Navigating AI-assisted language learning through Computational Thinking Skills in Computer Assisted Language Learning (CTsCALLs): A qualitative investigation of learner perceptions

Abstract

Computational thinking (CT) is the heart of 21st-century digital skills, serving as an essential problem-solving skill that enables users to address challenges using information and communication technologies (ICTs). Recently, CT has been recognized as a critical skill within STEM education; however, scholars in computer-assisted language learning (CALL) and applied linguistics have developed a specialized framework known as computational thinking skills in computer-assisted language learning (CTsCALL). Despite its novelty and potential, this innovative framework has garnered limited attention. For this reason, we integrated CTsCALL into our language teaching practices and aimed to cultivate these skills among 104 Iranian EFL learners in the context of Artificial Intelligence Language Learning (AILL). The results of the content analysis indicated that participants perceived skills such as algorithmic thinking, abstraction, collaboration, evaluation, and generalizability as facilitating their ability to achieve higher levels of reliability, trustworthiness, and individualized learning patterns while engaging with AI to accomplish learning tasks. Based on these findings, the study provides qualitative support for the relevance of the CTsCALL framework within language learning contexts and suggests that CTsCALL may offer a promising approach for addressing challenges associated with passive language learning and AI hallucinations in AILL.