New Possibilities of Artificial Intelligence-Assisted Language Learning (AIALL): Comparing Visions from the East and the West

• Main Authors: Cristina A. Huertas-Abril (Author), Francisco Javier Palacios-Hidalgo (Author)
• Format: Book
• Published: MDPI AG, 2023-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.3390/educsci13121234; 2227-7102
• Keywords: artificial intelligence-assisted language learning; comparative study; culture-related perceptions; qualitative research; teachers' attitudes; Education; L
• Source: Education Sciences, Vol 13, Iss 12, p 1234 (2023)

Despite the benefits of artificial intelligence-assisted language learning (AIALL) for students and teachers, the scientific literature in this field remains relatively scarce, especially regarding the perceptions of language teachers. This paper aims to narrow this research gap by considering the potential cultural differences between in-service language teachers by comparing and contrasting the attitudes of language teachers located in different contexts (i.e., Eastern and Western countries) towards AIALL. Following a qualitative research approach and a descriptive, transversal, and correlational method, a six-question semi-structured interview was designed and administered to unveil the perceptions of six language teachers located both in Eastern (i.e., Vietnam, Iran, and Indonesia) and Western (i.e., Spain, Germany, and the United Kingdom) countries. The findings show that the participants were positive about the potential of AIALL for teaching and learning languages, although they all showed a certain anxiety regardless of their context. Moreover, and although there were shared concerns, differences were found between Eastern and Western participants, especially concerning equitable access, balance between language skills, and ethical aspects. This study reveals that teacher training is essential to introduce AIALL in the classroom, and that practitioners need to rethink assessment to avoid plagiarism and cheating, but also to take advantage of AIALL.