Using Artificial Intelligence Tools in Virtual English Learning: The Case of a Tutoring Project

Abstract

In today’s digital age, artificial intelligence (AI) has expanded in every area of education and English language teaching and learning are not the exception. Currently, English language teachers have thousands of resources available to prompt the use of AI tools to create follow-up exercises, complete lesson plans and warm-ups for their classes. Similarly, language learners benefit from AI by accessing tools that provide them with autonomous and personalized learning experiences. This qualitative research delves into the experiences of high school students enrolled in an English learning tutoring project offered by a public university in Costa Rica, and the tutors working in the project. This project is led by pre-service teachers who tutor students virtually on a weekly basis. The research question that drove this case study was: To what extent do AI tools contribute to the English learning process during virtual tutoring sessions? The data collected corresponded to the perceptions of 10 high school students who attended sessions for a 12-week period, and in some of the sessions, students were introduced to applications and websites powered by AI. The perspectives of two tutors were also considered. The data, which were collected by means of a focus group and one-on-one interviews, revealed more opportunities than challenges. One clear opportunity was that in virtual sessions with a great number of students, AI tools became an ally since students highlighted the importance of receiving real-time feedback, increasing their autonomy, and enhancing their overall engagement.

Presenters

Evelyn Valverde
Student, Master, Universidad Nacional, San José, Costa Rica

Hillary María Lizano Mora
Student, Bachelor´s Degree, Universidad Nacional, San José, Costa Rica

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

Technologies in Learning

KEYWORDS

AI TOOLS, PRE-SERVICE TEACHERS, ONLINE LEARNING, AUTONOMY, REAL-TIME FEEDBACK