Amotivation in AI injected EFL classrooms: Implications for teachers - Dian Toar Y. G. Sumakul; Fuad Abdul Hamied (Universitas Pendidikan Indonesia, 2023)
Motivation is an essential aspect of students' success in their learning, and an investigation into the factors that could deteriorate their motivation could shed light on that issue. This study investigates amotivation during the application of artificial intelligence technology in EFL classrooms or AI-injected learning. As artificial intelligence is still a relatively new technology, but its application is becoming increasingly more prevalent in language classrooms, this study aims to explore factors that could negatively affect EFL students’ motivation to use technology in their learning. This study included questionnaires and interviews to collect data from 133 EFL students in an Indonesian higher education institution. The students had experience working with AI applications in their learning. The statistical analysis of the questionnaire data suggested that, although not dominant, amotivation was evident among the students. More than 25% of the students experienced amotivation while learning using the AI apps. The qualitative analysis of the interview data revealed three factors that could give rise to amotivation among the students when working with the AI apps: intelligence, user interface, and lesson design. Intelligence and user interface were internal to the AI apps, while lesson design was associated with the teachers' pedagogical competence in preparing the lessons for their students. This study suggests that app design and lesson design are two motivational factors that could affect students’ motivation in AI-injected learning.