LatinCALL24

Since the launch of ChatGPT in 2022, there has been growing interest in the potential role of artificial intelligence (AI) in second language teaching. AI offers unique advantages, such as its ability to cater to individual learning differences and function as a 24/7 support system for both students and instructors. However, before fully integrating AI tools into classroom settings, it is crucial to assess their effectiveness in enhancing language acquisition. This synthesis study addresses this gap by systematically reviewing 113 empirical studies published between 2004 and 2024 that examine the use of AI in second language learning. The study seeks to answer two synthesis questions: (1) What linguistic knowledge and skills have AI tools been used to enhance in second language instruction? (2) What types of AI tools have been utilized in second language instruction? By analyzing these studies, we aim to provide educators and researchers with insights into how AI can be most effectively implemented in language education, ensuring that it supports teaching effectiveness and meets diverse learner needs. The findings will inform both theoretical discussions and practical applications of AI in second language instruction.

The workshop will introduce Luduan.ai, an AI-powered adaptive platform designed to enhance language learning and teaching. We will use Spanish and Portuguese as examples to showcase how generative AI can support the development of the four proficiency subskills  in a given language (e.g., reading, writing, speaking, and listening). The platform offers both teacher and student modes, allowing instructors to adapt lessons to individual learning needs. In addition to skill-building, we will discuss how Luduan.ai's accessibility features ensure inclusive learning environments for all students. The workshop will conclude with an interactive Q&A, giving participants the chance to dive deeper into AI optimization in the teaching of Spanish and Portuguese. 

Text-based, audio-based, and video-based computer-mediated communication (CMC) has become integral to both social and professional interactions. In language education, CMC has been widely used to enhance learners' language production, task-based collaboration, and cultural exchange, with numerous studies documenting its positive effects (Kern et al., 2016; Lin, 2014). With advancements in AI, learners can now engage in more "natural" conversations with chatbots and access features like text suggestions, grammar correction, and instant transcription. When available on both web and mobile platforms, CMC increases the accessibility of communication language learning opportunities. In Language for Specific Purposes (LSP), CMC on mobile devices enables learners to collaboratively complete tasks that resemble real-world scenarios and links formal and informal learning contexts between teachers and students (Krystalli & Mavropoulou, 2020). This presentation reports on a case study where 30 intermediate Spanish learners used Pangea Chat, an AI-powered instant messaging platform, to engage in written, spoken, and listening tasks across six topics related to jobs, medicine, and the creative arts. Preliminary data analyses showed higher levels of engagement and collaboration compared to traditional pen-and-paper classroom activities. Additionally, students used built-in translation and grammar-checking tools during task completion, demonstrating attention to language form during meaning-focused activities, which promotes second language development (Long, 2015). Participants’ post-task reflections also indicated that integrating AI chat tools enhanced their understanding of cultural concepts in the Hispanic world relevant to LSP course objectives.

Since the public release of ChatGPT, language teachers and writing instructors have contended with its possible pedagogic applications and with the challenges it brings to assessment practices. The blossoming literature in the field of AI in Applied Linguistics has veered towards two broad directions: (1) applications of AI into teaching and (2) the extent to which AI can simulate original pieces of writing. In this study, we explore the extent to which the linguistic profile of ChatGPT assignments approximates the linguistic profile of assignments written by linguistics’ undergraduate students in an English as a Foreign Language context. To this end, we compiled two different corpora, one with 54 assignments written for different courses in the linguistic major and another generated with ChatGPT 3.5. For the ChatGPT corpus, we input the same prompt given to the students and collect the AI’s responses.  To compare the linguistic profile of both corpora, we conducted an additive Multidimensional Analysis (MDA) using Biber’s (1988) dimensions, which allows for a broader comparison between different genres. Both corpora were tagged with the Biber Tagger and factors scores were calculated for each text. The results show considerable differences between both corpora. In Dimension 1 (Involved vs Informational production), student writing loads on the positive side (1.34), while ChatGPT assignments load on the negative side (-22.1). This suggests that ChatGPT approximates more academic and professional writing, while student writing is more personal. The MDA also revealed some similarities between both corpora, such as the use of narrative features.

The objective of this study is to present Artificial Intelligence (AI)-based tools and resources with the potential to enhance English vocabulary teaching. The research within the field of language teaching and technology is currently underway. It is justified by the growing influence of AI, not only in people’s daily lives but also in education. The study specifically aims to explore AI’s applications in foreign language vocabulary teaching — an area that has been relatively unexplored in Brazil. The research follows a descriptive and applied approach, utilizing documentary research as the chosen methodological procedure. It is structured into two main stages: (1) an online search conducted to identify materials that explore the intersection between English vocabulary teaching and AI-based resources; (2) based on a Literature Review previously conducted, selection criteria are established for the tools/resources that will compose the final table. This stage also involves critical analysis. The final output will be a structured table that includes AI tools and their potential for teaching English vocabulary. The detailed information provided by the table is expected to facilitate learning and inspire innovative pedagogical strategies. The study seeks to contribute to the practices of English teachers and future educators, fostering discussions about AI’s impact on language teaching. Ultimately, it aims to optimize the English vocabulary teaching-learning process and encourage critical reflection on AI’s role in this domain.

Text-to-speech synthesizers (TTS) have captured the interest of L2 researchers and practitioners for their potential to enhance learning (e.g., Liakin et al., 2017). While previous research has suggested that TTS voices are not comparable to human speech in terms of naturalness (Cardoso et al., 2015; Bione & Cardoso, 2020) and prosodic authenticity (John & Cardoso, 2016), these findings may no longer be relevant considering the recent advancements in generative artificial intelligence (Gen-AI): Gen-AI-based TTS systems can now produce speech that mimics human intonation and emotions (Barakat et al., 2024).