Embracing the Inevitable: Tips for EFL and ESP Learning with AI
This research aims to present practical pedagogical strategies for using AI language learning tools that are free or have free versions (e.g., Speechace, Diffit, Newsela) and ChatGPT for both EFL and ESP learning, focusing on improving students’ receptive and productive language skills. The benefits of these AI tools are illustrated with examples from the author's teaching practice. The practical suggestions for EFL and ESP teaching and learning with AI are examined through the theoretical framework of AI-Enhanced Adaptive Language Teaching, an integral component of transformative and innovative pedagogy in (higher) education. This framework empowers language learners to find their paths toward successful lifelong learning in ever-evolving technological contexts. A study was conducted with a research group of adult students who are current or future security professionals. Its results demonstrate AI tools' statistically significant positive impact on students’ language learning, particularly writing, speaking, and reading skills. The primary method employed in EFL and ESP learning with AI is Task-Based Language Learning, in which students are assigned specific tasks (e.g., writing an email or essay, using new terms in context) and use AI language tools with multimedia interfaces to receive immediate feedback and improve their skills without the pressure of teacher supervision. This method allows for analysis and reflection on the language used during task completion, which is especially valuable for adult learners. The study results can inform English language educators seeking to integrate modern AI technologies into their classrooms.
Authors
- Valentina Georgieva (ORCID: https://orcid.org/0000-0001-8392-9613)
Institutions
- G. S. Rakovski National Defence College (BG)
Publication Details
- Journal
- E-Learning Innovations Journal.
- Published
- 2025-03-25
- DOI
- https://doi.org/10.57125/elij.2025.03.25.05
- Citations
- 1
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.48