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2025: ASCILITE 2025 Conference Proceedings

The Proceedings of the 2025 ASCILITE Conference

S. Barker, S. Kelly, R. McInnes & S. Dinmore. (Eds.). Future-focused: Educating in an era of continuous change. Proceedings ASCILITE 2025. Adelaide. Adelaide Convention Centre, Adelaide, Australia. November 30 - December 3 2025. https://eventstudio.eventsair.com/ascilite-2025

Published: 28 November 2025

Full Issue

ASCILITE Conference - Concise Papers

  • Identifying conflicting demands for a balanced teaching approach

    Duncan Murray, Karen Williams, Gediminas Lipnickas

    This paper introduces the preliminary development of the Teaching Balance Model (TBM), a conceptual framework to help educators navigate competing discourses in contemporary higher education. Developed through grounded theory methods combined with individual and collaborative reflection, the TBM responds to tensions heightened by increasingly complex teaching environments—particularly in technology-enhanced, online, and hybrid contexts. Rather than viewing challenges such as theory versus practice, learning versus assessment, or students as partners versus customers as binary oppositions, the TBM encourages an integrative approach. Data were generated through reflective memos and coding of teaching decisions and rationales from three business academics with experience across online, hybrid, and face-to-face settings. Through iterative coding, constant comparison, and theoretical sampling, key categories—such as value priorities and decision-making rationales—emerged to inform the model. The TBM proposes a balanced middle ground that supports inclusive, values-driven teaching while acknowledging systemic pressures. We discuss the model’s potential as a reflective tool for practitioners and its future development for research into academic identity, wellbeing, and institutional culture. The TBM aims to contribute to conversations about sustainable and equitable teaching practice in digitally mediated learning environments.

  • Enhancing student retention through predictive analytics and outreach: A case study in early intervention in online postgraduate studies

    Leanne Ngo, Gustavo Batista

    This paper presents a case study of a predictive analytics pilot aimed at improving student retention in postgraduate online learning. By leveraging Learning Management System (LMS) engagement metrics, students who had not accessed or submitted their first assessment at least five days before the due date, were flagged for early outreach. A tiered human-led interventions model via email, phone, and SMS were triggered to provide personalised support. The pilot was implemented across 12 postgraduate subjects in 2025 and benchmarked against 2024 cohorts. A 1.9 percentage point improvement in dropout rate was observed, equating to approximately 32 additional students retained. These findings highlight the practical value of low-complexity, data-informed interventions and the role of AI-human synergy in supporting online learners. This pilot demonstrates a scalable approach to integrating predictive analytics with personalised support in fostering adaptable learners and improving student outcomes, particularly in resource constrained settings.

  • Flagged by design? The intersection of gender, racial and neurodiversity bias in AI proctoring and academic judgment

    Mark Gorringe, Karen Williams, Duncan Murray

    While academic misconduct prevention has traditionally focused on student behaviour, limited attention has been paid to the role of educator judgment—particularly under the influence of implicit bias and AI-generated suspicion. As online proctoring software becomes more prevalent, concerns arise regarding systemic disadvantages experienced by specific student groups, particularly female students, students of colour, and neurodiverse learners. This positioning paper explores how AI-driven proctoring technologies, combined with the cognitive demands on academics, may inadvertently amplify reliance on bias and heuristic judgment in academic misconduct decisions. Emerging evidence suggests that certain student groups are disproportionately flagged by proctoring systems and subjected to harsher scrutiny, raising concerns about procedural fairness and equity in online assessments. Rather than reporting empirical findings, this paper outlines a research agenda to investigate how identity-related cues influence both AI flagging and academic judgment. We propose a mixed-method approach—combining meta-analysis with vignette-based quasi-experiments—to critically examine the intersection of bias, surveillance, and academic integrity.

  • Building educator capability for meaningful AI integration

    Toni Jones, Bill Simmalavong

    Generative AI (GenAI) is reshaping the practice of teaching and learning in higher education, creating new possibilities alongside significant complexity. While interest in AI tools continues to grow, meaningful adoption relies on approaches that are grounded in pedagogy, flexible, and responsive to context, rather than on technical proficiency alone. This paper reports on a project to embed AI capability development for educators, into existing professional learning programs, positioning AI as a tool to extend and enrich, rather than replace, innovative teaching practices. The project focuses on creating opportunities for educators to explore, test, and adapt AI tools within their specific teaching contexts, moving beyond generic training that often fails to address the complexities of practice. Design principles and implementation strategies prioritise equity, educator agency, and engagement, supporting sustainable and inclusive professional learning in online education. Early insights highlight the value of integrating AI capability into pedagogical initiatives rather than treating AI as a stand-alone technical skill. The outcomes of this work contribute a practical model for AI capability building that can inform future professional learning and institutional strategies for adaptable and innovative teaching in an era of continuous change.

  • Investigating the rationale for using online quizzes: The case of UniSA

    Bopelo Boitshwarelo

    Research on online quizzes has surged in recent years, focussing on providing pedagogical insights and success stories. While these studies indicate educational benefits of online quizzes, most of the empirical ones are focused on a single course as opposed to institution-wide studies. This study sought to investigate the pedagogy underpinning the use of online quizzes by academics by examining their authentic assessment statements. The analysis of over 2,500 words of academic statements demonstrated that quizzes are primarily designed to assess comprehension and application of knowledge, reflecting their strong pedagogical role in facilitating acquisition and practice types of learning.

  • Supporting the hidden curriculum: A layered open microlearning design model for inclusive learning in higher education

    Alison Lockley

    The hidden curriculum includes unspoken and unwritten expectations that can impact student success, often reinforcing inequities in marginalised student groups. While often overlooked when enacting curriculum, addressing the implicit learning requirements of hidden curriculum is crucial for fostering inclusive and equitable academic experiences. Drawing on existing literature and case studies at Charles Darwin University, this paper presents a layered design model for Open Microlearning (OML) as a novel approach to explicitly support and scaffold hidden curriculum in higher education. OML combines Open Educational Practice with microlearning principles to provide quick, flexible, and bite-sized learning experiences using freely available, reusable resources and encourages collaboration with others. The layered model supports modular and accessible design, grounded in pedagogical intent and responsive to diverse learner needs. The layered structure allows for a clear separation of key components within the design, enabling focused attention to enhance overall coherence and effectiveness. The flexibility and adaptability of the OML layered model enables just-in-time learning to bridge hidden curriculum gaps and empower students to engage meaningfully with their learning and assessment.

  • From resistance to resilience: A proposed study for supporting VET educators in Virtual Reality Adoption through inclusive professional development

    Ke Xu, Michael Cowling, Shweta Singh

    Virtual Reality (VR) technology is transforming Vocational Education and Training (VET) by providing immersive and engaging learning experiences. However, its successful integration depends not only on technological adoption but also on fostering resilience and adaptability among educators and learners in the face of rapid technological change. This proposed study will explore strategies for upskilling VET educators in VR, focusing on resilience, social-emotional well-being, and supportive professional development (PD). Using a mixed methods approach, this research will combine quantitative surveys and qualitative interviews to examine how VET educators can develop resilience and adaptability in VR-based training and assessments. The study will examine digital competency in Australia’s VET workforce by analysing survey data, mapping VR tools for trainers’ PD, and evaluating existing VR training opportunities. The study will contribute to strategies ensuring VET professionals equipped with the knowledge and skills needed to thrive in the digital age and the VET sector remains responsive to industry demands to prepare the learners to be part of a dynamic workforce.

  • From vision to reality: Shaping future nurses through co-design and programmatic assessment

    Michelle Pedlow, Olivia Gallagher

    The University of Western Australia aims to launch its first undergraduate nursing degree in 2026, co-designed from inception and underpinned by programmatic assessment for learning. This course was developed in direct response to sector-wide disruptions, including generative artificial intelligence, workforce challenges, assessment reform, and evolving healthcare demands. Instead of adapting existing models, we created a curriculum intentionally designed to equip students to navigate and thrive in complex environments. This paper traces our design journey, from co-design with clinicians, educators, nursing alumni, and community partners to the creation of a cohesive, feedback-rich assessment system. Key features include low-stakes assessments, structured academic mentorship, course portfolios, case-based vivas, and holistic progression panels. These components empower students to integrate feedback, track their development, and build professional identity over time. We also address the policy tensions encountered, particularly the misalignment between course-level progression and traditional unit-based governance. Through adaptive moderation processes and strategic alignment with institutional frameworks, we established a robust model that balances innovation with compliance. This case study offers a scalable, future-focused approach to curriculum reform for professionally accredited programs, one that prioritises student growth, industry alignment, and sustainable practice in an era of ongoing change.

  • Let it break: What fractures reveal about the future of assessment in the age of GenAI

    Justine Maldon, Michelle Pedlow, Rebecca Scriven

    The emergence of generative AI has not broken assessment systems in higher education; it has exposed long-standing fractures. Overly complex tasks, excessive assessment demands and staff overload point to a system that has privileged compliance over human connection. This position paper acknowledges that brokenness but looks beyond it. Inspired by the Japanese art of Kintsugi, where cracks are repaired with gold, we ask: what if these fractures are openings for stronger, more relational practices to emerge? Adopting an autoethnographic lens, we draw on our experiences in curriculum design, academic leadership and learning support during a period of rapid change. We argue that trust is foundational in assessment design, enacted through dialogue, feedback, collaboration, and willingness to take risks. While the system may be under strain, the people are not broken. Designing with trust enables the reimagination of integrity. The future of assessment lies in transformation – built differently and built together.

  • Factors influencing students’ intentions toward generative AI tools: An ethics-trust-norms framework

    Mazen Abdulwahab Asag, Md Abdullah Al Mamun

    This study explores the factors influencing students' intention to use generative AI (Gen AI) tools, such as ChatGPT, based on an extended Technology Acceptance Model (TAM) that incorporates ethics, trust, and social norms. Going beyond the traditional models that emphasise usefulness and ease of use, this study highlights the growing influence of ethical beliefs, peer influence, and trust in driving adoption behaviour. A survey of 316 students at an international university in Bangladesh revealed that intention is strongly driven by perceived usefulness and ease of use, and intention is a strong predictor of actual usage. However, trust and ethical concerns exert more subtle effects such that trust directly influences usage and moderates the intention-action link, while ethical concerns do not directly predict behaviour but strengthen the intention-to-use connection. Structural equation modelling confirmed multiple mediation paths, highlighting the complexity of GenAI adoption in an educational setting. These results suggest that adoption decisions are not simply technical but are shaped by students' trust in the tool, social signals from peers, and the accuracy and quality of responses. The study offers practical guidance for educators and policymakers seeking to promote ethical GenAI adoption in higher education institutions.

  • Virtual hotels, real skills: Developing sustainability competencies through simulation

    Mary Jesselyn Co, Bruce Mitchell, Lisa Powell

    This paper describes the development and implementation of an innovative hotel carbon reduction simulation aimed at developing sustainability competencies in business students. Using the Harvard Business School "Net Zero" simulation, we assess how interactive simulation-based learning opportunities improve students' self-assessment of the eight sustainability competencies with a mixed-methods approach. The research examines critical gaps in knowledge of how simulation-based methods can develop integrated competency sets needed to solve complex sustainability challenges. The simulation assigns around 950 first-year management students as hotel managers tasked with achieving 50% emission reductions over seven years while maintaining financial performance. Students select from 29 sustainability initiatives across Energy, Purchasing, and Management categories, working within realistic constraints of carbon budgets, site-specific emission factors, and dynamic market conditions. Our comprehensive analytical design combines pre-post competency surveys with cluster analysis of strategic approaches, and qualitative analysis of learning reflections. Anticipated outcomes are enhanced competency development across all eight dimensions, with gains in systems-thinking, futures-thinking, and implementation competencies. The research aims to provide empirical proof for developing specific sustainability competences as well as demonstrating scalable approaches of integrating sustainability education into core business curriculum.

  • Relieving instructor angst about inclusive design: Exploring the potential of gen AI to sustainably support the implementation of Universal Design for Learning

    Frederic Fovet

    The literature has established that if instructors shy away from implementing Universal Design for Learning (UDL) it is often because of lucid and tangible fears about workload. In parallel, the emergence of gen AI has immediately triggered hopes that large language models (LLMs) might be successfully used to support the challenging planning tasks of higher education instructors; it has immediately struck scholars that this might include supporting instructors who might have fears about workload and competencies in relation to UDL implementation in their classes. This study explored the degree to which an LLM could be effective in supporting an instructor redesign two Masters of Education courses in order to make them more aligned with UDL than they already were. The theoretical lens used in this project was the social model of disability. The methodological framework used was action research. The research team prompted the LLM for UDL strategies. A process of triangulation invited students having previously taken the courses to assess the effectiveness of the redesign. The findings suggest that gen AI can indeed support the UDL redesign of courses. Concerns are, however, raised because mastering the prompting competencies necessary may be as complex as the UDL redesign itself.

  • Developing a framework to guide university educators designing AI-powered study support tools: A work in progress

    Min (Doug) Guo

    This paper introduces a MPhil research project aimed at developing a framework to facilitate university educators, particularly non-technical users, in designing Generative AI (GenAI)-powered study support tools for regional, rural, and remote (RRR) students. The framework will guide the customisation of AI chatbots (AI-SUPBOT) that provide scaffolded academic support while upholding academic integrity. Grounded in Technological Pedagogical Content Knowledge (TPACK) and Design-Based Research (DBR) principles, the framework aims to offer a structured, pedagogically sound path for integrating GenAI in higher education.

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