Gen Z Students’ Readiness for AI-Assisted English Speaking Practice: Qualitative Analysis - Vistari, Lalita; Yuliasri, Issy; Yuliati, Yuliati (The Proceedings of English Language Teaching, Literature, and Translation (ELTLT), 2025)
This study aims to explore the perceptions and attitudes of Generation Z (Gen Z) students who are considered digital natives and interact with AI technology in English speaking practices. This study moves beyond conventional quantitative measurements to delve into the distinct qualitative psychosocial dimensions in question. Through a qualitative exploratory approach, perceptions, challenges, and expectations that students hold concerning educational technologies such as chatbots and speech recognition software were analyzed utilizing semi-structured interviews, reflective journals, and field notes. Findings indicate that even though students in this age cohort are technologically adaptive, they experience high levels of AI-induced emotional disengagement. In addition, Gen Z expresses a new form of “perfection anxiety” that relates to the pervasive tech issue AI faces in accurately capturing speech. This tension underscores a paradox in contemporary AI design, while AI interfaces have the potential to enhance multilingual pedagogical practices, they starkly lack the empathy and emotional sensitivity required to support psychosocial interaction. This study proposes advances the design of pedagogical AIs beyond the provided functionalities and aims by addressing the intrinsic design requirements that emerge from the learner level, thus, holistically attending to the psychosocial and emotional dimensions of fluency needs of digitally proficient Gen Z learners.