2023-09-12, 15:20–16:20 (Asia/Tokyo), Terrsa Hall A
Since the end of the COVID-19 pandemic, the landscape of STEM (science, technology, engineering, and mathematics) language education has undergone a profound transformation, impacting institutions, educators, and learners alike. In this new environment, institutions are having to consider radical changes to their curricula, accommodating various modes of instruction, including in-person, online, and hybrid formats. At the same time, instructors are having to adapt to these new environments by modifying or completely revising their existing materials, teaching methods, and evaluation procedures. Learners, too, find themselves navigating a vastly altered learning environment, where their interactions with instructors may be extremely limited, and they are expected to conduct much of their learning in a self-directed independent fashion. Even when interaction with instructors does occur, it might be within a completely virtual space that imposes its own constraints on communication modes and participation. These changes suggest a paradigm shift in STEM language education, where the empowerment of learners is a key factor for success.
In this keynote address, I will begin by describing the current state of STEM language education, stressing the importance of communication as a skill, the four pillars of curriculum and course design, and the roles of instructors and learners. Next, I will discuss how various innovations in educational technology and language data science can significantly enhance opportunities for learner empowerment. These innovations not only allow learners define their learning goals but also enable them to practice language skills beyond traditional classroom confines and assist them in producing target language depending on their needs. I will present these innovations with a view towards the technical writing classroom, but I will also touch on applications that can empower learners when developing their speaking skills, focusing on speed, stress, intonation, and pronunciation. Finally, I will conclude the presentation with a discussion of the potential implications of large language models (LLMs) and other breakthrough technologies on STEM language program goals and administration.
STEM, corpus linguistics, language data science, educational technology, keynote
Laurence Anthony is Professor of Applied Linguistics at the Faculty of Science and Engineering, Waseda University, Japan. He has a BSc degree (Mathematical Physics) from the University of Manchester, UK, and MA (TESL/TEFL) and PhD (Applied Linguistics) degrees from the University of Birmingham, UK. He is a founding member of the Center for English Language Education in Science and Engineering (CELESE), which runs discipline-specific language courses for the 10,000 students of the faculty. His main research interests are in corpus linguistics, educational technology, and English for Specific Purposes (ESP) program design and teaching methodologies. He received the National Prize of the Japan Association for English Corpus Studies (JAECS) in 2012 for his work in corpus software tools design, including the creation of AntConc.