While the practical value of English as an academic lingua franca is generally recognised, studies highlight negative consequences for non-native English speaker (NNES) university students and staff. These include difficulties communicating clearly in English and time spent learning it (Tardy, 2004), as well as the additional time required to do academic work in English (Amano et al., 2023). In Hong Kong’s English medium instruction (EMI) tertiary environment, a disjunction exists between the language of instruction and the proficiency and preferences of L1 Cantonese students (Evans & Morrison, 2011). Two thirds of secondary schools and most primary schools use Cantonese (Shephard & Rose, 2023), often leading to English proficiency depending on families’ socioeconomic background and extracurricular support (Li, 2018). Increasing enrolment of L1 Mandarin and international students has complicated matters further, and students often rely on translation, proofreading and paraphrasing applications to cope. The emergence of Generative Artificial Intelligence (GenAI) has also been met with enthusiasm by the Hong Kong government and local university administrations and can be perceived as improving academic equity for NNESs (Berdejo-Espinola & Amano, 2023). However, is GenAI an innovative technology helping to improve educational equity or a shortcut negatively impacting learning? This study investigates perceptions and use of GenAI of students from four English Language Centre subjects (n=76). Data was collected from pre- and post-course surveys, interviews, reflections, GenAI transcripts, and written assessments over two semesters. The findings suggest that while students are generally aware of ethical issues and limitations, they are increasingly adopting GenAI and positively view its convenience and efficiency for brainstorming, research, organisation and language use. However, few question GenAI’s impact on their overall learning. This presentation explores the growing disconnect between task performance and proficiency, and the extent to which GenAI-enhanced teaching and learning sustainably addresses the equity gap in globalised education.

The rapid progress of generative AI (GAI) has raised significant questions regarding its impact on teaching. As these tools become integrated into practice, educational institutions are challenged to rethinking their pedagogical approaches. Universities need to develop strategies to support faculty in integrating GAI to enhance teaching. In this context, an Estonian University formed a taskforce to address these issues.
A survey was developed and distributed online in February 2024 to understand teacher perspectives and practices about GAI tools in their classrooms. Out of 2479 staff members, 413 completed the survey. The taskforce aims to provide training for staff based on the collected responses and the survey will be repeated after one year to evaluate the effects of these training.
Our study aims to answer the following questions:

1. What are the main concerns identified by teaching staff regarding the use of GAI tools in their teaching practices?
2. How have these concerns and practices evolved over the course of a year?

Our initial survey results show that half of the respondents (48%) do not use GAI in their teaching nor regulate its use for students. The main reasons include uncertainty how to use GAI effectively, distrust in the information provided, and the belief that their subject is unsuitable for GAI integration. Some respondents reported unsatisfactory results from using GAI or found traditional teaching practices more effective. When asked about topics for staff training, respondents expressed interest in practical recommendations for effective GAI use and in understanding the connection between GAI tools and academic fraud.
Our study reports on the results obtained from the second survey comparing them with the initial findings. We aim to highlight the change in teacher concerns and practices. Based on these findings, we will offer recommendations focussing on professional development; policy guidelines on GAI use; equitable access to GAI tools.

Research Aim & Theoretical Framework: This presentation features findings from a bilingual, critical meta-analysis of global educator Ikeda Daisaku’s (1928–2023) publications on A.I. relative to ningen kyōiku, or “human education.” Comprising aims and methods of dialogue, value creation, creative coexistence, and a locally enacted global consciousness, Ikeda’s philosophy of human education centers on the persistent cultivation of fully human being and becoming in self and others, teacher and taught. Responding to the theoretical framing of “posthuman” converges of natural, social, and technological dimensions of human life and living (Snaza, 2015), this study provides teachers and teaching uniquely Eastern, quintessentially universal ways of engaging with A.I. that do not forsake or erase what makes us fundamentally human. Analyses center on two interlocking questions to which Ikeda consistently returns when assessing the impact of A.I. and the hyperfocus on reason and rationality underpinning and engendered by it: What does it mean to be human? and What is the nature of civilization and humanity?

Methods

The effects of A.I. and enhanced computerization on humanity and education abound in the popular and academic discourse. Ikeda has examined A.I. since the 1970s, but these works are inaccessible to the anglophone academy. This study employs bilingual-bicultural and critical discourse analyses (Rogers, 2004) of Ikeda’s 150-volume “Complete Works,” identifying his engagements with A.I., systematically coding, triangulating, and synthesizing these thematically.

Findings

Ikeda advocates practices of cultivating intuition, reestablishing human interactions in reality, developing creativity, and restoring the shigokoro, or “poetic mind/heart/spirit,” to enact justice and remedy and forestall what ails civilization and hinders human happiness in the expansion of A.I.

Relevancies

This study enhances our understanding of A.I. relative to the conference theme of teaching quality, socio-cultural identities, and what makes us uniquely human. It provides innovative, Eastern approaches for addressing social justice and leveraging technology.

Artificial Intelligence (AI) has been introduced in education recently. With its incorporation in the educational process, opportunities as also challenges have been arisen for teaching and learning. The research on AI in education aligns with equitable teaching practices by offering personalized learning experiences and enhancing engagement, but it must also address issues of access, cultural responsiveness, and teacher support to ensure inclusivity for all students. This research explores the impact of AI applications on both cognitive and non-cognitive skills of elementary school students. A systematic literature review was conducted, focusing on studies published since 2019, to gather insights into how AI technologies and AI educational platforms are integrated into primary schools and their subsequent effects on student learning. For a study to be included in the review had to be published after 2019, to examine an intervention with AI in elementary schools and be published in English language. For this purpose, experimental and quasi-experimental studies were identified. The results showed that these interventions were typically of short-term and utilized diverse AI-based tools, such as dialogic systems, AI-driven educational platforms, robotics, and educational games. The majority of these interventions concentrated on subjects like Language and Mathematics, aiming to assess the effectiveness of AI in enhancing learning outcomes in these core areas. The findings of the systematic literature review are generally encouraging, indicating that AI has the potential to positively influence student learning in primary education. The use of AI tools was associated with improvements in both cognitive skills, such as problem-solving and critical thinking, and non-cognitive skills, including motivation to learn and engagement in educational process. Despite these promising results, the review also highlights the need for further research to better understand the long-term effects of AI interventions, as well as their applicability across a broader range of subjects and skills.