María Amparo González

Within the framework of ongoing technological advancements and their integration into education, the conference ‘Technology-Enhanced English Language Teaching’, held as part of the 3^rd International Congress Transits: Identities and Cultures in Motion —Humanities and Progress from the Analog to the Digital Era— offered a detailed analysis of how Generative Artificial Intelligence is transforming the teaching of English as a second language (L2). This analysis is grounded in a combination of educational theories and practical examples of technology use, offering both insights into its opportunities and challenges, particularly within university settings.

One of the cornerstones of the conference was the presentation of the PPI methodology (Plan, Personalize and Implement), which provides a framework for maximizing the potential of AI in university environments. Collins and Halverson (2018) point out that planning involves the analysis and alignment of content with the available tools, while personalization allows resources to be tailored to the individual characteristics of students, —a key aspect when using technologies such as adaptive learning systems (Luckin et al., 2016). The effective implementation of AI depends on the proper integration of tools such as chatbots, adaptive platforms and automated assessment systems, fostering a hybrid environment that enables innovation in the classroom (Kukulska-Hulme & Traxler, 2019).

In various educational contexts —face-to-face, hybrid and online— Generative AI plays a crucial role. Knewton and Smart Sparrow, for example, are two platforms that, although both geared toward adaptive learning, offer different approaches: Knewton focuses on the personalization of educational content through advanced data analysis (Mills & Garrison, 2021), while Smart Sparrow is centred on creating interactive and individualized learning experiences. These platforms facilitate both autonomous learning and teacher intervention, providing tools for continuous monitoring of student progress.

Motivation is essential in second language acquisition, and AI has reframed some of the main theoretical constructs in this field. Self-Determination theory (Ryan & Deci, 1985) highlights how artificial intelligence can foster autonomy and intrinsic motivation by providing personalized learning experiences and immediate feedback (Ryan & Deci, 2023). Moreover, platforms such as Busuu and HelloTalk promote cultural integration and authentic learning, enabling learners to connect with native speakers, which reinforces integrative motivation (Gardner, 2023).

Self-Efficacy Theory (Bandura, 1997) is also fundamental in analysing the impact of AI. Tools such as Replika, with an adaptive learning system, provide learners with continuous feedback that enhances their confidence and motivation (Bandura, 2024). This type of interaction fosters a sense of competence and autonomy, key to foreign language learning.

AI has profoundly transformed the dynamics of interaction in English language teaching. In teacher-IA interaction, AI acts as an assistant by providing detailed analytical data that allows educators to adapt their pedagogical strategies in real time (Selwyn, 2019). In terms of student-IA interaction, tools such as ChatGPT and Replika offer constant practice of communicative skills, facilitating an adaptive learning environment and providing instant feedback (Heffernan & Ostheimer, 2021).

Platforms such as ImmerseMe combine virtual reality technologies and deep learning to provide immersive experiences, simulating real-life situations that help learners improve their language competence in a safe and controlled environment (Peterson, 2021). These types of tools allow constant exposure to the language and support second language acquisition in a more natural and motivating way.

The integration of AI into English language teaching requires consideration of several essential components, such as digital literacy and critical thinking (Redecker & Punie, 2023). Digital literacy involves developing both technical and ethical skills in the use of AI technologies, ensuring that students become informed and responsible users (UNESCO, 2023). Likewise, the incorporation of AI must be accompanied by the development of critical thinking so that both teachers and learners can evaluate and reflect on the ethical and pedagogical use of these tools (Bennett et al., 2023).

Technology infrastructure, ethical and privacy considerations, and an educational culture open to innovation are also critical components for successful adoption of AI in education. These elements ensure that the technologies are accessible to all students, promoting equitable and responsible use in the classroom. Finally, both opportunities and challenges in the implementation of AI in English language teaching were discussed. AI has the potential to increase learners’motivation by providing personalized and dynamic learning experiences, as well as immediate feedback, which contributes to a sense of continuous progress (Van der Kleij et al., 2024). However, technological dependency, lack of human interaction, and algorithmic bias, are challenges that must be considered to ensure the equitable and ethical integration of AI in education (Kohnke & Moorhouse, 2023; Selwyn, 2024). Throughout the conference, we have examined how AI can transform English language teaching, offering both innovative tools and challenges to consider. Future lines of research should focus on how to harness these tools ethically and how to promote a balance between the use of technology and human interaction in order to achieve meaningful and high-quality learning.

*This translation has been revised by María Amparo González Rúa from the original Spanish version, which can be consulted here.