XXIIIrd International CALL Research Conference

Cheryl Brown
Professor, University of Canterbury, New Zealand
Head of School, School of Educational Studies and Leadership

“Navigating the dis(connect): Advancing Equitable and Inclusive Practices in CALL”

Abstract

The potential of digital technologies to support inclusive and equitable CALL has been noted by many. Widening access and participation for everyone by removing barriers and making learning accessible has been a core tenet of the Open Education (OE) movement (Iniesto & Bossu, 2023). It also underpins global policies such as the Education 2030 Framework for Action (Ainscow, 2020). However, whilst digital technologies are integral to daily life for some, significant inequalities persist for others. The reduction of digital divides has obscured the barriers people face to access and participation in education. Professor Brown will draw on her research on digital (in)equality (Brown, 2024) o foreground the critical issues we need to address for digital inclusion in relation to CALL. Her work focuses on developing equitable, evidence-based, and sustainable practices to better prepare diverse learners for living and learning in an increasingly digitally mediated world.

References

Ainscow, M. (2020). Promoting inclusion and equity in education: lessons from international experiences. Nordic Journal of Studies in Educational Policy, 6(1), 7–16. https://doi.org/10.1080/20020317.2020.1729587 
Brown, C., (2024). Technology in education:  Equity and Inclusion in Pacific Education. Global Education Monitoring Report: Background paper. UNESCO.
Iniesto, F., & Bossu, C. (2023). Equity, diversity, and inclusion in open education: A systematic literature review. Distance Education, 44(4), 694–711. https://doi.org/10.1080/01587919.2023.2267472 

Lawrence Jun Zhang
Professor, University of Auckland, New Zealand
Editor of the System journal

“Ethical and Emotional Responses to AI Integration in Language Education: Insights from a Qualitative Case Study and a Q Methodology Investigation”

Abstract

As artificial intelligence (AI) technologies become increasingly embedded in language education, their ethical and emotional implications for teachers demand closer scrutiny in different educational contexts. To address this issue, I  draw on two complementary studies on Chinese university English language teachers’ ethical appraisals and emotional responses to AI integration. The first study adopted a qualitative case study approach, comprising two rounds of semi-structured interviews. In the initial round, interviews with 15 teachers identified broad patterns of ethical-emotional responses. This was followed by in-depth interviews with three purposively selected participants to further explore emergent themes. Thematic analysis revealed a cross-patterned synthesis linking emotional responses to key ethical principles: Challenge Emotions and Achievement Emotions were primarily associated with Beneficence, while Deterrence Emotions and Loss Emotions were predominantly linked to Non-Maleficence, Autonomy, Justice, and Explicability. To further explore teachers’ perceptions of AI’s ethical challenges, the second study employed Q methodology with 30 university English language teachers. Participants sorted statements related to AI Data, AI Models/Algorithms, AI Pedagogy, and the Socio-Technical Context according to their level of dissatisfaction. The analysis captured a diverse range of subjective viewpoints, revealing nuanced tensions between individual agency, institutional structures, and the broader socio-technical framing of AI use in education. Together, these two studies offer a more holistic understanding of the ethical and affective dimensions of AI integration into language education. The findings underscore that achieving ethically responsible and emotionally sustainable AI adoption requires promoting active collaboration through context-sensitive policy development, targeted professional learning, and inclusive multi-stakeholder partnerships.

Mark Pegrum
Professor, University of Western Australia, Australia
Deputy Head of School (International), Graduate School of Education

“Where Do Humans Fit In? CALL, AI and Human Agency”

Abstract

The balance between human agency and AI agency is one of the most important issues in contemporary education, and is closely linked to questions of diversity, equity and inclusion. This presentation will investigate the growing integration of AI into language education, with a focus on developing digital literacies, building co-intelligence, and practising design justice. We will begin by taking a step back to observe the big picture of our contemporary era, viewing it through three intersecting frames – the postdigital, the posthuman and the sociomaterial – and asking how these might help to inform our understandings of human and AI agency. We will go on to consider humanity’s two major encounters to date with AI, their impact on the so-called personalisation of both our networks and our learning, and the implications of such personalisation in terms of personal agency. It will be shown that personalisation may not in fact be a suitable term or concept to describe or capture these developments. Following on from these considerations, we will turn to our main focus: three possible strategies that we as language educators can promote with, and for, our students. These include developing AI literacy to build and bolster human agency; promoting co-intelligence to balance human agency and AI agency; and practising design justice to develop human agency for the marginalised. Numerous examples will be provided to demonstrate the implementation of these strategies in everyday language teaching and research settings. In this way, we can capitalise on the benefits of AI while tempering its drawbacks, as we work to build human agency and promote diversity, equity and inclusion.

Chun Lai
Associate Professor, University of Hong Kong, Hong Kong
Associate Editor of the Computer Assisted Language Learning journal

“Inclusivity in and via CALL: Supporting Personalization”

Abstract

Inclusivity is essentially about challenging the myth of ‘the average’ and supporting individual uniqueness to gain an edge in life. Personalization is hence a key theme of inclusivity. Personalization is not just about the adaptivity of learning process, but more importantly about self-defined outcomes towards personal fulfilment. These two different conceptualizations of personalization stand for different ideological stances towards the purpose of education. The outcome-orientation personalization emphasizes moving away from external control and standardized approaches, focusing instead on empowering learners to take charge of their own learning through self-direction and agency. In this backdrop, an important dimension of inclusive CALL is to create learning experiences that support agentic engagement in self-directed personalization of learning. This dimension of inclusivity is especially relevant and meaningful nowadays, given that self-direction and agency are key competences in the GenAI era. Drawing upon existing literature on learners’ self-directed learning with GenAI, we will discuss key considerations in supporting self-directed personalization of learning with GenAI. These key considerations revolve around empowering learners to imagine new possibilities with AI, creating conditions of possibilities, and adopting a fixer positioning. Going beyond GenAI, we will explore examples of inclusive CALL solutions that support learner agency in self-directed personalization of learning, and discuss the critical roles teachers play in empowering this aspect of inclusivity via CALL.