Artificial Intelligence as a Motivational Tool in English as a Second Language Learning: A Self-Determination Theory Perspective

Abstract

The study examines the concept of Artificial Intelligence (AI) as a motivational tool in English as a Second Language (ESL) learning, and its conceptualization within the framework of Self-Determination Theory (SDT). Language Pedagogy AI applications, such as Duolingo, Grammarly, and ChatGPT, are increasingly becoming part of language learning, making adaptive practice, personalized feedback, and interactive simulations affordable. Although widely used, there are limited empirical studies on the effects of using such tools on learners' motivation in terms of autonomy, competence, and relatedness. The study used a mixed-method design and enrolled 120 undergraduate ESL students in an eight-week intervention. Motivation was operationalized through the use of the Language Learning Orientations Scale (LLOS) and complemented by semi-structured interviews and focus groups. Quantitative analysis revealed that the increase in overall motivation was statistically significant (t (119) = 5.24, p < .001, Cohen's d = 0.65). Additionally, there was a strong increase in autonomy and competence, but the corresponding relatedness did not change. These results were supported by qualitative data, which showed that participants enjoyed flexibility, self-pacing, and corrective feedback; however, they also stated that AI interactions were not authentic and lacked depth. The fact that both quantitative and qualitative data point towards a similar conclusion suggests that AI will foster autonomy and competence but will fail to promote relatedness as a key SDT concept. Therefore, this research finds that AI can be best utilized as an additional motivational tool in the context of blended learning, where interactions with the teacher and other learners provide the necessary social support.