2025: ASCILITE 2025 Conference Companion Materials

ASCILITE Conference - Pecha Kuchas

• The AI client: Using empathic voice-interactive AI to support the development of clinical communication skills

  Naomi Cocks, Phoebe Simpson, Emily Calton, Christina Fernandes, Brenton Lush, Ife MacKenzie, Marcelo Jopia Vilches, Matt Reed, Janet Beilby

  Developing effective communication skills is essential for healthcare professionals. Poor communication can result in misunderstandings, clinical errors and reduced client satisfaction (Bensing, 1991; Ong et al., 1995; Ratna, 2019). Role-plays and simulations with actors are commonly used to teach and assess these skills (Kaplonyi et al., 2017). Students may also practice informally with peers or family members. These approaches are underpinned by Kolb’s Experiential Learning Cycle (Kolb, 1984), enabling students to engage in concrete experiences through interaction, reflect on their communication strategies, and actively experiment with applying these skills in future clinical scenarios. However, these approaches often fall short in authenticity and accuracy, particularly when participants lack knowledge of specific medical conditions or cultural contexts. Moreover, scripted role-plays can limit students’ ability to adapt to the unpredictable nature of real-world healthcare interactions, thereby hindering the development of communication flexibility. Peer feedback is frequently inconsistent or inaccurate, and actor-based simulations, while more realistic, are often prohibitively expensive. To address these challenges, previous research has used Artificial Intelligence (AI) tools to successfully support health professional student’s communication skill development (see Stamer et al., 2023 for review). However up until recently, the AI tools available have been limited in capability and have been difficult and expensive to access. Increased accessibility and improved capability in recent years has resulted in increased opportunity for the use of AI tools to support health professional student’s communication. This project aimed to leverage Hume.ai, an empathic voice-interactive AI application, to enhance communication skills and improve confidence among allied health students. The project also explored the potential of Hume.ai to be used in the assessment of communication skills. Students from a range of allied health professional courses, including speech pathology, physiotherapy, pharmacy, occupational therapy, social work, nutrition and dietetics, trialled the interacting with this tool. Students were provided with suggestions for simulated interactions with Hume.ai to practice and refine their communication skills. These simulations covered a range of scenarios, including patient interviews, describing therapy approaches, and engaging in difficult conversations. To evaluate Hume.ai, reflections were collected from staff and participating students were invited to complete a questionnaire and attend a focus group regarding their experiences. This presentation will share key insights from staff reflections and early findings from student evaluations regarding the use of Hume.ai in training and assessing communication skills. It will explore the perceived strengths and limitations of the application, discuss student engagement and reactions, and examine the extent of uptake among learners. Additionally, the presentation will address the practical and ethical challenges encountered in securing approval for the use of a voice-based AI tool in educational settings. These insights aim to inform future integration of AI-driven tools in communication training and stimulate discussion on their broader implications for education.

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• Dialogic pedagogy and student agency for critical AI literacy: An action research project

  John Pike, Tamra Ulpen

  As generative AI (GenAI) becomes increasingly embedded in higher education, students face contradictory narratives about its use as it is often presented either as a risk to academic integrity or as a valuable educational resource (Luo, 2025). Navigating these tensions can be particularly complex for students from equity groups, who already contend with challenges in adapting to university learning environments (Stokes, 2024). While institutional policies attempt to regulate GenAI use, these often lack the nuance needed to guide context-sensitive decision-making (Corbin et al., 2025). This presentation outlines an action research project that investigated how dialogic teaching approaches can support students in developing critical GenAI literacies through collaborative exploration and reflection. The research took place within an Australian university’s Enabling Education program and was grounded in the principles of Dialogic Pedagogy which is a critical framework rooted in reciprocal communication, shared meaning-making, and the co-construction of knowledge (Shor & Freire, 1987). Rather than imposing rules, this pedagogical model encourages transparency, inquiry, and inclusive negotiation of acceptable practices. Encouraging students, who are new to university, to become active agents supports them to build their critical AI literacy (Toncelli, et al., 2025; Wang & Wang, 2025). This approach shifts the emphasis from compliance to empowerment, allowing students and educators to engage in meaningful dialogue about the ethical and effective use of GenAI in their learning. Using a critical participatory action research methodology (Kemmis et al., 2014), the study collected data across three foundational courses: language and literacy, digital literacy, and information literacy. In the language and literacy unit, students explored the use of GenAI tools in developing their academic writing. Through classroom activities and reflective discussions, students examined GenAI-generated feedback on their work, considering how such input could enhance their language development while identifying its limitations and ethical implications. In the digital and information literacy courses, activities focused on the broader societal and epistemological impacts of GenAI. Students investigated how AI technologies influence knowledge creation, information access, and authorship. Educators facilitated discussions that encouraged students to evaluate when and how GenAI might be used responsibly in their coursework, particularly in creative and research-based projects, without compromising academic ownership. Findings from this project highlight the value of dialogic approaches in Enabling Education programs to help students take ownership of their learning. Students’ initial uncertainty shifted to confidence in sharing their experiences of GenAI. Further, this approach created a safe space for open discussion enabling co-construction of knowledge about critical AI literacy. By centering student voice and agency, this model offers a compelling alternative to top-down enforcement of AI-related policies. It suggests that fostering critical engagement with GenAI builds students’ confidence and skills and strengthens trust between educators and learners. This work contributes to emerging conversations around AI literacy in higher education by proposing a framework that is both inclusive and responsive to the real-world complexities of student experience. It underscores the importance of pedagogical strategies that are participatory, flexible, and grounded in shared inquiry, particularly for students navigating the margins of academic culture.

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• Synthetic media, generative AI, and Barbie in education

  Carmen Vallis

  Since the mass adoption of ChatGPT, educators have been prompted to rethink text assessment practices and respond to mounting concerns about academic integrity (Dawson et al., 2024; Nikolic et al., 2024). Critical, meaningful learning is often at odds with performative assessment models that prioritise measurable outputs (Wise et al., 2024). At the same time, social media and mainstream narratives promote AI promises of personalised learning and educational transformation, glossing over deeper ethical questions and its potential dehumanising effects (Bender, 2024). Yet the philosophical, social and ethical aspects of generative artificial intelligence (GenAI) use in education are more important than ever (Sidorkin, 2024). The practical implications are substantial as GenAI implementations frequently emphasise technological capabilities and operational efficiency over critical examination of learning theories, student autonomy, and the pedagogical implications of transferring educational authority to AI systems (Zawacki-Richter et al., 2024). Rather than viewing GenAI as purely transformative or destructive, it may be seen as a constructed vision that reflects social, cultural assumptions about personalisation and agency (Rahm, 2023). Moreover, the AI technology industry aims to “create progressively more complex simulacra of the human body and its surroundings” (Ferreira et al., 2023, p. 10), which has profound implications for society and education. This research uses metaphor to examine how synthetic media, such as generative AI, may reshape teaching practice and educational relationships (Vallis et al., 2025). Examining GenAI in education through the cultural lens of ‘Barbie’ shows how evolving attitudes towards empowerment and authenticity are mutually shaping technology’s role in learning (Vallis, 2025). The hyperreal setting of ‘Barbieland’ is presented as analogous to the promises of individualised empowerment in educational technology, which often mask superficial solutions that reinforce existing inequalities (Baker & Hawn, 2022). In the 2023 film, Barbie evolves from plastic figure to ‘real’ human, paralleling the accelerating development of synthetic media and AI-generated video, which may disconnect teachers and students from embodied human interactions in education. This blurring of the real and artificial challenges our understanding of authenticity (Vallis, 2024). Educational uses of AI, where the focus on efficiency and personalisation comes at the expense of deeper pedagogical intent (Baker & Hawn, 2022), risk replicating an inauthentic consumer-oriented ‘Barbie’ logic that prioritises appearance over genuine connection. The presentation introduces ‘(Re)generative Education’ as an alternative concept that emphasises adaptive, collaborative approaches to human-AI interaction in learning environments. Western-centric narratives of technological empowerment are contrasted with an Indigenous perspective from Ellen van Neerven’s ‘Water’ (2014) to reveal how dominant cultural narratives limit our imagination of human-AI collaboration in education. More holistic evaluation criteria and collaborative design are needed when integrating AI, to avoid the rigid either-or thinking sometimes found in education technology discussions (Matthews, 2021). This includes educational development that build critical technological fluency rather than operational competence alone and creating mechanisms for ongoing feedback. Connecting cultural analysis to operational practice supports more thoughtful, equitable, and pedagogically sound approaches to AI integration that honour diverse ways of knowing while still making purposeful use of its technological affordances.

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• Reignite the live learning experience

  Louise Luff, Benjamin Lay, Janine Coupe, Kaiying Ji

  Bandura’s timeless self-efficacy theory (Bandura, 1977) and its “I believe I can do it” theme informs learning across many domains. Whether it’s rewarding daily walking steps through a smart watch app or developing novel ways to improve tertiary level learning, creative use of Technology Enhanced Learning (TEL) tools and formative feedback strategies builds resilience, promotes continuous engagement and showcases personal achievement in the digital world (Garivaldis et al., 2022). For a suite of complementary financial reporting units in an undergraduate accounting major program, TEL tools from the publicly available HTML5 Package (H5P) open-source content collaboration framework and the tracking attributes of the Student Relationship Engagement System (SRES) developed by the University of Sydney have been innovatively combined to facilitate a deeper, emotionally supported learning experience. To promote confident student engagement during class time, playful interactive lecture and tutorial activities were created. Using branching scenarios, summary tools, dialogue cards, drag-the-word, and fill-in-the-blank H5P applications, the reimagined activities unpacked complicated, high cognitive load learning points into discrete and manageable learning steps. Each activity’s step by step approach carefully supports students through each aspect of complex concepts, calculations, flowcharts, mind maps, and real-world business problem-solving scenarios. At each step, H5P’s immediate and visual feedback functionality has been cleverly adapted to provide corrective feedback. As the activities allow unlimited attempts, they have also become supportive self-study resources that foster greater persistence. An accompanying SRES reward badge portal was created and implemented in the unit’s Learning Management System. For each submitted interactive activity, the student’s effort is acknowledged with a reward badge, visible through the student’s sign in. Tutors regularly encourage students to view their reward badge status throughout the semester; the ongoing narrative heightens the live learning experience. This game like recognition promotes student motivation and participation and provides self-efficacy opportunities (Zirawage et al., 2017). It has also allowed teaching teams to identify, monitor, and support less engaged students. There have been many notable benefits from the reignite the live learning experience. Through the student lens, it has provided a fun and enriching learning experience, consistent teaching across related units of study within a program, and deeper working in partnership connections. From a teaching perspective, it has made the teaching of abstract and complex concepts more accessible to diverse student cohorts and provided a layered, building block learning approach to facilitate, and at a broader level, achievement of program learning objectives. Reignite the Live Learning Experience’s beauty is its applicability. While suitable for all disciplines, it is highly recommended for first year units of study, units that have high student attrition rates or where student connection is at risk. The presentation will showcase the initiative’s development process, H5P interactive activities, SRES reward badge portal and live learning experience tutor narrative examples.

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• Securing academic references with referencing source information

  Uwe Kaufmann, Edward Willson, Liz Heathcote

  The release of Generative Artificial Intelligence (GenAI) tools forced [our institution] to rethink our assessment design by incorporating a process-oriented component that exploited GenAI weaknesses to limit its use and secure the integrity of student submissions (Shishavan, 2024). In our capstone subject, we require students to engage with academic literature. Using the right prompt, GenAI tools can easily summarise literature. In the early stage of GenAI availability, we frequently identified cases of hallucinated references in student submissions. Once students were aware of this issue, we began to see frequent references to older academic textbooks used in assessments with suspected GenAI misuse. However, even when referred to academic integrity investigations, proving any misconduct was a time-consuming exercise and often inconclusive, partly due to the difficulty in accessing the cited textbooks. With the aim of ensuring students are engaging critically with the academic literature at a level required in post-graduate studies and to disincentivise the unethical use of GenAI tools, we developed and trialled a process-oriented engagement called a “Reference Source Information document” (RSID). The RSID requires students to record their research and use of literature by providing the exact quotes, with page numbers, that formed the basis of their citations/ paraphrased content in their assessment. In addition, we interlinked the RSID within the marking rubrics. Submission of an incomplete or falsified RSID would result in a failing grade, without the need for an academic integrity investigation (unless egregious misuse was apparent). The rationale for the RSID was the following: Ensure students are engaging with the literature critically and methodically, rather than providing GenAI-generated summaries, and therefore create an incentive for the ethical use of Gen AI. Students who use GenAI ethically would only see a small amount of extra work, if any, in completing the RSID as its process reflects good research practice expected from a post-graduate student. Current popular GenAI tools struggle to provide direct and accurate quotes, implying that without engaging with any literature, producing an RSID is not possible (Jazwinska & Chandrasekar, 2025; Peters & Chin-Yee, 2025). When students have substantially relied on GenAI to produce a section of an assessment, reverse engineering the RSID requires them to engage with the literature to find a direct quote that matches the claim made by GenAI. The requirement for students to perform a verification process underlines the ethical best-practice use and norms of GenAI in a professional context (Victorian Legal Services Commission, 2024). We found that requiring students to provide the RSID was an effective way to secure academic references. The requirement greatly reduced the number of hallucinated references and textbooks. While there were some student comments on the extra workload, these comments were in the minority. We found a key way to avoid this type of concern was for academics to make it clear why the document was important: to ensure cognitive engagement and learning from research, credibility of the submission, uphold academic integrity and ensure that subject and course learning outcomes are met.

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• Tools of entanglement: Making interdisciplinary learning happen (despite everything)

  Miriam Pollard, Bevan Warren, Angela Kerry

  Universities, learners and educators face an increasingly challenging and interconnected world (Corbacho 2025; Spelt et al. 2009). Technological change and generative AI mean access and production of knowledge are no longer limited domains, and the role of universities is evolving. Traditional binary and disciplinary approaches to education are no longer adequate. Rather, we need to work with learners to become change-agents able to face and thrive in the context of intractable global challenges (Bertolini et al. 2024; Stephens et al. 2008). Future-focused learning requires more than new content; it requires ways of thinking, working, relating and enabling that are adaptive and reciprocal. From this perspective, interdisciplinary approaches have much to offer, traversing multiple ways of knowing and understanding, while addressing ‘wicked’ problems. This will require innovative curriculum structures and practices that mirror its complexity, including hybrid tools, collaborative cultures, and conceptual agility (Lindvig et al. 2025). The process of enabling interdisciplinarity is itself interdisciplinary. In this paper we share the story of a cross-institutional initiative that challenged our large dual-sector institution, providing a catalyst to realise our interdisciplinary aspirations. Our interdisciplinary initiative, a minor built around the theme of global challenges, is underpinned by a constructivist approach, adopting an inquiry-based pedagogy, focused on co-design and collaborative teaching models. This required cultivating new relationships, connections and tools for learning and teaching – fostering the generative entanglements that underpin our interdisciplinary toolkit. Our toolkit, inspired by the work of Edinburgh Futures Institute (Overend et al. 2024) is not a fixed product but a dynamic mindset, evolving and shaped through practice. Co-designed through grant-supported collaborations, our toolkit is an ongoing structure that includes examples of assessment innovation and collaborative learning experiences that support and guide interdisciplinary endeavours (Laursen et al. 2024). Operating from the educational third space, our role has been not just to enable new ways of learning, but to clear space within legacy systems to allow educators and learners to think and work differently. This work has articulated the idea that interdisciplinarity is not just a way of organising learning, it also shapes the ways in which we facilitate learning. Supporting complexity requires a diversity of tools, systems, methods and metaphors (Newell 2001). We embraced both digital and embodied modes, using hybrid collaboration platforms, experimenting with AI tools for reflection and design, while also valuing physical environments and tactile tools. Some of the most generative entanglements emerged in low-tech, embodied moments, demonstrating that fostering new learning is situational, relational, and multimodal. Much of this work involved a sometimes-messy interplay between the analogue and the digital. We brought everything we had – frameworks, metaphors, platforms and technologies – holding all lightly and ready to adapt or abandon when it no longer served. In co-creating this work, we found that enabling interdisciplinary practice requires not only tools and mindsets, but ways of working that challenge our assumptions, reaching across distance and disciplines to make space for a connected future.

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• From idea to classroom: Accelerating bespoke educational tool creation through vibe coding

  Maurizio Costabile, Sarah Davey, Kuan Tan

  The democratisation of educational technology development through generative artificial intelligence (GenAI) is reshaping how educators design bespoke learning tools. This presentation chronicles the emergence of vibe coding, an approach where subject-matter experts (SMEs) exchange natural-language prompts with GenAI models to translate pedagogical ideas directly into functional software, thereby lowering cognitive load and enabling rapid experimentation (Erez & Hazzan, 2025). In a 2025 case study, an immunology lecturer with no programming background produced a broad suite of HTML5 simulations for 2nd-year students, serving as a powerful example of cross-disciplinary potential. Simple activities moved from concept to classroom in fifteen minutes; richer interactions took two to three hours. The simulations serve three purposes: a virtual laboratory reinforcing key principles, a work-integrated resource linking theory with professional practice, and a formative assessment tool providing instant feedback. Development required no external support, licences, or IT approvals, illustrating how cloud-based GenAI can bypass traditional bottlenecks. This case exemplifies the TPACK (Technological Pedagogical Content Knowledge) framework (Archambault & Barnett, 2010), demonstrating how GenAI can bridge the gap for educators with deep pedagogical and content knowledge but limited technical expertise. The approach aligns with research positioning natural language as the key interface between pedagogy and code (Plate & Hutson, 2024), effectively removing technical barriers to accelerate prototyping (Hare, 2024; Keith et al., 2025). Unlike conventional no-code platforms, the GenAI method offers near-unlimited customisation, making the educator’s pedagogical intent, not the platform's constraints, the primary driver of tool design. The four-phase development process was driven by pedagogy: (1) conceptualisation grounded in constructivist learning objectives; (2) iterative prompting; (3) rapid prototype testing; and (4) classroom deployment. The resulting tools were designed to reduce extraneous cognitive load for students, allowing them to focus on core concepts through active experimentation. Across all stages, the educator's disciplinary expertise, rather than programming skill, determined success. The finished simulations exhibit functionality that would normally demand months to years of professional work. Beyond access to Google AI Studio, cost was negligible, aligning with evidence that GenAI tools deliver significant productivity gains (Ziegler et al., 2024) and enable the creation of high-quality learning objects with minimal resources (Trckova et al., 2024). Formal student feedback and learning-outcome analysis are scheduled to quantify the impact on engagement and comprehension. Maintenance and sustainability issues emerged, particularly for newcomers. However, exemplar prompts and peer mentoring quickly mitigated these challenges. The ability to visualise ideas within minutes also promises to enhance traditional workflows by enabling SMEs to communicate nuanced requirements to developers. Ethical considerations, including data privacy and model transparency, will be addressed to ensure robust governance. Institutional implications are substantial. By shifting educators from consumers to creators, GenAI functions as a cognitive amplifier for non-technical staff, fostering a culture of iterative digital pedagogy. Leaders will need policies that safeguard equitable access, privacy, and sustained professional development. This presentation offers practical guidance for educators, strategic insights for administrators, and new directions for researchers studying GenAI-pedagogy intersections, highlighting the shared responsibility of educators and institutions to steer this transformation toward sustainable and high-quality educational outcomes.

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• EngageAI: Transforming student engagement through ethical AI-driven nudging in online higher education

  Rhodora Abadia, Gosia Ludwichowska-Alluigi, Reid Honan, Neil Bretana, Srecko Joksimovic, Paggie Liu, Leon Kimani, Fernando Marmolejo-Ramos

  Student engagement in digital learning environments presents a critical challenge, with attrition rates in online delivery modes averaging six times higher than traditional face-to-face courses (Wang et al., 2023). To address this pressing issue, the EngageAI project introduces an innovative AI-driven persuasive technology tool that delivers personalised, real-time nudges to enhance student engagement in digitally rich learning environments. EngageAI represents a significant advancement in Technology Enhanced Learning by applying behavioural economics principles within educational contexts. While existing tools rely on teacher-determined schedules and group-based messaging, EngageAI leverages individual student behavioural patterns derived from LMS analytics to deliver strategically timed, psychologically informed interventions. This innovation centres on the system's adaptive personalisation capabilities, which analyse individual engagement patterns to identify optimal intervention moments across three critical areas: motivation enhancement, time management improvement, and meaningful instructor interactions. For instance, when analytics indicate a student typically engages with course materials on Tuesday evenings but has missed their usual pattern, the system delivers a contextually appropriate nudge that respects their preferred learning schedule while encouraging re-engagement. The project's theoretical foundation rests on Thaler and Sunstein's (2009) nudge framework from behavioural economics, ensuring interventions respect freedom of choice while encouraging positive behaviours. Building on Wang and Eccles' (2013) multifaceted engagement model, the system simultaneously targets behavioural, emotional, and cognitive dimensions. Most importantly, EngageAI incorporates Lades and Delaney's (2022) FORGOOD ethics framework, ensuring all interventions meet rigorous standards for Fairness, Openness, Respect, Goals, Opinions, Options, and Delegation. This comprehensive ethical foundation distinguishes EngageAI from purely technical solutions by consistently prioritising student autonomy, privacy, and dignity throughout the intervention process. The research methodology employs a within-subjects design implemented in the undergraduate online course Critical Approach to Online Learning. The approach begins with an initial analysis of engagement patterns without AI-based nudging, establishing baseline data that informs the strategic deployment of interventions. The methodology then tests the intervention in one semester, comparing results to the non-intervention baseline, followed by refinement and retesting in subsequent semesters. This systematic approach unfolds across five carefully structured phases: framework development, tool creation, prototype testing, refinement and scaling, and final evaluation. Throughout each phase, continuous ethical review and stakeholder feedback ensure sustained alignment with educational goals and ethical standards. EngageAI’s design principles demonstrate inherent scalability across diverse tertiary contexts. The system's foundation in learning analytics enables seamless adaptation to different Learning Management Systems and course structures, while planned expansion to courses across Business, STEM, Health, and Creative disciplines confirms its broad applicability across academic disciplines.

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• Empowering higher education through heutagogical assessment strategies

  Ashley Howard Kerr

  This abstract explores how the redevelopment of a Master of Education program embraced heutagogical principles to create an adaptable, resilient, and future-ready learning environment. Grounded in adult learning theory and social constructivism (Blaschke, 2019), heutagogy offers a compelling response to the needs of contemporary students navigating diverse professional, cultural, and technological contexts. Our subject redesign began with a foundational question: Who are our learners? In our case, they are working professionals with rich, varied backgrounds who seek meaningful opportunities to apply and extend their expertise. Traditional assessment strategies often constrain such learners, focusing on prescriptive outputs rather than individual growth and agency. In contrast, a heutagogical approach empowers students to actively shape their learning journeys by setting personal goals, selecting relevant resources, and reflecting on real-world application (Blaschke & Hase, 2015). This session shares how we embedded heutagogical principles into every layer of the curriculum, particularly the assessment strategy. The assessment strategy intentionally incorporates assessment of, for, and as learning, recognising the importance of evaluation, feedback, and learner self-regulation as interconnected components of the learning process. Metacognition and self-efficacy are intentionally scaffolded to support learners in becoming resilient and reflective. Assessments are not merely tools of measurement but engines of learning. From reflective journals to digital toolkits and advocacy plans, students are encouraged to explore their own context and present their understanding in diverse formats. The emphasis shifts from product to process, promoting engagement, academic integrity, and deeper conceptual learning (Blaschke & Hase, 2015). A key feature of the assessment design is the focus on real-world relevance and personal meaning. Students are encouraged to explore issues or challenges connected to their own professional or community context, applying theory to practice in ways that create tangible value. This approach embodies authentic assessment, situates learning in lived experience, and reflects broader course themes such as empowerment, advocacy, and social responsibility. As a result, students often report a stronger sense of ownership over their work, and educators observe greater depth, originality, and critical engagement in their submissions. The reflective structure of the assessments also supports social-emotional learning by encouraging learners to explore their identity, values, and professional purpose, fostering wellbeing alongside skill development. The heutagogical model also fosters inclusivity and adaptability. Offering students agency in how they demonstrate mastery not only accommodates diverse learning needs but encourages critical and creative thinking. Through strategies like process-driven assessment, learner-contextualised tasks, and reflection-infused outputs, students are supported to become agile, self-regulated learners prepared for an uncertain future (Carless et al., 2017). The design is sustainable across hybrid, online, and face-to-face delivery modes, ensuring consistency of student experience and adaptability to institutional needs. Incorporating Artificial Intelligence into Authentic Assessment As artificial intelligence reshapes the educational landscape, its integration into assessment design must be intentional and values driven. In our Master of Education redevelopment, AI is positioned as a catalyst for deeper inquiry. Students are encouraged to critically engage with AI tools, such as generative platforms, to support research, ideation, and reflection. This approach aligns with heutagogical principles by fostering learner agency, self-direction, and metacognitive awareness (Blaschke & Hase, 2015; Narayan & Vanderburg, 2025). Rather than policing AI use, assessments are designed to promote transparency, ethical reasoning, and critical evaluation of AI-generated content. Learners reflect on how AI influences their thinking, decision-making, and professional practice, embedding academic integrity within a framework of trust and personalisation (Anthology, 2024; Dolbin et al., 2024). This empowers students to become discerning users of technology, capable of navigating complex, real-world challenges with confidence and integrity. AI-supported assessment also scaffolds metacognition and self-efficacy, enabling learners to identify patterns in their thinking and refine their approaches (Lineman, Sweet, & Sutton, 2025; Searle Center, 2025). These strategies align with process-driven, authentic assessment models that prioritise learner context, critical engagement, and adaptability (Carless et al., 2017). Looking ahead, we argue that assessment design must prioritise flexibility, authenticity, and student voice. In the age of artificial intelligence and rapid technological transformation, academic integrity cannot rest on control or surveillance. Instead, it must be built on trust, personalisation, and critical engagement. Heutagogy offers a timely and sustainable path forward, where learners are not passive recipients of content but co-creators of their educational experiences. This presentation offers practical strategies, examples, and design principles that participants can adopt and adapt in their own contexts. In doing so, it contributes to the conversation on how higher education can remain relevant and empowering. It aims to equip learners to thrive in a future defined by continuous change.

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• Enhancing engagement in large postgraduate capstone classes: Structured participation and one-on-one interaction

  Dhayani Kirubaharan

  Student engagement is increasingly recognised as an important factor influencing achievement and learning in higher education (Kahu & Nelson, 2018; Mandernach, 2015). Sustaining meaningful engagement in large classrooms is difficult, particularly with diverse student cohorts and generational differences in learning preferences (Cuseo, 2007; Giunta, 2017; Maringe & Sina, 2014; Mendoza, 2019). While technology-enhanced learning (TEL) tools are widely used to promote engagement through active learning (McKinsey & Company, 2022), they do not always address the deeper, relational aspects of engagement that help students feel connected and supported (Crawford et al., 2024). In an era of constant technological change, personal teacher-student and peer relationships remain vital to creating safe and supportive environments where students feel seen and are encouraged to share ideas, ask questions, and seek help. This Pecha Kucha introduces a classroom-based intervention designed to enhance engagement in a large postgraduate accounting capstone unit. It draws on Kahu and Nelson’s (2018) concept of the educational interface, a psychosocial space where institutional and student factors interact. It also builds on the findings of Kahu, Picton and Nelson (2020), who found that supportive conversations, empathy and encouragement as key triggers for student engagement. This intervention involves an oral participation assessment that incorporates structured participation and one-on-one interaction to foster connection and conversation. The unit enrolled approximately 250 students across three workshops of 65–95 students each, many from diverse cultural and linguistic backgrounds. Engagement in such contexts is challenging, particularly when students face barriers to oral participation. To address this, the participation assessment was reimagined to be inclusive and multifaceted. For consistency and efficiency in assessment, groups were formed through a structured networking activity in Week 1, establishing table-based peer cohorts for the semester. Participation was scaffolded through three pathways: whole-class discussion, small-group conversation, and one-on-one interaction with staff. During case-based activities, staff and assistants rotated between tables in structured engagement rounds. These real-time conversations provided quieter or linguistically hesitant students with opportunities to contribute in low-pressure settings. Weekly feedback was integrated into class time to reinforce progress and support iterative learning. Although digital tools and generative AI were embedded to aid discussion, content review, and peer collaboration, the heart of the practice lies in the high-touch, relational nature of teaching. It highlights how innovation in TEL can come from reimagining how we use structure, space, and time within existing classroom ecosystems. This approach complements technology in education by embedding purposeful human interaction that strengthens engagement and learning. Students reported high levels of satisfaction, particularly with having multiple ways to participate and opportunities to feel seen and heard. One staff member reflected that the structured conversations mirrored workplace readiness by giving students practice in reporting succinctly to senior leaders. Workshop assistants noted that the assessment motivated preparation and improved real-time communication, particularly for students less inclined to speak voluntarily. Challenges included time pressures associated with rotating through tables and ensuring fairness in marking. These were managed through collaborative planning, transparent criteria, and clearly defined participation roles. The overall outcome was a relational learning environment that made large classes feel smaller, more inclusive, and more responsive. In an era of digital transformation, this case highlights the enduring value of intentional, human-centric assessment design. Purposefully combining TEL with low-tech strategies affirms that low-tech does not mean low-impact; rather, it demonstrates pedagogical resilience that places equity, connection, and student voice at the centre of technology-rich higher education.

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• PolyFeed—Enhancing feedback literacy and strategies with feedback analytics

  Yi-shan Tsai, Bhagya Maheshi, Hiruni Palihena, Thomas Ka Ho Ng

  Quality feedback is crucial to student success and learning experience; yet higher education continues to struggle with the provision of effective feedback. Scholarship in feedback studies has shifted from viewing feedback as a product transmitted from teachers to students, to promoting it as a two-way process in which students and teachers engage in interactive dialogue (Yang & Carless, 2013). However, predominant feedback practices still follow a one-way paradigm, with teachers having very limited understanding of how students engage with feedback. This is partly due to the difficulty in tracking ways learners interact with feedback. Consequently, there is a lack of support for students to benefit from feedback and for teachers to improve feedback strategies. To bridge the gap between students and teachers in a feedback process, we propose feedback analytics as a solution. Feedback analytics collects, analyses, and reports on students’ interactions with feedback. Such data-based insights have great potential to scaffold the development of students’ feedback literacy, manifested in active involvement in seeking feedback, interpreting it, acting on it, and regulating the emotions that may arise during feedback processes (Carless & Boud, 2018). By capturing, analyzing, and reporting data about learners’ interactions with feedback, feedback analytics can enhance reflections among learners on their learning progress and teachers on ways to support learners. In this presentation, we introduce a novel feedback analytics system that builds on key feedback theories including feedback literacy (Carless & Boud, 2018), dialogic feedback (Yang & Carless, 2013), and learner-centred feedback (Ryan et al., 2023). The tool can: a) support students to make sense of feedback and act on it; and b) support teachers to track student interactions with feedback and provide targeted support. The system contains a student-facing tool and a teacher-facing tool, both leveraging AI technologies to support key functionalities. The student-facing tool enables students to highlight and label feedback, create reflective notes and action plans, seek further explanations from Generative AI or teachers, and track their strengths, weaknesses, and action progress across multiple assessments and courses. The teacher-facing tool supports teachers to enhance feedback quality by assessing the alignment of their feedback with learner-centred principles and suggesting ways to improve it. It also helps teachers shape feedback strategies by providing data about students’ interactions with feedback through the functionalities mentioned above, in addition to students’ feedback requests and perceptions of feedback usefulness. The tool has been piloted in both lab and authentic learning settings, receiving positive feedback from educators and students on its potential to transform feedback practice, while noting the need to balance human judgement with AI suggestions.

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• Seeking a foundational understanding of instructional video use in tertiary music education

  Joshua Milton

  Despite the widespread use of instructional video and other technologies across higher education, the role of learning technologies in tertiary music education remains largely unexplored (Zhukov, 2015). Instructional videos have been shown to be a widely used pedagogical tool within higher education in Australia (Colasante, 2022; Fyfield et al., 2019; Henderson et al., 2017). Music is a domain in which students typically engage in extensive independent practice and learning (Jorgensen, 2000; Zhukov, 2015), presenting a strong use case for the provision and use of asynchronous learning materials to support this independent study and practice (Grant, 2013; Johnson, 2022). However, in the context of tertiary music education, there is little empirical evidence to confirm widespread use of instructional videos in explicit or self-directed learning, or to explore the pedagogical purposes they serve (DeWitt et al., 2013). This Pecha Kucha reports on preliminary findings from the first phase of a mixed-methods research project on the use of instructional videos in tertiary music education. The research project aims to address these gaps in the literature by (1) establishing foundational understandings of current practices relating to instructional video in tertiary music education, (2) investigating how educators’ values and perspectives influence pedagogical decisions regarding video selection and design, and (3) evaluating the impact of various multimedia design features on student learning gains, drawing on theories such as Mayer’s (2014) Cognitive Theory of Multimedia Learning (CTML) for analysis in subsequent phases. The first phase of the research involved distributing an online survey to tertiary music educators and students across Australian and international institutions. The survey collected both quantitative and qualitative data, which are currently being analysed using statistical methods and inductive thematic analysis, respectively. Quantitative data describes the extent, frequency, context, and purpose of instructional video use in tertiary music teaching, and qualitative data captures the reasoning for utilising instructional videos, factors influencing adoption, and perceived pedagogical quality. The online survey was conducted in the second half of 2025. While data collection and analysis are ongoing, this Pecha Kucha presents a descriptive analysis of the data collected to date, providing an initial picture of how instructional video is currently being used (or not used) in tertiary music education contexts, as well as educators’ and students’ experiences with and attitudes toward the use of instructional video within the tertiary music context. This research aims to make a novel contribution to the fields of music education and digital pedagogy by providing a foundational view of the use of instructional video in tertiary music education, with a focus on the Australian context. It will also provide insight into educators’ pedagogical reasoning and preferences, offering evidence to inform the design of more effective, discipline-specific video resources. In doing so, the research aims to support more pedagogically grounded use of instructional video within the tertiary music context. More broadly, instructional video can enhance accessibility and inclusion by supporting regional learners, enabling flexible engagement with diverse expertise, and fostering equitable participation in independent learning.

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• Developing a values-based ethics learning tool

  Anisha Fernando, Siaw Mei Sim, Kathy Darzanos, Kirsten Wahlstrom, Nina Evans

  Disruptive technologies create value tensions that students need to consider, irrespective of their discipline or professional context. These value tensions arise when competing values are present in a technosocial context. In 2018-2019, a card-based ethics learning tool was created to support students in developing values-based ethics and data literacy competencies. The cards engage students in considering ethical dilemmas and values when designing or using technologies and are informed by doctoral findings and classroom observations (Fernando, 2017; Fernando, 2020). The first prototype of these cards was primarily aimed at undergraduate IT students, and was presented to local collegiate communities, at MozFest 2019, a conference sponsored by Mozilla, and at ETHICOMP 2020, the leading international computer ethics conference (Author, 2020). This early prototype of the conversation cards was based on value tensions but had not been validated or expanded to address the values-based ethics competencies in other discipline contexts. At present, the authors are working on a funded Scholarship of Teaching and Learning (SoTL) project to extend the initial prototype by applying the theorising of Shannon Vallor (2018) and Shoshana Zuboff (2019) to the value tensions conceptual framing. Vallor (2018) theorised 12 technomoral virtues that people should consider when using or designing technologies, whereas Zuboff (2019) theorised surveillance capitalism, where the commodification of personal data through the design and use of technologies may curtail human freedom and dignity. The technomoral virtues and surveillance capitalism informed our identification of values to include in the conversation cards. These theoretical framings provide rigour while establishing clarity for learners. Student-centred and active learning pedagogical principles are realised in the conversation cards (Dada et al., 2023). The cards support problem-solving, reasoning, ethical understanding and responsible decision-making, while allowing for flexible, self-paced, learning in pairs. A PRISMA scoping survey revealed that such cards are an innovative contribution to the field, and at present we are validating the cards through a repeated-measures study followed by focus group discussions. The repeated-measures study uses a factor vignette survey eliciting responses on a 7-point Likert scale eliciting quantitative data to be analysed with an Ordinal Logistic Regression, to reveal which combinations of social and market values are the most readily identifiable as problematic. The focus groups will explore participants’ thoughts and responses about the cards to elicit qualitative data to contribute nuance and clarity to the quantitative data. To support future educators, this project will enhance educational accessibility by developing an Open Educational Resource (OER). The effective implementation of the OER hinges on User Experience (UX) and usability principles and its development will be guided by Jacob Nielson’s 10 Usability Heuristics (1994) and Norman’s broader design principles (2013). The OER interface will incorporate clear navigation and intuitive interaction to guide learners through complex ethical reasoning while being highly usable (Mayer, 2014) and will provide a feedback-rich environment. The OER will be platform independent, support diverse disciplines and educational approaches (Bower, 2010). Adopting the Web Content Accessibility Guidelines (WCAG) principles (W3C, 2023) will ensure universally accessibility, while visual design principles (Williams, 2014) will immerse learners and facilitate understanding of complex ethical dilemmas.

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