strategies include the application of scaffolding, the creation of a supportive learning environment, the use of engaging activities, the provision of constructive feedback, and reflection practices. These findings show that the success of speaking learning is determined not only by linguistic aspects, but also by students' psychological readiness and teacher ability to adapt learning strategies. Thus, the deep learning approach has strong potential in improving speaking skills through meaningful and reflective learning, although its implementation requires continuous adjustment to classroom conditions.