2025: ASCILITE 2025 Conference Companion Materials

The proliferation of digital tools and technology in the 21st Century university offers students flexibility in how and when they study, access to a range of scholarly resources, and tools to aid study and life as a student (Haleem al

The proliferation of digital tools and technology in the 21st Century university offers students flexibility in how and when they study, access to a range of scholarly resources, and tools to aid study and life as a student (Haleem al., 2022). However, flexibility and the choice of technologies can create complex challenges to navigate. Access to multiple contradictory digital tools to aid study can create too much choice, which requires adaptability, resilience and persistence to successfully navigate (Lahey, 2024). Students’ use of digital technologies to facilitate learning is a process of individual and distributed agency (Matusov et al., 2015) and there is a correlation between higher education success and students’ ability to adopt strategies to leverage the benefits of digital technology (Bond et al, 2018). But how do students acquire knowledge to become skilled digital navigators and thrive in rapid technological and societal changes? Digital capabilities needed for student success are unclear as research has focused on generic digital skills (Starkey, 2019) while strategic skills for learning in higher education are poorly defined (Sánchez-Caballé et al., 2020), particularly with AI and large learning models re-negotiating the student-technology dyad. This poster presents the findings of research that aimed to identify strategic digital capabilities that enable students to navigate course content. To explore this topic we used an interpretivist, qualitative paradigm to answer the question of how high-achieving undergraduate students’ access, curate, collate, synthesise, and use digital course content and tools for learning. We recruited 25 students from one University in New Zealand from deans lists or who self-identified as high achieving. Participants were from a range of subjects, Arts, Commerce, Law and Design, and data were gathered through interviews, focus groups and talanoa for Pasifika students. Ethical approval was granted by the University’s Human Ethics Committee. Participants shared strategies and provided insights which highlighted how successful students navigated digital course material in complex systems and changing landscapes. For example, digital tools such as Google Docs, OneNote and Notion allow for structure, creativity and quick searchability, and tools like Glean useful to generate transcriptions. ChatGPT was used as a conversational partner in lieu of peers “to bounce off ideas”, where the LLM was interrogated, challenged and disagreed with, to affirm their reflective practice. This poster presents a visual representation of how high-achieving undergraduate students navigate a plethora of digital tools (including AI) across four capability categories identified in the research: To create social connections To manage information To navigate the university systems To organise their learning. The findings can be used as a framework to empower future students to develop digital capabilities to navigate their undergraduate courses. These capabilities foster adaptability and persistence and support strong learning communities in both physical and virtual spaces.

The rise of generative artificial intelligence (GenAI) is prompting a fundamental review of assessment design and academic integrity in higher education. This systematic review synthesises insights from 50 peer-reviewed studies and policy

The rise of generative artificial intelligence (GenAI) is prompting a fundamental review of assessment design and academic integrity in higher education. This systematic review synthesises insights from 50 peer-reviewed studies and policy documents to explore how GenAI is reshaping pedagogical practice, institutional policy, and integrity norms. Evidence reveals a broad transition toward authentic, process-based, and oral assessments, alongside increased use of hybrid human–AI feedback mechanisms. A growing emphasis on AI literacy for students and staff also signals a shift in pedagogical priorities. However, the review identifies persistent tensions, including ethical ambiguity, fragmented policy responses, and over-reliance on detection tools with limited effectiveness. A distinctive contribution of this study is the Stakeholder Relevance Matrix, which highlights how emerging practices in assessment innovation, feedback design, and policy clarity unequally affect students, educators, and institutions. This matrix surfaces disparities in responsibility, vulnerability, and agency, underscoring the need for inclusive and values-driven responses. The review calls for a move from reactive enforcement toward integrity-by-design approaches that embed ethical and pedagogical principles from the outset. It concludes with forward-looking propositions to guide institutional policy and future research, offering a roadmap for building resilient, equitable, and ethically grounded assessment systems in the age of GenAI.

Micro-credentials are a flexible and responsive course type that meets the evolving demands of learners, industries, and higher education institutions (Department of Education, 2024; Department of Education, 2022). However, despite

Micro-credentials are a flexible and responsive course type that meets the evolving demands of learners, industries, and higher education institutions (Department of Education, 2024; Department of Education, 2022). However, despite universities increasingly integrating micro-credentials into their credentialing ecosystems, formal and non-formal education still operate in a largely separate fashion (Oliver, 2019); in this system, micro-credential learners are often not afforded the same status, rights, or institutional support as traditional degree-seeking students. Although online learning has become more commonplace in recent years, accessibility issues are still frequently experienced by students (Briggs et al., 2024). Additionally, when accessible and inclusive practices are present, they often lack integration or are applied inconsistently (Bandalaria, 2020). These discrepancies undermine both the learner’s experience and the credibility of micro-credentials as a legitimate higher education pathway. As such, when designing micro-credentials, it is critical that clear processes for ensuring accessibility and inclusion are embedded from the outset (van Rooij & Zirkle, 2016). For accessibility and inclusion strategies to be implemented effectively during course development, they should be designed with an intersectional perspective and consideration for the diverse needs of learners (Australian Disability Clearinghouse on Education and Training, n.d.), guided by key frameworks such as Universal Design for Learning (UDL) (CAST, n.d.) and Web Content Accessibility Guidelines (WCAG) (World Wide Web Consortium, 2023), and supplemented by related frameworks such as Cognitive Accessibility (Le Cunff, 2024; Web Accessibility Initiative, 2024) and Multimedia Learning Theory (Mayer, 2017) alongside relevant pedagogical approaches such as inclusive teaching (Rossi, 2022), and andragogical strategies to support adult learners (Ramirez & Inga, 2022). In our work as educational designers, we co-develop micro-credentials for our traditional student cohort, for MOOC platforms, and custom credentials for clients, working closely with academic staff and industry subject matter experts as part of a collaborative course development process. Our approach builds upon foundational standards such as the Higher Education Standards Framework (TEQSA, 2022) and draws upon different areas of expertise, including the frameworks and practices identified above, to help us support the unique context and learner cohort of micro-credentials. Through balancing effective pedagogy with inclusive and accessible design we developed a cohesive, consistent approach to course development. Our approach included clear guidelines to uphold our principles of providing equitable access to education through making content accessible and inclusive for a diverse audience, whilst also benefiting all learners by making learning experiences more flexible, learner-centred, and engaging (Digital Learning Institute, n.d.). This case study demonstrates how rapid development of short courses can be undertaken with an inclusion-first approach to creating learning environments that cater to diverse needs, abilities, and backgrounds. We share practical principles and evidence-based strategies, in addition to how these principles were consistently applied in practice through examples of our work. Through shared, transparent practices, we will demonstrate how accessibility and inclusion-first approaches can be embedded in micro-credential design, in order to provide a practical approach that can be adopted by others to build more equitable micro-credentials and enhance the quality of learning for all.

The RISE learning framework was developed to address a persistent gap in online learning design: the disconnect between pedagogical theory and practice. While social constructivist principles emphasise active engagement, formative feedback

The RISE learning framework was developed to address a persistent gap in online learning design: the disconnect between pedagogical theory and practice. While social constructivist principles emphasise active engagement, formative feedback and alignment, many digital courses continue to rely heavily on passive content delivery. RISE (Relevant, Interactive, Structured, Engaging) offers a practical, discipline-agnostic conceptual tool that supports academics and learning designers in co-creating purposeful, student-centred online learning experiences. Unlike traditional activity-type taxonomies, RISE clearly distinguishes between passive (acquisition) and active (application) tasks, emphasising alignment with learning outcomes and the integration of formative feedback. It promotes the inclusion of collaborative learning experiences, recognising the value of peer interaction in fostering engagement and supporting learning outcomes, and foregrounds authenticity by encouraging the design of learning that reflects professional practice and builds industry-relevant capabilities. This poster introduces the conceptual foundations and development of the RISE learning framework, explores its use in collaborative course design, and outlines our plan to evaluate its use through a structured survey capturing academic and learning designer perspectives. Findings from this evaluation will inform future refinements to the framework.

This proof-of-concept study explores the feasibility and usability of an interactive curriculum mapping dashboard designed to support informed decision-making around ophthalmology trainee rotations. Developed using data from the Royal

This proof-of-concept study explores the feasibility and usability of an interactive curriculum mapping dashboard designed to support informed decision-making around ophthalmology trainee rotations. Developed using data from the Royal Australian and New Zealand College of Ophthalmologists’ eDiary (surgical logbook) and Curriculum Component Survey, the dashboard allows stakeholders including trainees, supervisors, training networks, and the college to visualise curriculum coverage and identify potential gaps in clinical learning across training sites. Two key datasets informed the project: (1) 2023–2024 eDiary data, selected due to improved completeness following the introduction of required minimum procedures, and (2) 2023 Curriculum Component Survey data, which captured the type (Observe, Assist, Perform) and frequency (Frequent, Moderate, Occasional) of curriculum exposure reported by training sites. Data were integrated and visualised using Microsoft Power BI, with dashboard prototypes tested by college staff, Fellows, and committee members. The results highlighted substantial variation in clinical exposure across training posts and demonstrated how dashboard filters could assist in aligning individual trainee needs with available learning opportunities. User feedback confirmed the dashboard’s value in supporting planning and transparency, while also emphasising the importance of data accuracy and quality to ensure trust and usability. Overall, this study demonstrates the potential of a curriculum mapping dashboard to enhance data-informed training decisions in specialty medical education.

Generative artificial intelligence (GenAI) is rapidly reframing academic practice, yet staff confidence to harness its potential remains uneven. Many university staff indicate that a “lack of familiarity with the technology, uncertainty

Generative artificial intelligence (GenAI) is rapidly reframing academic practice, yet staff confidence to harness its potential remains uneven. Many university staff indicate that a “lack of familiarity with the technology, uncertainty about its use, or a lack of time to engage, contributed to their reluctance to use AI tools for their work” (McDonald, 2024). Building this confidence demands accessible opportunities that honour diverse starting points, and courageous experimentation which normalises trial-and-error—two of the principles guiding the University of Newcastle’s GenAI response. Our GenAI Tinker Workshops operationalise these principles by offering low-stakes, experimentation-based experiences where educators co-explore AI tools, reflect on ethical dimensions and iterate on real teaching artefacts. Playful, informal learning environments may lower cognitive load and heighten curiosity by reducing the focus on serious workplace implications (O’Hara & Lo, 2025). Tinkering studios, for example, cultivate “permission to fail” that supports creativity and innovation (Henriksen, 2021). The informal, low-stakes format of the sessions promoted engagement, echoing Worth’s (2024) assertion that “AI playgrounds” backed by appropriate guidance can support learning. Responding to TEQSA’s call for structured capacity-building around GenAI (TEQSA, 2024), Learning Design & Teaching Innovation designed monthly Tinker Workshops capped at roughly ten participants. Each 60-minute session invited academics to “tinker” with tools like ChatGPT, NapkinAI Copilot, NotebookLM and Gamma to draft real artefacts (course plans, presentations, podcasts, images, etc) for use in their teaching activities. Facilitators guide the participants through a simple introductory activity and focus on identifying opportunities to promote discussion in the group. Evaluation of the workshops, through informal participant feedback and in-session observations, showed an appreciation for this approach. Participants reported increased confidence not only with the tools but with navigating rapid change more broadly, citing reduced anxiety and a stronger sense of community. Participants noted possible operational benefits identified by exposure to various AI tools (example comments – “this will save me so much time” and “That just took about 20 seconds, it would take me three days to do the same.”). They also developed insights beyond the immediate operational focus of the activity (example comments – “I’d never thought of structuring my course that way, it’s really clear” and “This has really helped me think about how I use images and graphics in my lectures.”). Further, the informal nature of the sessions, with facilitator positioned as fellow learner rather than expert instructor supported honest discussion and debate around the implications (both positive and negative) of GenAI (example comments – “it’s just good to be able to talk about this stuff, and know everyone is in the same boat” and “I kind of knew that not all AI is not bad, but have not had the time to learn more.”). End of session discussion is guided towards awareness of the fallibility of GenAI outputs, and the importance of human expertise in co-creating learning experiences with GenAI. By embedding accessible, iterative, low-stakes Tinker Workshops alongside more traditional GenAI initiatives, we aim to directly tackle the challenge of uneven confidence driven by unfamiliarity, uncertainty and limited time. The format normalises trial-and-error, scaffolds ethical reflection and focuses “AI playground” tinkering on real world use cases—delivering immediate efficiency gains while supporting consideration of broader pedagogical impacts. Participants report reduced anxiety, stronger professional community and increased confidence in decision making around the use of GenAI. In short, structured opportunities to experiment safely are building adaptable educators who can collaborate with AI responsibly, meeting TEQSA’s call for capability-building and strengthening resilient, human-centred learning.

In today's data-rich educational environment, the ability to leverage institutional data effectively for course quality assurance and curriculum oversight is critical. Research indicates that automation of data has been a longstanding

In today's data-rich educational environment, the ability to leverage institutional data effectively for course quality assurance and curriculum oversight is critical. Research indicates that automation of data has been a longstanding feature of the education sector. Bhardwaj and Kumar (2025) found that institutions have adopted Robotic Process Automation (RPA) to enhance operational efficiency. Shaulska et al. (2021) demonstrate how Power BI can be used on the University management system to monitor, analyse, and improve the university’s value proposition through data visualization and business intelligence. Liu et al. (2023) argue that visualising Learning Management System (LMS) data helps educators better understand student engagement and learning behaviours and supports data-informed decision-making. From a learning design support perspective, this paper outlines a scalable, automated solution project that integrates Power BI, Python, Power Automate, and various data platforms to enable efficient and insightful academic decision-making. Drawing on data from institutional sources—including Canvas LMS, PeopleSoft, and Microsoft suites—this approach generates interactive dashboards that streamline course reviews and site management. Custom Python scripts (similar to Vashisht et al., 2021) retrieve and process LMS data, while Power Automate facilitates real-time data collection from Microsoft Forms and other sources. This data is processed and visualised in Power BI to support curriculum and learning design operations. Two key outputs are presented: Course Review Dashboard – Captures feedback and audits course quality via forms that automatically feed into Power BI. It draws on data from Canvas and PeopleSoft to present a view of course readiness. The automation and its dashboard iterations were intended to help Group-based leadership track course preparation for the upcoming period. Course Site Overview Dashboard – Supports pre-term preparations by monitoring course site setup status, including homepage configuration, staff pages, announcements, rubrics, and learning material customisation. This tool enables teaching and learning teams in ensuring course sites meet institutional standards before they are published. Automated notifications are sent to stakeholders through email triggers based on course readiness, missing elements, or quality issues. This reduces manual monitoring and allows targeted support to convenors and teaching staff, improving progress efficiency (Varun et al., 2024), with a focus on the student experience. The dashboards also support evidence-based decisions for curriculum improvements and staff development. Our approach illustrates system architecture, automation workflows, and real-world use cases in an Australian university, demonstrating how the adoption of an integrated digital ecosystem can lead to more informed, timely, efficient, and insightful academic decision-making and effective learning design practices. This automation is currently being adopted across three of four Academic Groups. Future directions include expanding university-wide and researching its application across all Academic Groups. Overall, our approach highlights the potential of low-code/no-code automation and Power BI tools in higher education to address administrative challenges, foster proactive teaching quality engagement, and streamline cross-team collaboration through data transparency. Sharing this approach can benefit learning designers, academic leaders, and ed-tech specialists in building sustainable and efficient systems for curriculum quality and academic readiness using existing institutional tools.

The growth of online learning in higher education, accelerated by technological advancements and the COVID-19 pandemic, has highlighted the importance of accessibility and flexibility for students. Within this context, cognitive engagement

The growth of online learning in higher education, accelerated by technological advancements and the COVID-19 pandemic, has highlighted the importance of accessibility and flexibility for students. Within this context, cognitive engagement refers to the mental effort students invest in understanding and internalising content (Martin & Borup, 2022), which is positively linked to student satisfaction and academic performance (Fredricks et al., 2019). As such, fostering cognitive engagement should be a central focus in the design and delivery of online learning. This study explores how university educators perceive students' cognitive engagement in online learning. Limited research examines how university educators' perceptions align with learning designers and students on cognitive engagement in online learning. Understanding this is important as misalignment may impact student learning outcomes. Sixteen teachers (male: 8; female: 8) from two Australian universities completed a survey containing five Likert-scale items (from 1 = strongly disagree to 5 = strongly agree) exploring their perceptions of students' cognitive engagement across learner-to-teacher, learner-to-learner and learner-to-content interactions (Moore, 1989). The questionnaire was adopted from Chi et al. (2014) Interactive, constructive, active and passive modes of cognitive engagement (ICAP) framework. The participants taught various disciplines including law, business, engineering, science, and health. Of the participants, five reported having fewer than five years of online teaching experience, six had between six and ten years of experience, and seven had been teaching online for more than 11 years. This sample represents the diversity of Australian university educators and demonstrated a balanced distribution of online teaching experience. Preliminary quantitative analysis indicated that educators perceived students demonstrate higher levels of cognitive engagement when they: (1) received one-on-one guidance and feedback on assessments from their teacher (mean = 4.37), (2) engaged in peer debates on case studies (mean = 4.31), and (3) worked on authentic problem-solving tasks (mean = 4.31). In contrast, the majority of participants perceived lower levels of student cognitive engagement under the following conditions: (1) when teachers delivered online lectures for more than one hour (mean = 2.87), (2) when students were solely reading online content (mean = 2.5), (3) when students reading and clicking through an online presentation (mean = 2.75) and (4) when student watched a video (mean = 2.38) or pre-recorded lecturing video (mean = 2.43) without engaging in active strategies (mean = 2.38). The initial findings suggested that university educators perceived student cognitive engagement primarily through their observations during online classroom and the quality of students’ contributions to peer interactions and assigned tasks. Notably, educators expressed the view that activities, such as reading and clicking through online presentations, do not effectively foster cognitive engagement. This perspective stands contrary to Goode et al. (2022) claims, which suggest that such activities can contribute to learning outcomes. As this study is in its initial stage, the current sample size is relatively small. Ongoing data collection will increase participant numbers, enabling a larger-scale investigation into how university students perceive cognitive engagement in online learning. Expanding the sample will help to strengthen the robustness and generalisability of the findings. Furthermore, we will explore how these perceptions align and differ from those of learning designers and students. Ultimately, the findings aim to inform learning design and teaching practices in higher education to promote effective online learning.

This poster presentation provides a visual/graphical analysis of the design and implementation of two iterations of an interdisciplinary engineering capstone project. The poster provides a graphical representation of the core project

This poster presentation provides a visual/graphical analysis of the design and implementation of two iterations of an interdisciplinary engineering capstone project. The poster provides a graphical representation of the core project concepts using the analogous circuit for a loudspeaker system as a metaphor for transforming pedagogy (Buskes et al., 2023; Cochrane, Harris, et al., 2024). The poster also graphically maps the project against two analysis frameworks: Activity theory (Cochrane, 2024; Cochrane, Galvin, et al., 2024) and Kolmos et al., (2024) model of interdisciplinary project types in engineering education, mapped to the metaphor of the transformation of energy in a loudspeaker system as an illustration of transforming pedagogy to inform the discussion with participants. An important part of the engineering design process is to understand the interface with other disciplines of engineering and to be able to specify appropriate requirements and verify that those requirements are being met. If groups of engineering students do not interact while at university, they are ill-prepared to do such design across disciplinary boundaries in the workplace. Moreover, if they are incapable of being able to formally specify what they require from other engineers, then they would not be able to verify that the design meets those specifications. The project implemented an educational design project to develop a multi-disciplinary final year capstone project involving students from the Department of Electrical and Electronic Engineering as well as the Department of Mechanical Engineering. Designing a loudspeaker system, which contains electrical and mechanical systems that interact in a complex transfer of energy from electrical to mechanical to acoustic energy, is an inherently multidisciplinary endeavour consisting of both electrical and mechanical engineering concepts. The equivalent circuit of a loudspeaker system also serves as a metaphor of how the project aims to not only transform energy from electrical to acoustic, but fundamentally transform pedagogy (Mezirow, 2018) from teacher-centred to student-centred design teams to develop learner agency (Hase & Blaschke, 2021). The project case study is informed by a scoping review of the literature around interdisciplinary education projects, with an a priori protocol. The project is framed using Educational Design Research (McKenney et al., 2022) that involves collaboration from key stakeholders. As well as the Poster the project methodology will be shared with conference participants through an accompanying PADLET page to share the presentation links and resources, as well as engage the participants in a Poll and invite questions and contributions from the participants, including sharing examples of their own case studies of designing and implementing interdisciplinary real world educational projects.

This poster explores the concept of liveness (Chhaya, 2015; Lee, 2021; van Es, 2017) within the conference theme Your Journey: here, the journey is the path of engagement, reflection and new knowledge for attendees at ASCILITE 2025. For

This poster explores the concept of liveness (Chhaya, 2015; Lee, 2021; van Es, 2017) within the conference theme Your Journey: here, the journey is the path of engagement, reflection and new knowledge for attendees at ASCILITE 2025. For TEL practitioners and researchers, liveness at the conference involves working with context (of the presenters' institutions, of the history of theories and technologies) as we enter the twists and turns of a project timeline, engaging with the presenter as a fellow traveler accompanied by their tech companions. Beyond the conference, liveness can inform practitioners’ designs, interactions, and evaluations of their tech-enabled educational work. Taking a socio-material perspective (Fenwick et al., 2011) allows the authors to examine content as well as networks, spaces, technologies, interactions, and affect (Lupinacci, 2019) generated through participation at ASCILITE. The authors will engage in collaborative autoethnography (Chang et al., 2012) as the method for interrogating the learning journey of attending this conference and future conferences. Departing from traditional poster presentations, this evolving document enables attendees to add to the space available in the poster for near-real-time content generated from the conference experience. We invite participants to engage with the authors and the poster itself by contributing via social media and on Padlet using the provided QR codes to share their reflections on this conference and the ASCILITE journey. We aim to encourage a timely immediate engagement with authors of new knowledge, as characterised in constructivist and experiential learning environments. Utilising poetic inquiry and reflexive praxis as diverse examples of tertiary practice (Table 1, S5), the authors will create an emergent poster by mining social media around online engagement at the conference and by using bricolage (Honeychurch, 2023) to add to relevant areas of the poster (Table 1, based on the Activity-Centred Analysis and Design (ACAD) framework (Goodyear et al., 2021) for learning designs: epistemic (“liveness”), social (“community”) and set (“technologies and tools”). This approach utilises TEL practice for a timely and effective surfacing of attendee reflections (Gibbs, 1988) and conference evaluation. It challenges the notion of the conference as merely a collection of "what was", instead, positioning it as a space to look forward to and encourage creativity, connectivity and learning (Bryant, 2024; Casey et al., 2024). The completed poster will provide a novel evaluation of the conference experience (Chapman et al., 2007) by integrating reflection directly within the conference and prompting the community to put their learning into practice.

Background As higher-education providers unbundle programs into micro-credentials and other variable-credit offerings, educators need a way to convert credit points into balanced hours of teaching and learning. In Australia, this is

Background As higher-education providers unbundle programs into micro-credentials and other variable-credit offerings, educators need a way to convert credit points into balanced hours of teaching and learning. In Australia, this is complicated by the lack of a national conversion formula and the coexistence of units that may carry anything from a small to a large credit point (e.g., 1 to 24 credit points or the local equivalent). Working in a central educational-practice team charged with curriculum innovation and architecture, we were repeatedly asked: How many credit points—and corresponding hours—should we allocate to a given mix of learning and assessment activities? What guidance can we offer when a unit carries fewer credit points than our legacy subjects? How can we design stackable short courses that still meet university policy and external volume-of-learning requirements? Aspiration and approach To address the above needs, our aim was to create a scalable sizing framework and digital workload estimator that aligns credit points, assessment, and student effort while remaining adaptable across diverse credit systems. Drawing on sector guidelines, workload literature, and institutional policy, we produced step-by-step guidance for balancing scheduled hours, learner-directed study, and assessment effort. This guidance is hosted on SharePoint and was then turned to a lightweight digital tool called Student Workload Estimator (SWE)—which generates course workload maps visually and supports adaptable program structures. Development snapshot We began with a spreadsheet prototype that encoded word-to-time equivalences and assessment-load caps. In collaboration with the university’s evaluation specialist, this logic was rebuilt in a low-code platform using Microsoft Power App, maintaining security and version control. All formulas derive from an evidence-informed framework; full methodological detail will appear in a companion journal article. Poster experience The poster will visualise student workload estimator’s workflow, illustrating the underlying hour-allocation logic. Audience takeaways include: A visual map of the literature and guidelines that underpin the credit-to-hours formulas, plus a QR link to the full bibliography. An annotated diagram of the framework’s core components (baseline contact hours, task-to-time multipliers, assessment-load caps) with tips for local adaptation. A scan-to-watch demo video walkthrough of the SWE, plus downloadable templates and a facilitation guide for CP, ECTS, or contact-hour models. Relevance to “Adaptable Learners” themes The Student Workload Estimator provides educators a real-time visibility of workload requirements, allowing courses to be flexible across credit points while considering learner well-being in workload. By translating high-level policy into an intuitive digital resource, the tool not only models how technology can nurture adaptive learning communities but also provides a practical mechanism for delivering the flexible learning options today’s adaptable learners need. Next steps Since its launch a year ago, the estimator has attracted steady enquiries and positive feedback from educators who report clearer workload conversations and smoother course-approval cycles. Building on this momentum, we will: (1) publish a research article on its theoretical foundations and curricular impact; (2) add use requested functions—such as creative-project workload calculators—via co-design workshops; and (3) develop a student-facing version to help learners plan and manage their own study time.

Background Digital access and flexible delivery approaches have become increasingly important in higher education, particularly with advances in blended and online learning. In the last decade, Learning Management Systems (LMSs) have

Background Digital access and flexible delivery approaches have become increasingly important in higher education, particularly with advances in blended and online learning. In the last decade, Learning Management Systems (LMSs) have emerged as essential platforms that facilitate adaptable, resilient, and learner-centered environments (Pozo-Sanchez et al. 2022; Olszewski & Crompton, 2020). Our institution has recently transitioned to an innovative LMS, powered by Canvas, Microsoft Teams, and integrated with complementary digital tools, entitled ‘MyLearn Ecosystem’. The ‘MyLearn-My Experience’ study was established to explore the educators’ experience in using the MyLearn Ecosystem. Method A mixed method approach was employed to gather reflections from academic staff during the first year of MyLearn implementation through an anonymous online survey. The study measure user experiences in different domains and the key focuses of this paper are reflections on functionality, communication tools and support of MyLearn. Quantitative data was analyzed using SPSS and thematic analysis was conducted for qualitative data. Findings Overall, there were 28 respondents with 17 completing all the questions. All respondents were aged between 36-55 years and 93% were females. Most participants (80%) held permanent employment status. Slightly over 80% of participants never used Canvas software prior to the MyLearn ecosystem; however, just under 80% of them reported that they were proficient in using digital technology. Some functions and tools for teaching and learning activities were commonly used by 60% of participants. There were some functions and tools that were never used by most of the respondents, including the Discussion Forum (40%); New Analytics (53%); and MyLearn Calendar (60%). The reliability of the system was rated as poor function by 80% of respondents followed by MS Teams meeting as an online class (60%). By contrast, 80% of the respondents rated ‘access to classes and ‘access to resources’ as acceptable or good functions in MyLearn system. Most of the reflections in using MyLearn system were negative experiences due to the poor reliability of the system and additional workload to cope with adaptation to the new system. Some quotes from reflections: “It has increased my workload”; “… add many administrative work”; “MS Teams has never worked well”; and “I was blocked from the online chat forum”. Outcomes and Implications This study revealed the user experience in adaptation to digital transitions in LMS platforms that could influence adaptability, teaching quality, and stakeholder satisfaction among educators. These findings recommend ongoing improvements to ensure that MyLearn Ecosystem continues to support the quality of teaching and learning based on the evolving needs of educators while sustaining positive learning outcomes.

Students trust GenAI-summaries of academic articles despite known issues of hallucinations and errors (Markowitz, 2024). Although this saves time, it costs understanding and engagement with the research findings, context, and authors. In

Students trust GenAI-summaries of academic articles despite known issues of hallucinations and errors (Markowitz, 2024). Although this saves time, it costs understanding and engagement with the research findings, context, and authors. In addition, within the academic text, writers craft a credible sense of self alongside balanced representation of subject matter to create a persuasive argument (Hyland, 2005; Ivanic & Camps, 2001; Matsuda & Tardy, 2007). Students are increasingly relying on GenAI to provide summaries of academic articles (Newell & Dahlenburg, 2024). The changes in the way that readers (in this case, student readers) engage with scholarly knowledge is often explored from the perspective of the reader (Schmidt & Meir, 2023; Xia et al., 2025). Comparatively little attention has been paid to how authors’ feel about the proliferation of GenAI-summaries of their work. As such, we explored journal article authors’ perceptions of the accuracy of GenAI summaries of their work. We conducted semi-structured interviews with 20 Australasian-resident authors to compare a summary they wrote with an AI-generated summary (ChatGPT4). Interview transcripts were analysed qualitatively through Reflexive Thematic Analysis (Braun & Clarke, 2021). The following research questions were posed: 1) How are AI-generated journal article summaries perceived as accurate/inaccurate by their authors? 2) How do authors feel about the author-reader relationship when readers only engage with GenAI-summaries?, and 3) What potential implications exist when using GenAI-summaries for learning and teaching? Authors noted although the AI-summaries appeared accurate overall, they were accurate but vague. However, as we progressed through the interviews, authors identified inaccuracies and omissions of: context, disciplinary conventions and concepts, important findings and limitations, and connection/attribution of ideas to prior authors. Participants described how AI-summaries present author suggestions as established facts. The absence of methodological details was concerning because methods sections provide information on researchers’ decisions, validity of the findings, and training for novice researchers/students. In summaries of the introduction sections, prior literature was omitted, thus misrepresenting the study as an isolated unit instead of ongoing knowledge-building conversations. AI summaries, therefore, lacked a sense of scholarly community, “no map to take readers to the key people...and further reading”. Several authors explained their sense of disconnection from the reader through the loss of their voice in the linguistically “flattened” output. This felt like losing individuality as everyone’s English sounds the same. Some academic authors felt disappointed, robbed, or slapped in the face that the loss of time readers would spend engaging with their work would not be reciprocated by readers only using generated summaries. We present a model that illustrates these issues of accuracy and writer-reader relationship for educators to use to guide students through critically evaluating AI outputs. Students can make informed choices about when to iteratively prompt, and when to consult/read the full article. This model can increase student understanding of the author, community, and previous research context from which the research has evolved.

In an era of continuous change in digital education, we need educators who can not only respond to complexity but design for it. This poster reflects on my personal and professional shift from performing arts (stage acting and directing)

In an era of continuous change in digital education, we need educators who can not only respond to complexity but design for it. This poster reflects on my personal and professional shift from performing arts (stage acting and directing), and how that creative foundation has shaped my work as a curriculum and learning designer in higher education. It highlights the value of cross-disciplinary experience, particularly from the creative arts, as a driver of innovation, adaptability, and human-centred learning design. It is increasingly common for educators to transition from other professional fields into education, bringing with them diverse experiences and perspectives. Even when those fields appear unrelated, they can offer rich conceptual and practical tools for designing better learning experiences. These transitions are not detours. They can strengthen our contributions to education and broaden our capacity for innovation (Anyichie, Butler, Perry, & Nashon, 2023). Importantly, leaving the performing arts was never a failure or fallback, as I once thought. The creative skills and understanding of story and narrative that I developed are not lost but continuously repurposed in service of teaching and learning, particularly in digital contexts. For example, I use narrative mapping and visual storyboarding to co-design online learning experiences with academic staff, and apply storytelling principles to structure emotionally engaging, technology-enhanced learning environments. As an actor, I learned early the importance of failure as feedback; opportunities to reflect, adjust, and grow. This embodied experience of iterative, collaborative learning aligns closely with constructivist and social constructivist theories of education, where knowledge is actively co-created through experience, dialogue, and reflection (Powell & Kalina, 2009). However, it was directing that most significantly shaped how I now approach learning design. A director must maintain a holistic vision of the production. This involves ensuring coherence across narrative, staging, character, and tone, while also creating space for actors to explore, improvise, and contribute their own interpretations. Similarly, in curriculum design, I work to maintain a consistent narrative and conceptual structure across a course, while also leaving space for learners to personalise, question, and construct their own meaning. This practice aligns with constructive alignment, which ensures that learning activities and assessments are purposefully linked to intended learning outcomes (Biggs & Tang, 2011). However, my approach extends beyond alignment as a checklist. It involves crafting a throughline: a conceptual and emotional arc that connects outcomes, assessments, and activities into a meaningful and engaging learner journey (Cutting, 2016). This approach is particularly powerful in digital learning environments, where coherence and engagement can be harder to sustain. Tools such as narrative mapping, branching scenarios, and visual storyboarding support this process and foster collaborative dialogue with academic colleagues (Yusoff & Salim, 2014). This future-focused perspective requires adaptability. Just as a live performance adjusts to audience energy and technical constraints, learning environments must remain responsive to learner needs, shifting technologies, and broader social change. Drawing on rehearsal-based practices such as iteration, experimentation, and feedback, I design learning that is structurally coherent, emotionally engaging, and open to ongoing evolution. This poster invites fellow educators to reflect on how their diverse pathways can enrich digital education, promote creativity, and cultivate resilience in a rapidly evolving landscape. The poster will visually map the throughline metaphor, connecting performing arts practices with key learning design principles, supported by examples of narrative mapping and curriculum architecture. It will also include an interactive activity inviting participants to map their own professional journeys and identify how these experiences can inform technology-enhanced learning design. This journey traces a personal and professional trajectory across disciplines, highlighting how diverse experiences can shape innovative and human-centred digital education. At its core, learning design is an act of storytelling, crafting meaningful, coherent, and engaging journeys that help learners make sense of complex ideas and find their place within them.

Belonging is a fundamental human need that motivates individual pursuits (Baumeister & Leary, 1995). In higher education, it is closely tied to affective engagement, playing a critical role in sustaining student retention and participation

Belonging is a fundamental human need that motivates individual pursuits (Baumeister & Leary, 1995). In higher education, it is closely tied to affective engagement, playing a critical role in sustaining student retention and participation (Strayhorn, 2019). Compared to undergraduate students’ belonging, graduate students’ experiences remain underexplored (Matheson & Sutcliffe, 2018). This gap is particularly relevant for MBA students, who often invest financially, juggle multiple commitments, and adapt to new academic environments. While belonging is increasingly recognised as multifaceted (Gravett, Ajjawi, & O’Shea, 2023), research indicates that graduate students experience this primarily in the academic domain (Briant Spratling & Valdovinos, 2022). A low sense of belonging can lead to disengagement and reduced satisfaction with the course (Lee & Anantharaman, 2015). While induction programs may foster early belonging (e.g., Matheson & Sutcliffe, 2018), its dynamic nature (Allen et al., 2024) presents challenges for supporting personalised beyond initial stages. In this poster, we describe a tailored email intervention to support MBA students’ belonging by providing a schedule of timely and personalised communications, tailored to students’ goals for the program. Students in the program can tailor their curricular and extra-curricular experience based on their unique career and personal goals. Given the diversity of student pathways to the program and associated aspirations, there is substantial scope to tailor the MBA experience. Accordingly, students require support to understand the scope of choices available and make appropriate choices accordingly. This intervention was carried out over two semesters of an MBA program at the University of Technology Sydney. An initial survey was disseminated near the start of the academic year to all students in the program, to solicit their goals for enrolling in the MBA program. The survey was framed against students’ general career aspirations, disciplinary specialisation interests, profession networking interests, communication development aspirations, employment goals, mentoring interests, views on contributing to positive societal outcomes, entrepreneurial interests and international exposure interests. Following this, three personalised emails were sent over each semester via the automated feedback tool, OnTask (Pardo et al., 2018), tailored to students’ responses to the initial survey. 70% of the Autumn cohort (total enrolled = 449 students) and 27% of the new Spring cohort (total enrolled = 56) responded to the initial survey and therefore received the personalised emails. Students were invited to complete a short survey to provide feedback about the personalised emails, and to participate in an interview about their experience. Students reported positive perceptions of their personalised support, which provided timely academic guidance and enhanced the feeling of being valued. An important finding was that prior educational experiences influenced students’ engagement with their personalized advice: newcomers desired more structured mentorship, while returning students more effectively navigated opportunities to enhance integration and belonging. These findings highlight the nuances of belonging faced by graduate students, especially those from international backgrounds. In this poster, we present the challenges and key learnings from this pilot implementation of personalising support for belonging at the program level.

ePortfolios are increasingly recognised as a high-impact practice for both assessment and learning. They can enhance students’ critical thinking and reflective abilities, while also contributing to improved success outcomes in higher

ePortfolios are increasingly recognised as a high-impact practice for both assessment and learning. They can enhance students’ critical thinking and reflective abilities, while also contributing to improved success outcomes in higher education. (Eynon et al., 2017). This is due to their ability to be a useful framework for organising learning, their varied and complex pedagogical uses, and promoting high learner engagement (Hallam & Creagh, 2010; Watson et al., 2016). Yet there is scant high quality empirical research on ePortfolio implementation. In particular, there is little research on how higher education learners experience ePortfolio tasks and how these experiences intersect with student motivation, a key element of self-regulated learning (SRL). Effective self-regulation depends on learners' motivation to actively control their learning through goal setting, progress monitoring, and strategy adjustment (Zimmerman, 2002). Motivational elements, including self-efficacy and perceived value of learning and assessment tasks are key factors in fostering academically successful independent self-regulated learners in higher education (Pintrich, 1999; Lim & Yeo, 2021). However, students are expected to view ePortfolios as both an assessment by the institution of their work and a space for authentic learning agency, often creating a tension between the two (Van der Gulden et al., 2023). This tension may undermine student motivation by reducing perceived value of the learning process while increasing the perceived burden, particularly given that ePortfolios are frequently reported as time-intensive and demanding tasks (Jansenns et al., 2022). Additionally, the dual assessment-learning function may create challenges for how students construct their academic and professional identities while managing the significant labour involved in portfolio creation and maintenance. As such, a deeper understanding of students' experiences of ePortfolio may shed more light on how ePortfolios can function as effective assessment and learning tools. This poster showcases current findings from an ongoing PhD thesis project. Results from 40 semi-structured interviews with undergraduate speech pathology students at an Australian and a UK university were analysed using expectancy-value theory (Eccles & Wigfield, 2020) as a framework to uncover motivational influences towards engaging with ePortfolio tasks. The analysis explores how ePortfolio experiences intersect with assessment, learning, identity development, and academic labour to help create a motivation-informed framework for ePortfolio design, providing practical design principles for educators seeking to enhance student engagement with ePortfolio tasks.

Understanding and enhancing student engagement is crucial for online learning as it reflects student satisfaction and academic achievement. Cognitive engagement (CE) refers to students’ investment in learning through strategic, reflective

Understanding and enhancing student engagement is crucial for online learning as it reflects student satisfaction and academic achievement. Cognitive engagement (CE) refers to students’ investment in learning through strategic, reflective and self-regulatory behaviours that foster problem-solving (Chi and Wylie, 2014). It involves critical thinking, conceptual understanding and cognitive skill development. Online discussion forums serve as a key tool that facilitates CE by enabling critical thinking and collaborative knowledge-building (Ahmad et al., 2022). Analysing students’ CE in discussion forums can enhance learning systems and inform course and assessment design (Prince et al., 2020). Although CE is difficult to detect, tools like the ICAP framework offer a structured approach by categorising engagement into four observable dimensions: Passive, Active, Constructive, and Interactive (Wiggins et al., 2017). ICAP hypothesis suggests that CE increases progressively from passive to interactive (Chi & Wylie, 2014). While widely applied in synchronous settings (Barlow & Brown, 2020), ICAP has seen limited use in asynchronous online environments. While prior studies have applied the ICAP framework as a complementary tool to analyse CE in online learning, they often combine it with other models such as Community of Inquiry (CoI) or Bloom’s taxonomy and focus primarily on synchronous or manually coded environments, highlighting the need to solely apply the ICAP and automate prediction of cognitive behaviours (Farrow et al., 2022, Gorgun et al., 2022; Ahmad et al.,2022). Building on ICAP hypothesis, this research modifies ICAP framework, tailored to capture CE in discussion forums in asynchronous and fully online learning environments. The study employed a mixed-method approach, combining manual content analysis and descriptive analysis using visualisation to examine student interactions in discussion forums within STEM courses in an Australian University. Courses from IT programs across four consecutive study periods (2023-2024), each with over 80 students were selected to manually annotate and map against the modified ICAP framework (with passive excluded, and dimensions categorised into three levels low, medium, high) using keywords and phrases of the discussion forums. Inter-rater reliability was 100%, as project team members collaboratively resolved conflicts. The mapped data was then evaluated descriptively through visual and text analysis to uncover deeper patterns of CE. Students demonstrated higher active and constructive engagement, but gains from constructive to interactive were limited. To better support CE, forums should be designed to encourage more student interactions. To better support cognitive engagement, online discussion forums should be designed to encourage more interactions among students. These preliminary findings pave the way for empirical validation of the modified ICAP framework in future controlled studies, though generalisation is yet to be established due to domain specificity. The research highlights the importance of educators understanding students CE in fully online and asynchronous learning and adopting the modified ICAP framework. This can be further utilised to better design the online courses to encourage deeper student participation, help students move from passive-active-constructive-interactive engagement. As universities continue to expand online education, understanding how to structure discussion activities to improve student CE is essential for better learning outcomes and shaping online teaching practices.

Decades of research have advised that visually engaging slides with minimal text can enhance learning (Klemm 2007; Mayer 2008; Kustritz 2014, Lenz et al. 2015; Naegle 2021). Yet, text-heavy lectures and presentations are still delivered in

Decades of research have advised that visually engaging slides with minimal text can enhance learning (Klemm 2007; Mayer 2008; Kustritz 2014, Lenz et al. 2015; Naegle 2021). Yet, text-heavy lectures and presentations are still delivered in tertiary education contexts today. This paradox offers a valuable opportunity to reflect and grow as educators in an era of continuous change, where the way we deliver content matters. This poster explores this tension through the experiences of an early career academic developer at a South Australian university currently undergoing a merger. The experience has required collaboration with academics across disciplines during a period of rapid course development at scale. A synchronous online workshop was introduced to complement other course development supports like individual consultations. The workshop unpacks new curriculum guidelines and key concepts like constructive alignment with academics (de Grave et al. 2014). A PowerPoint slideshow guides the workshop, and two breakout room activities allow academics to apply their learning and provide feedback to each other (Bertholini 2024). While the breakout rooms were engaging, the didactic segments guided by the slides often fell victim to the “death by PowerPoint” (Harden 2008) effect. The irony is that this phenomenon is something that we academic developers teach academics to avoid in other faculty development programs. Even so, we succumbed to the default bullet point communication mode and included excess text on the slides. The main reasons for this were to have consistency across different academic developers delivering the workshop and because the slides were later provided as handouts (Issa et al. 2011; Harden 2008). The solutions for improving the slides were not new or groundbreaking. They included replacing written explanations with diagrams and images, implementing Mayer’s (2008) multimedia design principles, creating more thoughtful presenter notes and providing separate handout materials (Kustritz 2014; Issa et al. 2011). However, the key learning from this experience was not about effective slide or workshop design. The key learning, which will be the focus of this poster, was the necessity of pausing to examine our default practices and make improvements that lead to better teaching and learning, even when the advice is already familiar. In academic development, our learners are academics; but best practices for designing learning experiences for tertiary students should also inform the design of things like our workshops (de Grave et al. 2014). Tensions between pedagogical ideals (e.g. effective workshop and slide design); and practical constraints (e.g. time pressures and the need to cover content); will always be present. Therefore, it is essential that we actively create moments of reflection to review our practices (McAlpine et al. 2009). Embracing the idea that changes are iterative, not instantaneous, this poster calls for educators to pause, revisit default habits and digital tools with fresh eyes, and consider how small shifts in practice can contribute to more engaging and learner-focused teaching. This poster includes interactive elements that encourage participants to contribute their own reflections to the conversation.

This presentation will outline the implementation and dissemination of a Teaching Squares approach with a focus on enhancing academic learning (sessional staff and continuing), collegiality, and networking across all seven academic units

This presentation will outline the implementation and dissemination of a Teaching Squares approach with a focus on enhancing academic learning (sessional staff and continuing), collegiality, and networking across all seven academic units within the University of South Australia (UniSA). We identified that the Teaching Squares approach was a safe and valuable approach for continuing staff to view, meet, reflect, and ideate on their teaching while observing their colleagues from the same academic unit. Based on these positive findings garnered through questionnaires and focus group interviews, we now wish to extend this study to include sessional staff, a cohort of teaching staff that are under-represented in the literature concerning Teaching Squares support. We will outline how we developed a community of practice to include staff across all academic units. We then purposely connected a maximum of four staff from different units so that we can further determine the benefits of staff learning and networking while viewing and interacting with colleagues from distinct and unique disciplines. Through a combination of pre-and post-questionnaires, we collected data on staff perceptions, experiences, and learnings through the Teaching Squares approach. More detailed data was then obtained through focus group interviews. The outcomes of these findings and this project has the potential to greatly enhance sessional and continuing staff belonging, reflective practice and networking, which will result in enhanced teaching practice and student learning.

The aim of this project is to explore how Fink’s Taxonomy (Fink, 2013) can be integrated into Bloom’s Taxonomy (Bloom et al., 1956; Biggs, 1996) to support both academic and professional development. In higher education, constructive

The aim of this project is to explore how Fink’s Taxonomy (Fink, 2013) can be integrated into Bloom’s Taxonomy (Bloom et al., 1956; Biggs, 1996) to support both academic and professional development. In higher education, constructive alignment has been widely used for curriculum design and validation, as well as quality assurance (Biggs, 1996; Anderson and Krathwohl, 2001; Jaiswal, 2019). The important role of Bloom’s Taxonomy in guiding constructive alignment in teaching practice has been studied and recognized (Anderson and Krathwohl, 2001; Momen et al., 2022; Sudirtha et al., 2022). While its focus on cognitive domain facilitates the design of learning outcomes and assessments with expected cognitive skills, Bloom’s Taxonomy neglects affective factors in learning (Soozandehfar and Adeli, 2016; Wu et al., 2019; Momen et al., 2022). In contrast to Bloom’s hierarchical taxonomy, Fink’s non-hierarchical taxonomy considers personal, social and emotional aspects of learning, promoting a more comprehensive learner-centred learning experience (Levine et al., 2008; Fink, 2013; Gravett and Bach, 2024). Based on the nature of Fink’s Taxonomy, we investigate how Fink’s Taxonomy dimensions can be integrated into Bloom’s Taxonomy to enhance constructive alignment in curriculum design to support learner’s development of life-long learning skills for success in both academic and professional life. To translate educational theory into practice, we integrate inquiry-based and collaborative learning and adopt a flipped classroom model to enhance student engagement and cognitive development (Koretsky et al., 2015; Dellatola et al., 2020). To support diverse learner needs and foster active learning, we leverage technology-enhanced communication platforms and employ multimodal channels. Furthermore, we implement self-assessment and peer-assessment mechanisms to promote metacognitive awareness and deep learning through structured reflection and peer feedback (Topping, 2009). The implementation of these strategies across two postgraduate units has demonstrated the feasibility and pedagogical value of our framework. However, the rapid emergence of AI technologies has prompted a question: how can we integrate AI technologies into the framework while fostering the development of fundamental life-long learning skills? This challenge defines the next phase of our project.

Academic integrity is a cornerstone of ethical scholarship and fair and credible higher education. However, many students – particularly those from underrepresented backgrounds (Bretag et al., 2019; Devlin et al., 2018; Dockery et al

Academic integrity is a cornerstone of ethical scholarship and fair and credible higher education. However, many students – particularly those from underrepresented backgrounds (Bretag et al., 2019; Devlin et al., 2018; Dockery et al., 2016; Webb et al., 2024) such as international, low socio-economic, and regional, rural and remote cohorts - struggle to understand its principles and institutional expectations (Birks et al., 2020; Locquiao & Ives, 2020, 2024; McCabe et al., 2012; Waltzer & Dahl, 2023). These challenges are often shaped by systemic barriers, which can lead to disproportionate rates of unintentional misconduct, disadvantage (Dockery et al., 2016; Webb et al., 2024), and poorer learning experiences. Existing academic integrity education often fails to address these inequities (Bretag et al., 2019; McCabe et al., 2012) relying on generic, compliance-focused, one-size-fits-all approaches that do not fully meet the needs of these diverse learners. This project addresses these gaps by creating interactive digital resources that promote ethical decision-making and academic resilience for all students. Unlike traditional technology enhanced learning models, it embeds inclusive design and student co-creation at its core. Students were engaged as active partners in the design of these resources, ensuring their voices shape both pedagogical and practical decisions. Grounded in constructivist learning theory, this project drew on inclusive education design, and students-as-partners frameworks (Cresswell, 2011; Gravett et al., 2020; Tennyson, 2010). Constructivist principles informed the use of authentic, scenario-based learning to support ethical reasoning, while iterative co-design cycles, guided by the students-as-partners approach, ensured the materials reflected diverse perspectives and needs. The project was implemented across multiple phases, using both quantitative and qualitative methods to investigate students’ knowledge and understanding of academic integrity. Results from an online questionnaire showed that while most students could correctly identify plagiarism, fewer understood subtler concepts such as paraphrasing and correct referencing. Focus group discussions further highlighted varied experiences with academic integrity education. Students described current online modules as outdated or unengaging and expressed a need for more practical resources as well as ongoing support to navigate academic integrity expectations. The previously outlined theoretical foundations, together with the collected data, guided the development of scenario-based resources, including case-studies, interactive digital tools such as an AI chatbot, and staff guides and training material. Student co-creators from diverse backgrounds collaborated with academic staff to design, refine and test these materials for accessibility and relevance. Preliminary findings highlight that student co-created materials improved students’ understanding of academic integrity and increased their confidence in ethical academic practices. Staff also report greater ease in integrating practical academic integrity concepts into their teaching. This work demonstrates how academic integrity education can move beyond a ‘one-size-fits-all’ approach, offering a scalable, equity-driven model – supported by innovations such as interactive AI - that better serves the realities of today’s diverse higher education landscape.

Educators often rely on textual data from student evaluation comments and feedback survey responses to gain insights into students’ learning, understand their perceptions of educational innovations, as well as to evaluate curricula for

Educators often rely on textual data from student evaluation comments and feedback survey responses to gain insights into students’ learning, understand their perceptions of educational innovations, as well as to evaluate curricula for improving educational practices. Such nuanced data from individual students capture subjective perceptions and experiences, and are analysed through interpretive lenses in qualitative research (Denzin & Lincoln, 2011). However, large corpora of data present significant challenges in being able to scale qualitative analysis. In this poster submission, we present a novel multi-agent architecture using large language models (LLMs) for analysing open-text responses as a possible solution to this problem. Building on our previous LLM-based workflow (Bakharia et. al., 2025), our agentic workflow involves multiple steps for responsibly automating the inductive thematic analysis process (Lochmiller, 2021) including validation with a multi-stage process designed to ensure analytical rigour and reliability. Our workflow first finds stable themes within each document by making multiple parallel calls to a LLM, generating a wide range of possible themes. We then use semantic clustering to identify themes that appear across many runs, going beyond just keywords. A verification step checks that all quoted evidence actually exists in the original text, preventing hallucinations and grounding themes in real student voices. Next, all themes go through a refine-and-review loop. A critic agent gives feedback on the quality of each theme, and a refiner agent improves the name, rationale, and keywords. Once all documents are complete, the system groups similar themes using hierarchical clustering to find broader categories. To support human interpretation, we built a user interface that includes a Sankey diagram to show how themes connect back to the original documents. Researchers can interact with the diagram to see the actual quotes behind each theme, providing clarity and context. Our approach emphasises trustworthiness through built-in verification and ensuring transparency at every level of abstraction. Our workflow also incorporates human-in-the-loop processes to ensure rigour.

This exploratory project addresses the ASCILITE 2025 conference theme—Future-Focused: Educating in an Era of Continuous Change—by introducing an innovative virtual reality (VR) experience designed for over 300 first-year business students

This exploratory project addresses the ASCILITE 2025 conference theme—Future-Focused: Educating in an Era of Continuous Change—by introducing an innovative virtual reality (VR) experience designed for over 300 first-year business students per term. Aligned with the sub-themes of AI and Human Synergy, Inclusive Futures, and Adaptable Learners, students engage deeply with a real-world airline case to explore the SERVQUAL framework (a widely used model and research instrument for assessing service quality): reliability, assurance, tangibles, empathy, and responsiveness. Advancing TEL Research and Practice: Responding proactively to continuous educational change, this initiative combines immersive technology with AI-led oral assessments. Grounded in contemporary Technology-Enhanced Learning (TEL) literature, it promotes embodied and accessible learning as an alternative to anxiety-inducing traditional oral assessments (Alcorn & Cheesman, 2022; El Shazly, 2021). Innovative Practice: Students initially explore the airline case study through traditional classroom activities before transitioning to an interactive VR environment. Here, they assume the role of airline customer service staff, interacting with AI-powered avatars portraying airline passengers. This enables students to apply SERVQUAL principles through authentic conversational scenarios. AI-led oral assessments offer immediate, personalised feedback, significantly reducing assessment anxiety, logistical complexity, and associated costs (Alcorn & Cheesman, 2022; Gardner, O’Leary, & Yuan, 2021; Yong, 2020). Theoretical Foundations: The project integrates experiential learning theory (Kolb, 2015) and cognitive apprenticeship (Matsuo & Tsukube, 2020), providing authentic professional experiences supported by structured opportunities for reflection. Drawing from social constructivist principles (O’Connor, 2022; Richardson, 2003), students collaboratively analyse their VR interactions, fostering critical thinking and resilience. The design highlights AI’s capacity to enhance motivation, reduce anxiety, and support fair, inclusive assessments (Luckin, Holmes, Griffiths, & Forcier, 2016; Rane, Choudhary, & Rane, 2023). Enhancing Accessibility and Learner Experience: A core aim of this pilot is exploring student acceptance of AI-driven oral assessments, given their novelty compared to traditional methods. Qualitative data collection included surveys, student reflections, and assessor feedback designed to capture key student perspectives on fairness, adaptability, and overall learning experience. Guided by social constructivism, this learner-centred approach is essential for evaluating the effectiveness and scalability of this innovation (Richardson, 2003; O’Connor, 2022). Cross-disciplinary Relevance: Originally piloted within business education, the flexibility of the VR and AI framework supports adaptation across disciplines including hospitality, healthcare, and law. Flexible access options—from VR headsets to browser-based simulations—ensure inclusivity across diverse learning contexts (Asad, Naz, Churi, Tahanzadeh, & Jermsittiparsert, 2021). Collaborative Futures and Scholarly Impact: Developed collaboratively with educational technologists and interdisciplinary academics, this project exemplifies innovative digital education. Integrating AI-led assessments aligns with Education 4.0 and 5.0 trends, emphasising personalised and adaptive learning (Rane, Choudhary, & Rane, 2023), and opening avenues for future research into learning analytics, student engagement, and comparative assessments (Gardner et al., 2021; Luckin et al., 2016). This abstract presents scalable innovation, showcasing the transformative potential of immersive technology and AI-driven assessment in higher education.

As university libraries confront rising costs, shrinking budgets, unstable subscription models and expanding digital learning demands (CAUL, 2023), Open Educational Resources (OER) provide more than just student affordability: they offer a

As university libraries confront rising costs, shrinking budgets, unstable subscription models and expanding digital learning demands (CAUL, 2023), Open Educational Resources (OER) provide more than just student affordability: they offer a sustainable strategy for smarter spending. This presentation recasts OER not as an optional extra, but as essential infrastructure for modern teaching and learning, enabling libraries to deliver greater impact with fewer resources. University libraries are often forced into an impossible balancing act, attempting to deliver on their mission in a fiscally strained environment while becoming increasingly dependent on the volatile and expensive commercial textbook market for materials the institution neither owns nor controls. One institution reports paying an average of A$1,800 per commercial textbook licence (University of Adelaide, 2022). These are often recurring costs, not one-offs. Moreover, ProQuest’s announcement earlier this year (2025a, 2025b) of its plans to remove perpetual (one-off) purchase options for its widely used suite of print and ebooks is a cold discovery of just how ephemeral these “purchases” are and the lack of consultation with libraries prior to the decision, underscores the tenuous and imbalanced nature of the library-publisher relationship (CAUL, 2025). So, how can libraries continue supporting equity, access, and excellence in academia when budgets tighten and learning resources are tangled in ever-constricting commercial knots? By being strategic. OER, by design, are free, openly-licensed, forever-owned, flexible and adaptable resources which empower libraries to shift from reactive purchasing to proactive co-creation – building the system we need, rather than remaining beholden to the broken system we’ve unwittingly enabled. But OER, while free for the user, are not free for the creator, publisher, or distributor, all of whom must front-load the endeavour with their time, knowledge and technology for the future pay-off of a high-quality, free and open resource – and it’s typically the university library’s budget that covers this upfront cost which is larger than an individual commercial textbook subscription. So, we arrive at the problem. Without considering the long-term implications, when faced with a choice between the status quo of expensive, but familiar, commercial options versus also expensive, but unfamiliar, open options, university libraries can easily mistake OER as the “nice to have”. The flaw in this logic is clarified when analogised: cutting out grocery staples, such as flour, eggs, pasta, and meat, because they cost $100 a week, and replacing them with a seemingly cheap $15 takeaway meal is not a savings when factoring in three meals per day, seven days a week. That’s what cutting an OER program in favour of commercial textbook purchasing looks like. Continuing the analogy, home cooking requires effort and knowledge, but it’s cheaper per meal, adaptable, and the quality and details can be controlled. The same goes for OER: it might require upfront investment, but it saves money long-term, gives back control, and builds institutional capability. Unlike takeaway (and commercial textbooks), home cooking (and an OER) is not at the mercy of price hikes or sudden menu changes. With theoretical underpinnings in open and ecological systems (Cronin & MacLaren, 2018; Stagg, 2017) and drawing from practitioner experiences (CAUL, 2023; Desrochers, 2019; Hofer, 2017; Tlili et al., 2023), this presentation highlights how commercial textbook models represent a growing impost on public funds and how, by contrast, libraries can invest in OER to create long-term value and system resilience.

This study is providing the findings and lessons of research on Small Private Online Courses (SPOCs), a variation of Massive Open Online Courses (MOOCs) in China. Since 2013, more than 1,700 universities in China have launched SPOCs and

This study is providing the findings and lessons of research on Small Private Online Courses (SPOCs), a variation of Massive Open Online Courses (MOOCs) in China. Since 2013, more than 1,700 universities in China have launched SPOCs and millions of students have registered for credit courses. The growing use of SPOCs in Chinese higher education has reshaped how universities deliver personalised and flexible learning. Despite widespread adoption, limited research has explored how flexibility of student learning has been integrated into SPOCs. By extending the Advance HE Flexible Learning Framework (Loon, 2021), this study proposes the Flexibility for SPOC-based Online Learning (FSOL) model, a tool designed to assess the multifaceted factors of student flexibility in online learning. This model categories the complexity of flexibility in online learning with five critical factors: institutional support, teacher support, information quality, system quality and perceived employability. A survey of 294 university students in China was conducted. Exploratory factor analysis and Confirmatory factor analysis confirmed a five-factor model with high internal consistency and strong construct validity. The results, analysed with FSOL, demonstrated that the proposed factors explained 60.3% of the variance in flexibility. Findings revealed that strong institutional and teacher support enhance students’ overall learning flexibility. This is an important finding especially in a collectivist cultural context in China, where hierarchical student-institution structures affected educational experiences (Hofstede, 2001). Quality of the SPOCs, reflected in the content, layout and available support, influenced student’s use and further affected their flexibility. Embedding content for employability development also increased students’ flexibility in SPOCs-based online learning by enabling them to customise their learning paths to align with career goals. The FSOL model offers an innovative and practical contribution for evaluating flexible learning strategies in technology-enhanced learning settings. The focus on employability in the model highlights the importance of aligning course design with students' future career goals. The FSOL model can further inform future technology-enhanced learning and research to support more inclusive and effective learning in diverse global settings. This study will be beneficial to teachers who use blended and online learning. It will provide strategies on how to effectively integrate the FSOL flexibility framework, which can be adapted to non-Chinese online learning contexts.

Artificial Intelligence creates challenges for assessment integrity and validity (Lodge et al., 2023). Interactive Oral Assessments (IOA) are emerging as an academically sound and pedagogically robust assessment option to address these

Artificial Intelligence creates challenges for assessment integrity and validity (Lodge et al., 2023). Interactive Oral Assessments (IOA) are emerging as an academically sound and pedagogically robust assessment option to address these challenges (Lodge, 2024) while also supporting student employability and communication skills (Ward et al., 2023). Further, studies show that students are less likely to engage in academic misconduct when undertaking IOA that are relevant to real-world situations (Sotiriadou et al., 2020). Considering the above and recognising the power of collaboration, in 2024 a business school academic and educational designer commenced an iterative process to introduce IOA into a Postgraduate Management subject that is focused on career planning. The subject serves multiple Masters degree programs, and students come with varying levels of professional experience. IOA are uniquely suited to this subject as part of building student employability via enhancing the ability of students to articulate their knowledge, attributes, skills and experience (Daubney, 2022). IOA also support the development of students’ communication capabilities, identified as a criticalskill in graduate recruitment, with 88% of employers rating it as important and routinely assessed (Australian Association of Graduate Employers, 2020). IOA align with the Subject Learning Objectives (SLO’s), which require students to persuasively communicate their skills, knowledge, and attributes to demonstrate their employability to a professional audience. Previous assessments required students to reflect on their skills, knowledge, and experiences, develop a career plan, and submit a generic recorded career pitch. As IOA rely on authentic and genuine scenarios (Sotiriadou et al. 2025), an important first step was setting up a scenario that would resonate with the diverse cohort in the subject. In 2024, the recorded pitch assessment was adjusted to include a choice of scenarios tailored to the student personas typically enrolled in the subject. Students could choose to pitch for their first professional role; a lateral move; a promotion; or a career change. Student feedback was positive, particularly relating to the applicability of the assessment in supporting their career goals, which validated the authenticity and relevance of the scenarios. In 2025 the pitch will be replaced with an IOA where students will participate in a conversation based on one of the four authentic scenarios enabling them to articulate their communication and employability skills (Logan et al. 2017; Sotiriadou et al. 2020), demonstrate understanding of key subject content (Ward et al., 2023), and fulfil the SLOs. To replicate the real-world scenario, educators will be prepared with a set of prompts, for example, to clarify content or probe on specific topics (Pearce & Chiavaroli, 2020). Indicative results from 2025 implementation will be available for sharing at the conference. IOA effectiveness will be assessed via comparative student surveys, benchmarked year-on-year. Learnings will be applicable for academics and learning designers interested in exploring IOA, including how an iterative and collaborative design process can improve outcomes for all stakeholders, and how to manage diverse student groups. Findings may also contribute to the body of knowledge regarding IOA and their role in supporting student employability.

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)

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

As Generative AI (GenAI) technologies become more commonplace in educational settings, its far-reaching impact on assessment, teaching and learning can be felt across all educational sectors. In terms of assessment, dealing with a

As Generative AI (GenAI) technologies become more commonplace in educational settings, its far-reaching impact on assessment, teaching and learning can be felt across all educational sectors. In terms of assessment, dealing with a technology that can easily produce written work such as an essay with high levels of accuracy and written style, teachers have been challenged in navigating this new space. Two challenges exist – how teachers can effectively share specific, appropriate and permitted GenAI use for a task, and how students may share with their instructors how they have used it. Previous models of GenAI integration into assessment generally exist on a spectrum of total and free GenAI use to this set of technologies being essentially banned (see AIAS scale by Perkins et al., 2024), with little specificity. PETRA AI (PErmissive and TRAnsparent) is a single page web application that addresses these challenges by providing teachers a way to permit specific and fine-grained use of GenAI for an assessment task in the form of a digital badge and also allows students to share how they used AI for a task to ensure compliance and transparency. This badge can then be downloaded as an image or embedded into an online learning platform to provide more transparency for all parties.

The rapid evolution of digital tools and heightened expectations for technology-enhanced learning are driving academics to continually upskill and adopt emerging digital tools in their teaching. However, the support systems surrounding

The rapid evolution of digital tools and heightened expectations for technology-enhanced learning are driving academics to continually upskill and adopt emerging digital tools in their teaching. However, the support systems surrounding these tools have often been fragmented, reactive, and insufficiently integrated into our institutional structures. Offering limited opportunities for staff to build the confidence and capability needed to use educational technologies effectively and independently. Moreover, the absence of systemic coordination contributes to staff anxiety and disengagement. For example, teaching staff reported feeling overwhelmed with troubleshooting the Moodle gradebook during peak assessment periods, uncertainty about who to contact and frustration with inconsistent, incorrect or delayed responses from vendor support. Those less confident with the technology often reverted to manual workarounds or avoided adopting new tools and features altogether. To address these challenges at our university, we developed the Cyclic EdTech Support Model: a unified, collaborative framework that shifts from traditional siloed EdTech support to a connected, scalable and feedback-driven ecosystem. Informed by constructivist learning theory, socio-technical systems thinking and continuous improvement principles, the model focuses on moving from dependency to empowerment. Giving staff the confidence to navigate the EdTech ecosystem independently while still feeling supported. It emphasizes community learning, distributed expertise, and the importance of feedback loops in complex systems to enable scalable innovation. It operates on six interconnected elements: Capacity-building at the Start: where staff and students are onboarded through training and workshops(e.g. Hands-on workshops on key edtech tools prior to the start of the term for staff, Orientation Week demo for students) Self-help Enablement: using digital resources and chatbot support to reduce barriers encourage just-in-time help-seeking(e.g. Scribe step-by-step guides on web resources which can be updated real-time, Chatbots directly accessible within Moodle) First-Level Internal Support: via a new in-house team replacing the previous vendor-based service, staffed by knowledgeable professionals who provide fast, contextual troubleshooting and triage (e.g. In-house EdTech level 1 team supporting via phone, chatbot escalation and webform) Second-Level Expert Intervention: through advanced troubleshooting, trend analysis, local faculty collaboration and resource development(e.g. Team of technical SMEs, Power BI reports on inbound enquires) Systemic Escalation: where vendor-facing teams manage issue resolution and patch deployment(e.g. Coordination with Moodle, Turnitin, Echo360 vendors to resolve bugs) Ongoing Improvement & Automation: to streamline processes and maintain up-to-date knowledge base and chatbot responsiveness(e.g. Transition from email enquiries to webforms and then to PowerApp, monthly update of Chatbot knowledge base, automated notification on system/ reported issue updates) To ensure long-term sustainability and support for new tools, the model is also incorporated into a standardised university EdTech change management framework via a project-to-operations checklist, allowing newly introduced EdTech platforms and features to be transitioned into ongoing support with aligned training, documentation, and escalation pathways. Since implementation, the model has significantly improved coordination, service delivery, and confidence among staff. It places user experience at the centre, drawing on automation, data trends and stakeholder networks to deliver more than just ‘support’ - it enables digital confidence and capacity across the university. User satisfaction has consistently exceeded 95%, based on post-support survey from over 7600 enquires in the last 24 months. Satisfaction was measured using standardised feedback form asking users to rate their experience on a 5-point scale. Feedback from users frequently described the service as approachable, prompt, knowledgeable, clear and solution oriented. This case exemplifies how Technology Enhanced Learning practices can be augmented through operational innovation by embedding collaboration, shared responsibility and upskilling into a sustainable support structure. Its platform-agnostic and modular design makes it readily transferable across tertiary contexts, particularly for institutions aiming to streamline support and foster digital independence among staff.

Higher education has recently experienced significant disruptions from the COVID pandemic to the rise of generative AI. In addition, a focus on inclusion and accessibility have required thoughtful and intentional responses to the design of

Higher education has recently experienced significant disruptions from the COVID pandemic to the rise of generative AI. In addition, a focus on inclusion and accessibility have required thoughtful and intentional responses to the design of quality learning. Technology plays a significant role in designing these responses and contributing to innovative learning experiences that prepare students for the real world (Pelletier et al., 2022). While these disruptions and changes are challenging, they provide opportunities to spotlight the valuable role of education and learning designers in supporting transitions to online learning, redesigning assessment and creating engaging online learning activities and environments (Bellaby et al., 2020). These (predominantly) professional staff are critical to the design and development of technology enhanced learning experiences (D’Souza, Luu & Cui, 2022, Altena et al., 2019, Halupa, 2019). However, despite their valuable contribution to this work, the contribution of education and learning designers remains largely hidden, undocumented and unacknowledged in the sector. Bisset (2018, p. 18) noted that “Educational designers themselves need support and professional development to identify and articulate the way in which their professional interactions at the personal, relational, and institutional level bring different dimensions to the role” and D’Souza et al. (2022) similarly highlighted the need for future research to identify the influence of educational designers. To address these identified needs, the Learning Design Evidence Framework has been developed to assist learning designers to support their value proposition in collaborations with academic teams, guide them to be more intentional in those collaborations, and provide a means to evidence to institutions the impact of good design in promoting quality teaching and learning. It is a means by which learning designers can ‘show’ what they ‘know and do’. (Boreland, Henry & Sharpe, 2025). This makes it an invaluable resource for leaders and managers of project teams or learning design units who can use the Framework to showcase the value, impact, and contributions of these teams or units in meeting the challenges currently faced in higher education and/or in advancing institution-wide goals. This session provides a brief overview of the Framework and a case study of how it is being implemented at one university. The session will challenge other team leaders and managers to think about how they can evidence and promote the value learning designers bring to the creation of quality learning for successful student outcomes in an era of continuous change.

The rapid integration of generative artificial intelligence (GenAI) into higher education has sparked debates about the future role of teachers (Chan & Tsi, 2024), including in providing feedback information to students. While GenAI offers

The rapid integration of generative artificial intelligence (GenAI) into higher education has sparked debates about the future role of teachers (Chan & Tsi, 2024), including in providing feedback information to students. While GenAI offers unprecedented accessibility and immediacy, this presentation argues that teachers' expertise remains irreplaceable in productive feedback – i.e., processes in which students make sense of information about their performance and use it to improve the quality of their work or learning strategies (Henderson et al., 2019, p. 1402). Drawing on a large-scale, cross-institutional survey involving 6,960 Australian university students (Henderson et al., 2025), this Pecha Kucha highlights students' perceptions of GenAI versus teacher feedback. The quantitative analysis revealed that nearly half of them (49.7%) reported using GenAI for feedback. However, they rated teacher feedback as more helpful and significantly more trustworthy. While 83.9% found GenAI feedback helpful, only 60.1% considered it trustworthy, compared to 90.5% who trusted teacher feedback. This trust gap may reflect the inconsistent quality identified in GenAI's feedback comments (Venter et al., 2024). The thematic analysis of 5,736 open-ended responses from students who used GenAI for feedback yielded 8,498 coded instances, revealing four interrelated characteristics in which teacher feedback was perceived as outperforming GenAI. Contextualisation and Relevance: Teacher feedback was perceived as more sensitive to specific assignment contexts (95.2% of 669 instances rated GenAI as less contextualised than teacher feedback) and more relevant to learning objectives (84.6% of 123 instances rated GenAI as less relevant). This contextual awareness enables teachers to identify what matters within disciplinary and course-specific frameworks. Reliability and Accuracy: Students perceived teacher feedback as significantly more reliable and trustworthy (95.4% of 1143 instances), reflecting teachers' ability to provide more trustworthy and accurate guidance without the hallucinations and factual inaccuracies that can appear on GenAI outputs. Relational Significance: Teachers offered more personal, connected feedback experiences (93.8% of 471 instances), providing the interpersonal recognition essential for productive learning relationships. This relational dimension cannot be replicated by GenAI’s algorithmic responses. Expertise: Students recognised teachers as more authoritative sources (88.2% of 119 instances), valuing their disciplinary knowledge and pedagogical understanding of student development trajectories. Students' evaluation of feedback is fundamentally shaped by perceptions of source credibility (Bearman et al., 2024), which may explain why students perceive teacher feedback as more trustworthy than GenAI's. Research demonstrates this selective engagement: uptake of content-focused GenAI feedback was considerably lower than form-focused feedback(Ziqi et al., 2024), suggesting students recognise GenAI's limitations for substantive guidance requiring disciplinary expertise. This translates into learning outcomes, with students not only perceiving instructor feedback as more useful but also demonstrating significantly greater lab score improvements than those receiving GenAI feedback (Er et al., 2025). GenAI may create opportunities for educators to focus on what they do best: providing expert, contextualised, and relationally-grounded feedback within authentic learning relationships. This potentially positions teacher expertise as increasingly valuable, with educators prioritising higher-level pedagogical responsibilities, such as developmental guidance, facilitating critical thinking, and disciplinary enculturation, while GenAI supports lower-level feedback processes, like grammar correction and initial draft review. Students appear to already recognise this distinction, trusting teachers for more substantive, transformative feedback while appreciating GenAI's supplementary role for immediate, accessible guidance.

This Pecha Kucha will explore how a large metropolitan Australian university is strategically investing in the pedagogically expertise of learning designers (Lodge, 2023) to lead institutional wide assessment transformation and artificial

This Pecha Kucha will explore how a large metropolitan Australian university is strategically investing in the pedagogically expertise of learning designers (Lodge, 2023) to lead institutional wide assessment transformation and artificial intelligence (AI) capability development. As AI becomes increasingly embedded in higher education (Perkins, 2024), institutions face mounting pressure to ensure the integrity and relevance of student learning outcomes. In response, learning designers are being placed across faculties to lead both systemic change and targeted support for educators, navigating a complex digital and cultural shift. Their nuanced understanding of discipline-specific needs enables them to co-design solutions that balance assessment security, AI literacy, and pedagogical integrity (Lodge, 2023). Applying a hub-and-spoke model that connects nuanced disciplinary expertise with a centrally driven strategy, the team of learning designers are collaborating with academics to drive change at scale and lead educational innovation. These designers work closely with teaching staff to adapt assessment practices in ways that are contextually relevant and pedagogically sound. At the same time, they are bridging institutional silos by co-developing cross faculty resources, contributing to academic integrity frameworks, curating and disseminating exemplars of effective practice, and facilitating professional learning. Their work includes mapping assessment against program outcomes, redesigning tasks for authenticity and AI resilience, supporting the development of academic and student AI literacy, and enabling scalable approaches to feedback and moderation. This coordinated approach ensures that local innovation aligns with institutional priorities, enabling meaningful and sustainable assessment transformation. This presentation will showcase one faculty’s approach which includes a scalable and sustainable series of workshops aimed at engaging hundreds of academic staff, delivered through multiple school-specific sessions, fostering collegial dialogue around AI, assessment design, and quality assurance, providing educators with the tools and confidence to adapt to a rapidly evolving landscape. In practice, participants are invited to critically evaluate the broader assessment architecture of their courses – asking whether tasks align with course and program learning outcomes, whether the chosen methods best capture intended learning and how principles like UDL and authenticity are embedded. These sessions also explore opportunities to meaningfully integrate AI, not as a threat but as a catalyst for pedagogical innovation. Drawing on the framing of AI as a “wicked problem” (Corbin, et al., 2025), educators are encouraged to shift from seeking perfect solutions to making continuous professional judgements in conditions of permanent uncertainty. This approach builds resilience – not just to AI, but to the future challenges yet to emerge – by treating assessment transformation as a strategic, adaptive and context-sensitive process (Dawson, et al., 2024). This institutional initiative demonstrates how human expertise, through collaboration, trust, and pedagogical design—can effectively guide AI adoption at scale. It also illustrates the vital role learning designers play in balancing institutional priorities with discipline-specific aspirations. Session attendees will gain insights into the power of strategic collaboration between central and faculty teams, and how learning designers are enabling ethical, innovative, and future-ready learning environments.

Intelligent tutoring systems (ITS) utilise artificial intelligence to deliver personalised educational content, guidance, and feedback. Recent advances in Generative AI (GenAI) have shown considerable promise in the development of ITSs

Intelligent tutoring systems (ITS) utilise artificial intelligence to deliver personalised educational content, guidance, and feedback. Recent advances in Generative AI (GenAI) have shown considerable promise in the development of ITSs, offering the potential to provide highly tailored educational experiences. However, current GenAI-based systems frequently suffer from critical limitations such as content hallucination, generation of overly complex responses, and misalignment with defined course objectives, undermining pedagogical effectiveness and risking academic integrity. Existing GenAI-powered educational tools often rely on vast, unfiltered internet-sourced training data, lacking the ability to restrict outputs exclusively to course-specific materials. This typically results in feedback that is either overly generic, misaligned with curriculum sequencing, or pedagogically inappropriate. Traditional ITSs, relying on rigid, rule-based structures, similarly face difficulties in capturing the nuanced, context-rich language typical in higher education environments. Research suggests potential solutions using context-free grammar (CFG) and predictive parsing techniques. Nevertheless, these methods have traditionally been limited to experimental laboratory environments, and their efficacy in comprehensive educational contexts remains underexplored. This research addresses these gaps by proposing a novel intelligent tutoring platform that integrates CFG and Earley’s parsing algorithm with a GenAI model specifically trained on curated, course-aligned content. Unlike traditional systems, our approach uniquely considers the student’s specific position within the course learning trajectory and their current understanding level, ensuring output is both cognitively appropriate and pedagogically relevant. For instance, if a student demonstrates difficulties in Week 6 activities, the system intelligently identifies underlying conceptual gaps originating from earlier weeks (e.g., Week 2) and delivers targeted, remedial content precisely aligned with their immediate learning needs. The integration of CFG with Earley’s parsing within a generative AI framework ensures pedagogical consistency, computational efficiency, and ease of integration with existing university infrastructure. By restricting content generation strictly to validated course materials, the system significantly reduces the risks associated with hallucinations and ensures alignment with educational objectives. A pilot study across two STEM courses within UniSA Online will evaluate this system’s effectiveness in providing accurate, relevant, and cognitively aligned content. Key research questions include: How effectively do GenAI-generated assessments and feedback align with course learning outcomes compared to instructor-authored materials? Does the integration of CFG and Earley’s parsing significantly mitigate hallucinations and curricular drift? To what extent can the system reduce academic staff workload related to assessment creation and personalised student feedback? Anticipated outcomes include improved alignment between assessment content and learning outcomes, enhanced personalised learning experiences, reduced academic workload, and valuable data for continuous course improvement. Deliverables encompass a fully operational tutoring platform, reusable grammar libraries, implementation guides, training resources, and scholarly publications. This project contributes significantly to Technology Enhanced Learning (TEL) by advancing theoretical and practical understanding of effective, course-aligned GenAI application. This project pioneers a new class of intelligent tutoring systems, course-aligned, hallucination-resistant, and responsive to individual learner trajectories. Its scalability and adaptability across diverse tertiary contexts underline its value for broad educational innovation, aligning strongly with UniSA’s strategic goals in fostering pedagogical excellence, integrity, and technological leadership in online education.

Healthcare training using simulation has experienced significant technological advancement, with immersive reality (XR) enhancements demonstrating impressive visual sophistication and procedural authenticity. However, this progress

Healthcare training using simulation has experienced significant technological advancement, with immersive reality (XR) enhancements demonstrating impressive visual sophistication and procedural authenticity. However, this progress conceals a critical misalignment between technological priorities and educational outcomes. Current XR healthcare education operates under what we term the "fidelity fallacy" - the assumption that high visual realism automatically translates to effective clinical preparation (Hamstra et al., 2014). This presentation challenges this paradigm, arguing that the industry emphasis on environmental authenticity has systematically neglected the affective dimensions essential for clinical competence. Contemporary research reveals that XR healthcare implementations predominantly focus on anatomical accuracy and procedural fidelity, while very few incorporate emotional regulation elements (Li, 2024). This disparity is particularly problematic given evidence that emotional resilience significantly impacts clinical performance and patient outcomes. Research consistently demonstrates that healthcare professionals and other stakeholders experiencing elevated stress show substantially decreased diagnostic accuracy and reduced communication effectiveness during critical incidents (Akhtar et al., 2025a). Yet existing XR systems present static, pre-programmed scenarios that fail to respond to learners emotional states, creating an authenticity gap between training and practice. The disconnect becomes more pronounced when examining real-world clinical demands. Healthcare professionals face numerous unexpected variations during critical events, requiring constant emotional regulation and adaptive decision-making. Current XR implementations, despite their visual sophistication, cannot adapt to individual emotional responses, limiting their effectiveness in preparing learners for these complex realities. Whilst many simulation centres collect biometric data, very few utilise it for real-time adaptation, representing a significant underutilisation of available technology (Akhtar et al., 2025b). This presentation advocates for a paradigm shift towards emotionally responsive XR systems that establish bidirectional relationships between learner and environment. Evidence from adjacent fields demonstrates the feasibility of such approaches - military training, aviation, and competitive sports have successfully integrated physiological monitoring with environmental adaptation (Yockey, 2023; Bernabei & Costantino, 2024). Healthcare education lag in adoption reflects not technological limitations but conceptual constraints rooted in the fidelity fallacy. The argument extends beyond individual learning outcomes to systemic healthcare implications. Studies show simulations with real-time biofeedback yield substantial improvements in stress management, decision accuracy, and learning transfer compared to traditional approaches (Farsi et al., 2021). These improvements translate directly to patient safety and care quality. Furthermore, cultural considerations add complexity often ignored in current implementations - research identifies significant variations in stress manifestation and decision-making patterns amongst healthcare students from diverse backgrounds, yet few XR simulations incorporate culturally specific elements (Zhang et al., 2024). The presentation introduces the Emotionally Responsive XR Clinical Environment (ERXCE) framework as a solution addressing these documented gaps. ERXCE establishes continuous feedback loops between physiological monitoring and adaptive scenario complexity, creating personalised learning experiences that prepare healthcare professionals for both technical and emotional challenges of clinical practice. By integrating affective computing with clinical simulation through multi-modal XR technologies, ERXCE addresses the critical gap between technical skill development and emotional resilience training. This work argues for a shift in clinical simulation for healthcare training from static representation to responsive adaptation that recognises the complex interplay between technical competence and emotional regulation in healthcare practice.

Generative artificial intelligence (AI) is reshaping assessment strategies in higher education. In units with online content especially, educators face increasing pressure to assess foundational knowledge with both authenticity and

Generative artificial intelligence (AI) is reshaping assessment strategies in higher education. In units with online content especially, educators face increasing pressure to assess foundational knowledge with both authenticity and integrity. Multiple-choice questions (MCQs), long valued for their scalability and efficiency, are now perceived as inauthentic and vulnerable to AI-enabled academic misconduct. A common response has been the abandonment of online MCQs. However, this risks leaving foundational knowledge unassessed, creating knowledge gaps and weakening the cognitive scaffolding essential for higher-order thinking and complex skills (Sweller, 2011). We present a strategy to reframe MCQs as both authentic and AI-aware instruments that support sustainable educator workload and motivate deeper learner engagement. Built on Action Mapping (Moore, 2017)—well-known in corporate instructional design, but under-utilised in higher education—we first shifted questions from rote recall to decisions anchored in real-world scenarios where foundational knowledge informs action. This results in authentic questions that help learners navigate real-world scenarios, outperforming typical people who do not possess knowledge or skills gained in a unit. Next, we added a novel layer to the framework to make the questions AI-resistant. This layer relies on inherent shortcomings of AI trained on large language databases, as well as entrenched reasoning biases common across LLM AIs. The result is a suite of questions that top-performing AIs consistently and confidently answer incorrectly. This design process led to what we call A+ MCQs—making questions that are: Applied: Rooted in discipline-specific, real-world decisions requiring knowledge-based judgement. Authentic: Reflective of lived or professional realities to increase relevance and engagement. AI-aware: Iteratively refined until AI responses consistently falter, ensuring human cognition drives success. A+MCQs were piloted in PSY2014: Mental Health in the Digital Age, a second-year undergraduate psychology unit. The result was a robust bank of A+ MCQs serving multiple purposes: reinforcing essential knowledge for complex tasks later in the learner’s journey, connecting knowledge with practical choices, and allowing for efficient automated marking without compromising assessment integrity or quality. These questions also clarify the current relationship between professionals and AI by illustrating to learners concrete instances where learners who retain and apply knowledge will outperform AI. The session will showcase how traditional MCQs were transformed into A+ questions, provide side-by-side comparisons, and share practical co-developing strategies using the TPACK lens. Attendees will leave with a design guide and tips to create authentic, AI-resilient assessments that maintain both pedagogical rigor and operational efficiency in a world increasingly shaped by AI.

How can higher educational educators break free from the isolation of online teaching and build meaningful professional connections? This presentation explores how an Australian University has adapted ‘Teaching Squares’ as initiative to

How can higher educational educators break free from the isolation of online teaching and build meaningful professional connections? This presentation explores how an Australian University has adapted ‘Teaching Squares’ as initiative to suit a digital environment, offering a flexible, scalable model for collaborative professional development among online educators. At its core, the initiative transforms solitary online teaching into a shared journey of observation, reflection, and growth. The purpose of this initiative is to address a persistent challenge in online education including lack of structured opportunities for peer interaction and reflective dialogue. Many online educators work in silos, rarely witnessing how others design or deliver their courses. The use of teaching squares program reimagines professional learning by bringing educators together through structured, non-evaluative peer observation which is designed not for critique, but for inspiration and self-reflection. Originally implemented in face-to-face university settings, Teaching Squares brings together three to four educators to observe each other’s teaching over a fixed period. In a digital space, instead of in-person classroom visits, participants share a curated selection of course artefacts including recorded lectures, forum threads, LMS navigation, announcements, and assessment materials. These are reviewed asynchronously, enabling participants to engage with rich teaching content at their own pace. This is then followed by a structured reflection and a virtual group debrief. This approach is underpinned by principles from the Scholarship of Teaching and Learning (SoTL), social constructivism, and collaborative learning theory. It recognises that peer-led reflection can deepen teaching practice and build collegial bonds, particularly when done in a psychologically safe, non-judgemental space. Rather than being evaluated, each educator reflects on their own practice after observing others, focusing on elements they found inspiring or thought-provoking. Participants report wide-ranging benefits including greater self-awareness, new pedagogical ideas, and a stronger sense of professional belonging. From improving student engagement strategies in discussion forums to rethinking assessment clarity, many have implemented changes directly influenced by what they observed. For some, the experience sparked longer-term collaborative partnerships and ongoing pedagogical conversations. What makes this initiative particularly relevant to today’s online education landscape is its accessibility and scalability. By removing geographical constraints and time pressures, the program invites broader participation including casual and early-career educators who are often left out of traditional professional development opportunities. The asynchronous format also allows for deeper, repeated exploration of teaching materials, leading to more thoughtful reflection. Preliminary results from our ongoing evaluation show strong participant satisfaction and increased teaching confidence. These early findings suggest that Teaching Squares doesn’t just support individual growth, it fosters a culture of shared learning across the institution. This presentation will walk through the process of adapting and implementing Teaching Squares in an online education setup. It will showcase real artefacts, share participant views and reviews, and offer practical guidance for replicating the model in other online or blended environments. Ultimately, it invites educators to rethink professional development not as a solitary pursuit but as a shared, reflective, and transformative practice.

Since OpenAI’s release of ChatGPT (November 2022), generative AI models have proliferated and evolved rapidly. Beyond chat-based interactions and text generation, newer multi-modal and reasoning models incorporate image, video and audio

Since OpenAI’s release of ChatGPT (November 2022), generative AI models have proliferated and evolved rapidly. Beyond chat-based interactions and text generation, newer multi-modal and reasoning models incorporate image, video and audio generation and interpretation, as well as citation tools. These tools are increasingly embedded into mainstream productivity systems (e.g., Copilot in the Microsoft suite), lowering barriers to everyday use. The widespread availability of AI tools has had a profound impact on education. In Australia, the AI disruption has prompted the higher education sector to rethink existing assessment practices to mitigate misuse while adopting approaches that support the ethical, critical, and responsible use of AI (Lodge et al., 2023). As Huijser et al. (2024) explain, the challenge for academics and professionals supporting teaching and learning in higher education is not just to build technical proficiency with these tools, but also to build staff capabilities to critically engage with AI’s complexities and make informed decisions on its appropriate use in teaching contexts (Markauskaite et al., 2022). The project aims to design and iteratively refine a layered professional development (PD) suite to support staff AI literacy, defined as the capabilities enabling individuals to critically evaluate, communicate, and collaborate with AI (Long & Magerko, 2020). In this design case, I ask: How can responsive PD scaffold staff adaptability, critical judgment, and ethical engagement with AI? This approach responds to critiques that Technology Enhanced Learning (TEL) PD initiatives primarily focus on knowledge and skill acquisition and to calls for PD that goes beyond tool proficiency by intentionally designing for “learning about AI…, learning with AI…, and learning for human-AI collaboration” (Carvalho et al., 2022, p.2). The PD suite iterates an earlier pilot approach to support staff AI literacy at the same institution (Tibbs et al., 2024). This presentation focuses primarily on the workshops, which were delivered in six cycles (2024-2025). The 2024 workshops provided opportunities for first encounters with AI, tool comparisons, ethical discussions, and assessment design considerations. By 2025, informed by facilitator observations and reflections, transcripts, participant artefacts, evaluation survey responses, evolving AI technologies, and institutional infrastructure, the workshops were iteratively redesigned across cycles, alongside an updated self-paced module. The 2025 workshops were underpinned by socio-constructivist principles: more space was created for dialogue, critical evaluation of AI outputs was emphasised, and collaborative peer design challenges and the crafting of contextually relevant agents for practical use were included. They also incorporated a critical pedagogical orientation and elements of transformative learning, where staff interrogated assumptions about AI through engagement with ethical and Aboriginal and Torres Strait Islander perspectives, and explored their professional obligations to support students’ AI literacy development. The next planned layer in the suite, an AI in Learning and Teaching micro-credential, is currently in development. The evidence-driven, situative approach is grounded in educational design research (McKenney & Reeves, 2018) and design-based professional learning (Friesen & Brown, 2022); engagement and evaluation data from each workshop cycle informed the next cycle’s design. The PD suite is positioned to support staff’s critical and adaptive expertise, not just technical proficiency, to capably respond to the opportunities and uncertainties brought by AI (Markauskaite et al., 2022). Its layered architecture, from low-stakes self-paced exploration to applied collaborative workshops, and soon to reflective micro-credential, supports different starting points and scaffolded progression, enabling adaptation for institutions with different resource constraints. For example, a train-the-trainer model could be adopted so that tailored, discipline-specific workshops drawing on structured dialogue and critical reflection can be facilitated by school-based champions. This case offers insights into how this PD model can create conditions for adaptive and critical AI literacy development for university educators, beyond one-off technical upskilling (Friesen & Brown, 2022). It underscores the value of design interventions attuned to shifting teaching and learning ecologies, building staff capabilities to both create with and critique AI. The presentation will illustrate these design cycles, share facilitator reflections and participant artefacts, and outline future directions.

In an era of accelerated technological and societal change, the employability of graduates is an urgent concern for tertiary education institutions (Clarke, 2018). Graduates are increasingly expected to demonstrate teamwork, emotional

In an era of accelerated technological and societal change, the employability of graduates is an urgent concern for tertiary education institutions (Clarke, 2018). Graduates are increasingly expected to demonstrate teamwork, emotional intelligence, and lifelong learning skills alongside disciplinary expertise (Haselberger et al., 2012; Moore & Morton, 2017). However, evidence shows a lack of transferable skills among new graduates (Hurrell, 2016), and many curricula still lack explicit integration of these capabilities. In response to calls for the embedding of transferable skills into undergraduate curricula, the first-year subject Applied Psychology (PSY1APP) was recently developed at La Trobe University to develop work-ready competencies in psychology students. PSY1APP incorporates a range of assessments (including an unconventional reflective e-portfolio) which facilitate personal and professional growth and align with the competency-based learning models recommended in psychology education (Jhangiani & Hardin, 2015; Naufel et al., 2019). The subject also enhances engagement and authenticity through a variety of innovative digital learning tools – such as video interviews with psychology alumni embedded into the Learning Management System and the e-portfolio assessment – which further demystify career pathways and model diverse applications of psychology skills and knowledge. A qualitative study was conducted to explore students' engagement with PSY1APP and obtain feedback as part of a co-design process (Cooper & Krishnan, 2020). It comprised four focus groups with a total of 14 participants (10 women and 4 men, aged between 18 and 52 years, Mage = 31.6, SDage = 12.1) who had recently completed PSY1APP at La Trobe University. Focus groups had an average duration of 64 minutes and were conducted 3-5 weeks after the end of semester. Reflexive thematic analysis (Braun & Clarke, 2023) resulted in three broad themes, each comprising between two and three subthemes. 1) Personal Development: students described transformative impacts on their self-knowledge, relationships, and perspective. The subject promoted metacognitive thinking and empowered students to apply psychological principles to their own lives, relationships, and wellbeing. 2) Expanding Horizons: the subject offered insight into the ‘real world’ of work in psychology, exposing students to diverse applications and helping them reimagine possible futures, moving beyond traditional pathways such as clinical psychology. 3) Tension Between Breadth and Depth: while some students appreciated the wide scope of topics, others expressed a desire for deeper engagement with specific content, highlighting the ongoing challenge of designing adaptable learning environments that are both inclusive and personalised. These insights have prompted improvements to the PSY1APP curriculum and have positioned PSY1APP as a key subject in the current employability-focused re-design of the undergraduate psychology course at La Trobe. The results of this study show that through authentic and digitally enhanced curriculum design, the building of employability skills need not be restricted to placements and final-year subjects. Instead, digital tools such as reflective e-portfolios and multimedia case studies can support students to become resilient, future-focused learners. PSY1APP offers actionable insights for educators across disciplines wishing to embed applied skill development and innovative digital assessment types into undergraduate curricula for deep learning, transformative change and student wellbeing.

A national and global gap in transferrable work-ready skills among new graduates has led to calls both internationally (Strohmetz et al., 2015) and within Australia (Hamilton et al., 2018) for the adoption of a competency-based approach to

A national and global gap in transferrable work-ready skills among new graduates has led to calls both internationally (Strohmetz et al., 2015) and within Australia (Hamilton et al., 2018) for the adoption of a competency-based approach to curriculum design, focusing on skill acquisition as well as discipline knowledge (Jhangiani & Hardin, 2015). Despite this, undergraduate programs still often lack structured opportunities for students to develop generalisable skills that are highly valued by employers, such as resilience, critical thinking and reflective practice. Responding to this gap, the subject Applied Psychology (PSY1APP) was recently developed at La Trobe University to build work-ready competencies in psychology students. PSY1APP promotes deep active learning and strong student engagement through peer-to-peer knowledge construction, experiential learning (Kolb, 1984), and innovative digital tools. These include a unique reflective e-portfolio assessment, and video interviews with psychology alumni which are embedded into the Learning Management System and the e-portfolio, enhancing the authenticity of taught material and bridging the gap between psychology theory and practice. The current study aimed to examine the effectiveness of PSY1APP in increasing students’ generalisable skills and knowledge using a mixed-methods longitudinal study. Participants were 60 students (83.3% women, 15% men, 1.7% gender non-binary, Mage = 24.6 years, SDage = 9.86) who undertook PSY1APP in 2023. Students completed pre- and post-semester surveys measuring variables such as mindfulness, stress management and wellbeing. Qualitative open-ended text feedback was also solicited at post-test regarding students’ experience of the subject. Paired-sample t-tests revealed that upon completion of the subject, students practiced more mindfulness and stress management behaviours than at the beginning of semester; these effects were small to moderate in size. Students also reported improved attitudes and knowledge regarding reflective practices, stress management, behaviour change and teamwork; these effects were moderate to large in size. Thematic content analysis on open-ended feedback (Ryan & Bernard, 2003) revealed three main themes: students have improved 1) knowledge, 2) personal growth and 3) understanding of the connection of psychology to real life. Transformative change was driven by the use of digital tools such as the e-portfolio, enabling students to develop competencies such as reflective practice and project themselves into future professional roles. However, an increase in negative affect and a decrease in overall well-being were also observed, suggesting the need for additional support mechanisms. Our findings suggest that the deliberate integration of generalisable skills and innovative digital technologies into the undergraduate curriculum can meaningfully enhance students’ career-relevant capabilities, including mindfulness, stress management, reflective practice, behaviour change techniques, and teamwork. Given the limited opportunities for structured, career-focused skill development in undergraduate programs—particularly outside of placements and final-year subjects—PSY1APP represents a future-focused model. It offers a compelling example for educators in diverse disciplines seeking to embed professional readiness early in the student learning journey.

This Pecha Kucha presentation offers a reflective autoethnographic narrative of one third space educational developer’s transition from operational course-level support to co-leadership in the Scholarship of Teaching and Learning (SoTL)

This Pecha Kucha presentation offers a reflective autoethnographic narrative of one third space educational developer’s transition from operational course-level support to co-leadership in the Scholarship of Teaching and Learning (SoTL), curriculum transformation, and digital innovation. Working within a faculty-based initiative that integrates embedded scholarship with academic partnership, this role illustrates how hybrid professionals contribute to institutional transformation through relational, scholarly practice. The presentation is grounded in Third Space Theory (Whitchurch, 2008), which conceptualises the space between academic and professional roles as a site of emergent identity and leadership. Turner’s (1969) concept of liminality further describes the transitional nature of this work, situated within and across organisational boundaries. The approach is also informed by Hutchings, Huber, and Ciccone’s (2011) integrative vision of SoTL, which emphasises embedded scholarly practice as a catalyst for institutional change. Drawing on Felten’s (2013) principles of good SoTL practice and Lukes et al.’s (2024) strategic tools for building SoTL cultures, the presentation showcases the scholarly agency of third space professionals in enabling evidence-informed teaching and learning improvement. The twenty-slide narrative unfolds in four interconnected arcs. First, it traces the role evolution from reactive support to proactive scholarly partnership in SoTL. Second, it reflects on hybrid professional identity, including the emotional labour, invisibility, and pursuit of legitimacy often associated with third space roles. Third, it illustrates practice-based contributions to student learning through program-level assessment design, capability framework development, and collaborative SoTL projects. Fourth, it considers institutional enablers and constraints that influence the sustainability and visibility of third space contributions. Although focused on a single professional trajectory, the presentation contributes to broader sector insights. It foregrounds the methodological and strategic capacities third space professionals bring to academic development and SoTL. It argues that advancing educational transformation requires institutions to embrace more inclusive models of academic-professional partnership and to recognise hybrid roles as core to future-focused learning environments. Aligned with ASCILITE 2025 themes of Your Journey, Collaborative Futures, and AI and Human Synergy, this Pecha Kucha offers a practitioner-scholar perspective on educational innovation. It invites reflection on how third space professionals can be positioned as co-designers of pedagogical change, and how institutions can foster cultures where collaborative expertise is both valued and sustained.

The rapid rise of Generative AI (GenAI) tools is reshaping conversations about assessment and feedback in higher education. While much institutional attention focuses on detection, compliance, and academic integrity (Cotton et al., 2024)

The rapid rise of Generative AI (GenAI) tools is reshaping conversations about assessment and feedback in higher education. While much institutional attention focuses on detection, compliance, and academic integrity (Cotton et al., 2024), this presentation shifts the lens to educators and how they are actually using GenAI in assessment practice. We present findings from a grant-funded initiative at UNSW that explores educator-led innovation through a Postcards of Practice approach. The Postcards of Practice are one-page, practice-based narratives where educators document their use of GenAI tools. These postcards highlight applications including formative feedback generation, student prompting literacy, assessment redesign, and co-creation with AI. They reveal how educators are experimenting with GenAI to support student learning while navigating ethical concerns, transparency, and pedagogical alignment. Our study uses a qualitative interpretive methodology, combining thematic analysis of the postcards with follow-up interviews. The analysis draws on theoretical frameworks including feedback literacy (Carless & Boud, 2018), dialogic assessment (Nicol, 2010), and new paradigm feedback design (Winstone & Carless, 2020). We also apply institutional and national GenAI guidelines (Liu & Bridgeman, 2023; Perkins, 2023) to surface shared values such as authenticity, inclusivity, and responsible innovation that guide educators’ decisions. The aim of this study is to explore how educators are experimenting with GenAI in assessment and feedback, and to capture their emerging practices and reflections through the Postcards of Practice initiative. The central research question guiding this work is: How are educators integrating GenAI into assessment and feedback, and what opportunities, challenges, and support needs arise from these practices? This work advances Technology Enhanced Learning (TEL) by providing empirical insights into how GenAI is actually integrated at the coalface of teaching. Educators describe how GenAI supports more frequent, personalised feedback and builds student agency in learning. At the same time, they raise concerns about over-reliance, AI hallucination, and the need for clear pedagogical scaffolding. These reflections point to the need for professional development that is discipline-sensitive, responsive, and grounded in practice. The postcard approach also functions as a professional learning intervention. It prompts reflection, encourages cross-disciplinary dialogue, and helps build a local community of practice around GenAI use. Through this model, we demonstrate an innovative and scalable method of capturing and supporting TEL innovation in real time. The findings suggest GenAI is prompting a rethinking of assessment: from summative, compliance-driven models to more transparent, formative, and student-centred designs. Educators begin to embed feedback literacy, ethical AI use, and critical prompting into their teaching, with clear implications for program-level assessment and graduate capability development. To strengthen clarity, we propose a concise diagram mapping the emerging practices captured in the postcards against the theoretical frameworks of feedback literacy, dialogic assessment, and new paradigm feedback design. This visual representation illustrates how practical insights align with, extend, or challenge these frameworks, making the study’s contribution accessible across diverse tertiary contexts. This proposal offers exemplary innovation in TEL by foregrounding bottom-up, practice-led experimentation with GenAI. It is grounded in strong theoretical frameworks and applicable across diverse tertiary contexts. The Pecha Kucha format will present key insights through rich visual storytelling, including excerpts from the postcards themselves. We conclude by proposing future directions for research and institutional strategy, including how to embed GenAI into assessment ecosystems in ways that enhance learning, uphold integrity, and empower educators to lead digital transformation from within.

Generative Artificial Intelligence (Gen-AI) presents a profound challenge for designing and implementing authentic tertiary assessment. The rapid adoption of platforms such as OpenAI’s ChatGPT has intensified concerns about assessment

Generative Artificial Intelligence (Gen-AI) presents a profound challenge for designing and implementing authentic tertiary assessment. The rapid adoption of platforms such as OpenAI’s ChatGPT has intensified concerns about assessment validity and integrity (Namoun et al., 2024). These concerns are particularly salient in health science (HS) programs, where excessive reliance on Gen-AI may undermine the development of clinical reasoning and decision-making competencies, affecting professional readiness and patient safety. This presentation reports on a project employing a three-cycle action research methodology to enhance responsiveness to Gen-AI–related assessment challenges. Cycle 1 involved developing an innovative Assessment Appraisal Tool aligned with national and institutional integrity guidelines (Flinders University, 2023; Lodge et al., 2023a, 2023b; Monash University, 2023; TEQSA, 2022; Torrens University, n.d.). The tool assigns an AI risk score (out of 30) indicating the likelihood that an assessment could be generated by Gen-AI and was piloted across three foundational HS subjects. Cycle 2 refined the tool based on feedback and extended its application to additional HS subjects, identifying targeted strategies for redesign. Cycle 3, currently underway, implements and evaluates these redesigns to improve authenticity, learning, and academic integrity. We will also discuss the emerging theoretical links between this project and programmatic assessment design. We will conclude by considering the strategic and practical meeting points where this project may align with future institution-wide programmatic assessment design strategies, addressing the ongoing challenges of Gen-AI while ensuring assessment of learning.

A digital twin avatar (synthetic self, personalised virtual avatar, AI clone) is created and controlled by the person it represents, aiming to be an ethical use of deepfake technology (Altuncu et al., 2024). In higher education (HE), these

A digital twin avatar (synthetic self, personalised virtual avatar, AI clone) is created and controlled by the person it represents, aiming to be an ethical use of deepfake technology (Altuncu et al., 2024). In higher education (HE), these avatars can be used to deliver asynchronous video lectures, raising issues around ownership and representation. There are currently no HE policies in Australia that govern the use and control of digital twin lecturers who look and sound like real academics. While digital twins offer benefits such as low-cost and multilingual educational content, deepfakes pose risks including cyberbullying, reputational harm, and academic dishonesty (Roe et al., 2024). The panel will rely on audience input (bring your device) to discuss the pros and cons around the emotionally charged topic of replacing real lecturers with their AI generated digital twins. Draft guidelines for using digital twin lecturers in HE will be presented.

Higher education faces unprecedented assessment challenges from emerging technologies and academic misconduct. Interactive oral assessments (IOAs) provide a viable solution as real-time, dialogic assessments where students demonstrate

Higher education faces unprecedented assessment challenges from emerging technologies and academic misconduct. Interactive oral assessments (IOAs) provide a viable solution as real-time, dialogic assessments where students demonstrate understanding, critical thinking, and communication skills through two-way spoken interaction. This assessment type strengthens academic integrity while improving student engagement and learning outcomes. This panel showcases IOA implementation across diverse contexts—biological and health sciences, clinical training, business education, and creative arts—spanning all undergraduate years with varied formats. Our collective experience covers cohorts from 20 to 600+ students, delivered in-person and online. The panel addresses practical implementation challenges: scheduling, staffing, technological requirements, consistency, accessibility, student preparedness, and anxiety management. Attendees will participate in hands-on IOA activities, share experiences, and gain concrete implementation strategies while building connections with fellow educators exploring assessment innovation.

Every one of us has encountered times of change and disruption in our work, our institutions, and our world that challenge and reshape how we teach, learn, and lead. This panel explores how university learning and teaching professional

Every one of us has encountered times of change and disruption in our work, our institutions, and our world that challenge and reshape how we teach, learn, and lead. This panel explores how university learning and teaching professional development is sustained and reimagined in such times. Drawing upon the panellists’ experiences we ask: How do we adapt, and what enables us to thrive? Through collaborative autoethnographic reflection, we examine disruptions at the micro (individual), meso (institutional), and macro (sector and global) levels. These reflections have served not only as a method of inquiry but also as a means of resilience and renewal. Our discussion highlights the tensions and possibilities that emerge when professional development intersects with uncertainty, and how reflective collaboration can foster adaptability, community, and innovation. This session invites audience participation to collectively explore how we might shape more sustainable and inclusive futures for professional development in higher education.

The symposium will explore ways of better understanding, challenging and expanding the ways that its diverse users think about and use generative AI in higher education, to best respond to our emerging opportunities to achieve AI ethical

The symposium will explore ways of better understanding, challenging and expanding the ways that its diverse users think about and use generative AI in higher education, to best respond to our emerging opportunities to achieve AI ethical and pedagogical best practice. The symposium features a discussion between a range of AI in education experts, and session attendees, guided by key questions on how to achieve the best possible use of AI in education. These questions include how to best bring together technological and human interfaces, and how to best use generative AI in education practice. This could include by strategically expanding its current uses to help it improve whole student education, as well as academic education. Student engagement, wellbeing and motivation could be strategically improved via identifying current levels of, and potential improvements in, student and staff knowledge of and attitudes towards educational uses of AI.

This panel challenges the persistent framing of third space professionals as research support rather than research leaders. Grounded in Whitchurch’s third space theory, Wenger’s communities of practice, and Boyer’s model of scholarship, we

This panel challenges the persistent framing of third space professionals as research support rather than research leaders. Grounded in Whitchurch’s third space theory, Wenger’s communities of practice, and Boyer’s model of scholarship, we examine how structured mentoring through the 2025 ASCILITE Community Mentoring Program (CMP), the Research Mentorship Program for Third Space in partnership with the Learning Design SIG, enables learning designers and academic developers to engage in sustained scholarly inquiry. Panel contributors will share narratives of identity transformation, research emergence, and boundary-crossing practices that illuminate both enablers and constraints shaping third space scholarship. We propose that third space professionals are uniquely positioned to lead educational transformation through practice-based inquiry. Through facilitated dialogue, attendees will surface institutional conditions and co-develop strategies to sustain scholarly development. By reconceptualising mentoring as a community of practice, this panel demonstrates how CMP fosters the shift from peripheral participation to active scholarly leadership.

Learning design as a profession remains in a liminal space, increasingly central to digital education yet without the formal recognition or collective voice enjoyed by other professional domains. This panel addresses the current lack of

Learning design as a profession remains in a liminal space, increasingly central to digital education yet without the formal recognition or collective voice enjoyed by other professional domains. This panel addresses the current lack of shared professional standards by asking: What values, practices and indicators of quality might form the basis of a professional standards framework for learning designers? Drawing on established models from education and technology professions, and sociological theories of professionalisation, the panel invites ASCILITE participants to collaboratively explore what such a framework might look like, how it should be developed, and why it matters. Through guided provocations and participatory workshop activities, attendees will help shape a draft map of core values, domains of practice and levels of expertise, forming the foundation for further community-led work.

This panel explores the lived experience of cross-institutional collaboration in a major multi-university research initiative investigating students’ perspectives on generative AI in higher education. Bringing together researchers from

This panel explores the lived experience of cross-institutional collaboration in a major multi-university research initiative investigating students’ perspectives on generative AI in higher education. Bringing together researchers from four leading Australian universities, the project exemplifies how sector-wide partnerships can overcome institutional silos, foster methodological innovation, and generate richer, more inclusive insights. Panellists will reflect on the benefits, challenges, and transformative potential of working collaboratively at scale, offering practical strategies and provocations for others seeking to harness collective wisdom in response to sector-wide challenges.

Higher education faces declining student engagement, resulting in poor motivation and course completion rates. Students struggle with workload management, social disconnection, and limited meaningful interactions with instructors and peers

Higher education faces declining student engagement, resulting in poor motivation and course completion rates. Students struggle with workload management, social disconnection, and limited meaningful interactions with instructors and peers (Naylor et al, 2017). These challenges are intensified in digital learning environments where isolation is common. Artificial Intelligence (AI)-driven nudging systems offer potential solutions through timely, personalised feedback to improve motivation, increase behavioural engagement, and reduce dropout rates by restoring connection and teacher presence. This panel examines tensions surrounding persuasive AI through the EngageAI project, which uses persuasive AI technology to deliver personalised behavioural nudges to enhance student’s learning experience. Four panellists will discuss: Does AI nudging's technical promise translate into meaningful outcomes? Are we empowering learners or creating algorithmic dependency? Can persuasive AI survive institutional constraints like budget limitations, privacy policies, and educational conservatism? The panel explores whether AI nudging represents adaptive learning's future or technological control over student behaviour.

The ongoing expansion of Generative Artificial Intelligence (GenAI) technologies since the launch of OpenAI’s ChatGPT in late 2022 has created an unprecedented level of uncertainty about learning and teaching practice in the tertiary

The ongoing expansion of Generative Artificial Intelligence (GenAI) technologies since the launch of OpenAI’s ChatGPT in late 2022 has created an unprecedented level of uncertainty about learning and teaching practice in the tertiary education sector. The rapid pace of change and the steady release of new tools and functionalities have made staying informed a challenge for time-poor educators, students, institutional leaders and third space practitioners. This light-hearted panel discussion aims to alleviate some of this stress by showcasing the strengths and weaknesses of some of the leading GenAI platforms by comparing their performance when tasked with a selection of learning and teaching-related use cases. Our goal for the session is to provide attendees with an opportunity to discuss the important characteristics of useful GenAI applications as we test and develop an assessment rubric for the output from the bots and evaluate the tools together.

The sudden emergence and unprecedented growth of GenAI tools in the higher education landscape presents educators with new and significant challenges. In the face of these, we argue that educators should move from prohibition to supporting

The sudden emergence and unprecedented growth of GenAI tools in the higher education landscape presents educators with new and significant challenges. In the face of these, we argue that educators should move from prohibition to supporting students to learn through collaboration with GenAI, but that their own values towards assessment and AI are central to this shift. This workshop will build on an assessment typology developed by the authors. The typology has been designed to assist educators to identify and communicate authorised GenAI use, and to build assessments that identify and prescribe appropriate student use of GenAI tools. Participants will leverage GenAI tools to reflect on their own biases and practices related to assessment design and GenAI. This reflective approach encourages educators to explicitly articulate aims for student learning as well as their own values for assessment design. The hands-on workshop will offer participants opportunities to deepen their teaching practice, while refining assessments relevant to their own teaching contexts. The design and delivery of the workshop will draw on the hosts’ experiences providing professional development workshops in their home institution that have introduced staff to GenAI tools, challenges and uses; teaching practice; assessment design; and student feedback literacy.

Following the COVID-19 pandemic, the emergence of generative AI has created significant upheaval for Australian tertiary education. This uncertainty has been exacerbated by policy uncertainty both globally and within the Australian

Following the COVID-19 pandemic, the emergence of generative AI has created significant upheaval for Australian tertiary education. This uncertainty has been exacerbated by policy uncertainty both globally and within the Australian context. In alignment with the conference theme, this workshop will explore what it means to educate in an era of continuous change. The workshop will adopt a format built on Klein's (1998) decision-making methodologies. There will be two phases: the first will focus on mapping future scenarios for Australian tertiary education, and the second will focus on what needs to occur now, particularly in terms of changes to practice. Participants will gain collective insight into future trajectories for tertiary education and develop practical approaches for adapting teaching and learning accordingly.

This workshop aims to: Introduce participants to a human-centred framework for evaluating educational technologies. Explore how this framework has been adapted to assess AI tools in teaching and learning. Critically evaluate the parameters

This workshop aims to: Introduce participants to a human-centred framework for evaluating educational technologies. Explore how this framework has been adapted to assess AI tools in teaching and learning. Critically evaluate the parameters of the AI evaluation framework- what’s missing, where do we need to go next- and contribute to collaborative input for cross-institutional development. Facilitate collaborative evaluation of AI tools across key dimensions: pedagogical value, ethical considerations, and impact on human expertise.

What if leadership in higher education wasn’t about position or power—but about purpose, connection, and collective impact? This workshop invites you to think differently about leadership. It offers space to reflect, write, and reimagine

What if leadership in higher education wasn’t about position or power—but about purpose, connection, and collective impact? This workshop invites you to think differently about leadership. It offers space to reflect, write, and reimagine your leadership practice in a way that is relational, values-led, and grounded in community. Together, we will challenge dominant ideas—such as the lone hero, top-down command, or leadership as control—and instead explore approaches that centre listening, inclusion, and alignment across roles, disciplines, and initiatives. Designed for educators, researchers, professional staff, and academic leaders at all levels, the workshop creates a collegial and constructive space for deep thinking and real conversation. Participants will engage with structured frameworks to identify their leadership contexts, surface the challenges and opportunities they face, and explore what it means to bring people along to do hard things—together. Through guided writing, narrative development, and critically constructive peer coaching, this is a space for people who want to lead with clarity, kindness, and commitment to shared purpose.

Feedback is a cornerstone of effective learning, yet it remains one of the most persistently complex challenges in higher education, for educators and students alike. This workshop introduces current thinking about student-centred feedback

Feedback is a cornerstone of effective learning, yet it remains one of the most persistently complex challenges in higher education, for educators and students alike. This workshop introduces current thinking about student-centred feedback practices, and then explores the implications for how we can design valuable (and sustainable) feedback encounters across the course and through technologies. The workshop has four broad sections: Understanding feedback: This section briefly explains current thinking about feedback as a student-centred process. It introduces concepts of evaluative judgment, and feedback literacy. Building off these concepts we begin to identify a series of heuristics for our feedback designs. Designing for a feedback-rich course: Using research-informed design heuristics, educators and learning designers will work collaboratively to audit and reshape their own courses to support a feedback-rich experience, one that builds student agency, feeds forward, and fosters continuous engagement. Along the way we will tackle questions such as how we can build early and frequent feedback encounters, and explore examples of impactful exemplar strategies, AI formative feedback, and peer feedback. Sustainable feedback delivery: This section of the workshop narrows to the practice of teacher-delivery of feedback. The provision of feedback by teachers is a time consuming, effortful and emotional task. This workshop draws on a decade of research into audio, video, and screencast-based feedback and will offer explicit guidance on how to create these rich feedback artefacts, and how to do it efficiently. Through hands-on activities, participants will create their own multimedia feedback artefacts, testing sustainable workflows and content principles. Debating the role of AI in feedback: The workshop will close with a discussion of the emerging possibilities of AI feedback agents. While these rapidly evolving tools raise exciting possibilities for scalability and responsiveness, they also invite critical reflection. Participants will be introduced to some examples of AI-generated feedback practices and debate its strengths and limitations to those of human-mediated responses. By the end of this workshop, participants will have: Applied feedback theory to design a feedback-rich course tailored to their own teaching context; Produced audio, video, or screencast feedback artefacts testing sustainable workflows and research-based principles; Debated the potential and limitations of AI-generated feedback. This workshop is designed for educators, learning designers, and researchers seeking practical, research-informed, and critically reflective approaches to enhancing feedback practices through digital tools.