Hoan Kiem Lake, Hanoi, Vietnam. Photo by Mark Pegrum, 2024. May be reused under CC BY 4.0 licence.
GloCALL Conference
Hanoi, Vietnam
22-24 August, 2024
Unsurprisingly, the 2024 GloCALL Conference in Hanoi was dominated by discussions and debates about generative AI, as educators and educational institutions seek to come to terms with its uses and challenges. While there was a general acknowledgement that genAI is having and will continue to have a major impact on education, numerous speakers sounded notes of caution about the need to keep its novelty and power in perspective, to use it in line with established pedagogical principles, and to be wary of its pitfalls.
In his opening keynote, The transformative role of technology in language teaching and learning: Seeing through the hype, Glenn Stockwell began by noting that digital technologies change how and what we learn, and even our goals for learning, but they may sometimes sit beneath the surface of our awareness. He spoke about the rapid development of generative AI, and indicated that there are sometimes differences in teacher and student perspectives – teachers may worry that students will cheat, while students worry that they will be accused of cheating. Educational institutions are currently sending mixed messages about genAI; clear guidelines for usage are needed. He mentioned the AI paradox: the idea that teachers are using AI to create tasks that students are using AI to complete. He also mentioned Bryson and Hand’s 2008 notion of false engagement: students may engage in tasks simply for the sake of completing them, if they don’t fully understand their pedagogical purposes.
Although genAI brings enormous changes, we can learn a lot from discussions of the arrival of past educational technologies, and should remember that good pedagogical practices must remain the core of what we do. Among its possible pedagogical uses, genAI can be used as a writing assistant, or as a chatbot to provide non-judgemental feedback. However, he suggested that the relationship between technology and autonomy is tenuous; it is doubtful whether genAI promotes learner autonomy, though it is certainly used by autonomous learners. It is definitely necessary to rethink assessment, and ensure it is preparing students appropriately for today’s world. We should consider assessing both the process and the product.
Current research on AI in language education is still largely focused on perceptions and impressions, but we need research on actual practices. Teachers, meanwhile, have a sense of precarity with technology (Stockwell & Wang, 2024), with concerns over job security, funding cuts, workload, and training. This raises the issue of digital wellbeing in an AI era (Bentley et al., 2024). Legal and ethical issues also loom large. Much more discussion is needed of these issues, locally and globally.
In his plenary, Artificial intelligence in the language education context of Vietnam: From theory to practice, Nguyen Ngoc Vu traced the history of the development of neural networks from the early 1980s onwards, explaining the increasing parameters as GPT was developed. He referred to the biological theory of emergent properties (Saltzer & Kaashoek, 2009), that is, properties not present in the individual components of a system, but which show up when those components are combined. He argued that large language models (LLMs) have the potential to dramatically impact the landscape of education. One issue with the production of certain materials, such as videos, is that AI-made materials may seem too perfect in comparison with human-made materials.
He demonstrated the TARI AI Tools developed by the Training and Applied Research Institute (TARI) at the Ho Chi Minh City University of Foreign Languages and Information Technology (HUFLIT). These include chatbots for general university inquiries; teaching assistant chatbots with domain-specific knowledge; and healthcare chatbots that can draw information from reputable health information sources. He then went on to demonstrate tools designed to improve the teaching of linguistics, such as tools to parse or analyse texts according to particular linguistic frameworks. Students who have tried these tools have reacted positively but have stressed some ethical issues: the need for informed consent, anonymisation, legal/copyright compliance, review by ethics boards, and transparency and training.
In his presentation, The impact and perception of using an AI writing platform to improve narrative essay writing performance, Wang Yi (with his supervisor, Kean Wah Lee, as a co-author) described an AI narrative writing prototype tool called ‘Tale-It’, where students answer set questions step-by-step, describing the opening scene, setup, inciting incident, and so on. Students also have the option to obtain suggestions for improving their expression in terms of vocabulary or grammar. Students are able to compare their own original stories and the AI-supported stories side-by-side. In a study to examine the effect of the AI tool on improving students’ narrative writing, a significant pre-test to post-test improvement was found. In a study of student perceptions involving a survey enriched by interviews, all participants agreed that the tool improved their writing, two-thirds that it improved their confidence, and the majority that it helped facilitate their understanding of narrative structure and increased their creativity. Ultimately it improved not only their writing performance, but their understanding of genre structure, creativity, confidence in their storytelling abilities, their expression and grammar.
In his presentation, Generative AI-powered critical reading in academic contexts: An exploratory study, Haoming Lin listed some affordances of genAI technology: contextual understanding, coherent responses, reinforcement learning by human feedback, and a multilingual environment. He described three levels of reading comprehension: literal meaning, interpretative/inferential meaning, and evaluative/critical meaning. He reported on a pilot study in China examining which dimensions of critical reading postgraduate students found most and least supported by ChatGPT, and what the best and worst aspects were of using ChatGPT for critical reading support. Students were provided with readings and critical reading reports from a GPT-based Chrome extension app, Full Picture, which analyses papers according to overall reliability, reading time, three takeaways, content analysis, trustworthiness and bias check, and research topics. Students felt the app helped them to evaluate the arguments, evidence and generalisability of texts, but didn’t provide much help in comparing and contrasting the findings with others’ work, or evaluating how well theoretical frameworks were applied. At the literal level, it can provide sometimes irrelevant but new perspectives and allow quick comprehension; at the interpretative level it could be relevant to personal reading goals, inspire readers, and answer questions; and at the evaluative level it can align with personal beliefs in critical reading. Ultimately what is needed is a partnership with AI rather than relying on AI; development of AI literacy; and development of critical reading and writing together.
In my closing keynote of the conference, Not a(nother) revolution! Generative AI, language and literacy, I wrapped up our discussions of genAI by arguing that it will not revolutionise education (any more than any previous technologies have done) but that, used appropriately, it could help to support the evolution of education in areas where change may be needed. I began by looking at the technology itself and how it is developing and is likely to develop in the future; then I looked at the educational and assessment implications, and concluded that the future of study and work will belong to human-AI collaborations; and finally I looked at the societal and environmental implications, and stressed the need to maintain a critical perspective on genAI tools. Ultimately, all of us, educators and students, need to develop the AI literacy to ensure that genAI is being used appropriately and effectively to support the ongoing evolution of education.
In her presentation, Advancing TPACK: Unravelling contextual knowledge (XK) among Indonesian secondary school teachers, Ella Harendita (with her supervisors, Grace Oakley and myself, as co-authors) explored how teachers at various schools develop and employ their different levels of contextual knowledge. This XK influences their approaches to content (e.g., knowledge about students’ daily lives and values), pedagogy (e.g., knowledge about students’ learning preferences and levels of ability), and technology (e.g., knowledge about students’ technology access and interests). She concluded that teacher agency is a driving force in XK development; that teachers capitalise on the relational, collectivist culture of Indonesia to develop XK; that teachers engage in self-directed professional learning, for example on social media; and that classroom contexts are the major determining factors for teachers’ pedagogical decisions.
In his featured presentation, ‘I take it as a defeat if I work alone’: CALL, co-operation and professional development, Chau Meng Huat referred to Anne Burns’ statement that TESOL has only recently undergone a ‘collaborative turn’ in professional development and research. He spoke about key beliefs which can underpin successful collaborations, including positive interdependence (from the area of co-operative learning), abundance not scarcity, being more rather than having more, and kampung (community, village) spirit. He finished by quoting Betsy Rymes’ comment that we need to move from ‘applied’ to ‘collaborative’ linguistics. He suggested that issues of diversity, equity and inclusivity come to the fore in such collaborative approaches.
In his keynote, Integrating CALL to teach ESL and STEM: Interdisciplinary critical pedagogical approach, Kean Wah Lee described a design-based research project based on McKenney and Reeves’ 2019 framework, using four stages: analysis and exploration; design; implementation; and evaluation and reflection. Such a project, he said, has a collaborative, iterative nature focusing on practical application.
He stressed the importance of a project being tailored to its context, and he spent some time describing the issues for STEM learners in Malaysia, many of whom face discipline-specific language challenges. In addition, heterogeneous learners – some with interrupted schooling or trauma – need tailored English support. Work is underway on trying to shift teacher-centred approaches towards inquiry-based learning involving active participation and critical thinking. Educational strategies must focus on enhancing language proficiency alongside STEM content learning. Indeed, the integration of STEM and English language teaching has emerged as a global trend in recent years, to support student success in both areas, but there is still a need for more research in this area. He proposed an interdisciplinary multiple learning approach (bringing in blended learning, CLIL, PBL, IBL, and project-based learning) involving CALL/technology, which allows for multimodal teaching and innovative pedagogical practices. But this must also be a critical pedagogical approach, drawing on critical theory, and involving critical pedagogical competence, critical technological competence, and critical cross-cultural communicative competence.
He described a key project outcome, namely the Gene Detective e-Learning Module/Toolkit for STEM-EL; each ‘capsule’ in the digital platform involves a pre-test, a video, interactive activities, a virtual experiment and a case study, and is accompanied by hard copy activity books (these are extremely important in low bandwidth areas). The project is now in an evaluation stage. Students have reacted positively to the materials to date. Data collection is ongoing to improve the toolkit and make it culturally appropriate and relevant for classroom use. It is hoped that it can eventually be adapted for use in Malaysian school biology classrooms.
It was a conference full of informative presentations and rich discussions. It will be interesting to see how our discussions of technology in education – and especially genAI in education – have continued to evolve when we gather again at future GloCALL conferences.
