2024: ASCILITE 2024 Conference Companion Materials

ASCILITE Conference - Pecha Kuchas

• What makes this online course tick? Community of Inquiry and 23 Things International

  Kwong Nui Sim, Sarah Stein, Michael Rose

  The Community of Inquiry (CoI) (Garrison, Anderson & Archer, 1999; 2010) is well-established, widely accepted, and practical framework. It highlights social, cognitive and teaching presences in effective online learning communities. 23 Things International (23T) is an online, flexible course for research students and early career researchers. The course is self-directed and promotes the building of academic and research networks, familiarity with resources underpinning research, and establishing professional profiles. It was first implemented in 2020 and has been refined annually to better meet needs of participants. One of the features of the programme is the ‘pod group’ arrangement. Participants are connected to each other in groups (the pods) based on research interests. The size of the pods is kept to about ten, so to facilitate manageable and meaningful communication and discussion of topics within the programme. Each year, 23T participants have reported pleasing satisfaction levels. Using the CoI, this investigation examined possible reasons why. The study aimed to: (a) identify practices and structural mechanisms that seem to underpin the experienced success of 23T; and (b) articulate plans for more targeted evaluation-review-development. Data sources included: annual reports (2020-2023) on the course containing integrated analyses of participant evaluation data; the outline and structure of 23T, showing the fabric of the course, how it is organised and arranged and how it implemented; facilitators’ knowledge and experiences of conducting 23T. Data were organised using a simple matching process (Garrison et al, 1999). CoI elements were matched with practice examples from implementation, and evidence from the data. Positives, negatives, possibilities and conclusions were drawn about gaps and potential. Examples of evidence drawn the from the data sources about the 23T programme include: Teaching Presence: including the use of prompts built into the material presented online and the facilitators’ spoken and written interactions with participants through live activities and through blogs (boosting authentic participant application of their learning); Social Presence: pod groups and how they were arranged and supported; Cognitive Presence: range of topics covered and the participant activity surrounding the topics. To build on theoretical work investigating 23T (Stein, Sim & Rose, 2023), this study is helping us to pinpoint concrete elements that seem to be influencing online course effectiveness and enabling identification of ways to strengthen 23T’s future flexibility and attractiveness. This is pertinent because of the uniqueness of 23T, namely, that it is online, flexible and self-guided and has no formal assessment expectations and does not provide formal credit. Gauging what counts as effectiveness and success is quite different therefore from award courses normally offered by higher education institutions. Similar application of the CoI using our matching approach may be helpful for others in different contexts and settings who are planning and/or implementing online courses.

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• TEL Pedagogies: Gamification – Grammar Guru: Strengths and Challenges

  Vineetha Nair B

  The Centre for English Communication (CEC) developed and launched Grammar Guru (GG), a browser-based game application, as part of Singapore Management University’s (SMU) TEL initiative in 2023. GG is used as part of CEC’s blended learning resources, which complements our core curriculum module for undergraduates, Writing & Reasoning (WR). GG is an upgraded iteration of Power Grammar 1.0, a basic grammar game developed by students several years ago. GG is an effective TEL tool for teaching grammar as it uses gamification to make learning engaging and caters to the needs of learners with different language proficiency levels. GG improves student engagement through gamification. Gamification is the application of game design, techniques and elements in non-game contexts and activities (Deterding et al., 2011, p. 1). Research shows gamification is highly effective in increasing student engagement, attention, motivation, creativity, digital literacy and performance level (Barua & Bharali, 2023; Fernandez-Antolin et al. 2021; Skritsovali, 2023). GG includes elements such as points, leaderboards, hints, and non-playable characters (NPC) to teach grammar in a professional, corporate context. By contextualizing grammatical and linguistic forms in sentences and paragraphs, GG helps students achieve greater competence and fluency in their English language abilities. The gamification elements make learning more interactive and enjoyable which improves students’ knowledge retention and application. A primary quantitative study conducted by CEC established that “the positive correlation observed suggests that the higher level a student played, the higher the student’s English language proficiency”. CEC is currently conducting a qualitative study to gather students’ feedback. GG also addresses the requirements of learners with diverse language proficiency levels by varying the difficulty of questions. These questions include sentence and text correction, matching, re-arrangement, true/false, fill-in-the-blanks and multiple-choice questions. Players work their way through eight levels that comprises Junior and Senior Intern, Junior and Senior Management Trainee, Junior and Senior Middle Management and Junior and Senior Director. Perez (2020) and Langendah (2016) highlight how certain game elements such as storytelling, challenges, progression, and feedback can boost student drive and learning. The gamification elements in GG have a similar effect, motivating learners of different proficiency levels. GG’s interface is designed to be simple and intuitive. Regardless of students’ socioeconomic background or gaming aptitude, they would be able to navigate it effectively. One challenge GG faces is striking a balance between entertainment and education. Limited game development funds result in limited game design features and less engaging gameplay for students, especially in comparison to commercial games with substantial budgets that offer high entertainment value through advanced graphics and intricate storylines. Furthermore, as CEC instructors are not game design experts, we have limited knowledge that restricts our capacity in designing and maintaining GG. Currently, CEC outsources game design and maintenance to a third parties. This results in instructors not being able to directly make changes to the game questions and content. Moreover, the process of retrieving relevant data for analysis is tedious and time consuming. Despite these constraints, thoughtful and strategic approaches can create valuable TEL resources that improve student learning.

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• Building Bridges : Effective Learning Designer-Subject Matter Expert Collaboration Strategies

  Joab Hwang, Amal Khabbaz

  One of the major challenges faced in learning design is fostering effective collaboration between Subject Matter Experts (SMEs) and learning designers (LDs) in the implementation of new pedagogies and learning technologies (Gottler, 2023). This area of Technology Enhanced Learning (TEL) practice is still emerging in nature, with an acknowledged need for more examples of effective approaches (Pollard & Kumar, 2022; Tay et al., 2023). The importance of this collaboration is amplified by the fact that both SMEs and LDs share a key stakeholder—the learner. To ensure the learner benefits fully, both parties must work together seamlessly, drawing on their complementary skills to deliver a learning experience that is both meaningful and impactful (Pollard & Kumar, 2022). This presentation serves as a case study, showcasing the processes used by the Institution’s LD team to build positive collaboration with SMEs to integrate new pedagogies and learning technologies in the development of asynchronous mathematics modules. In particular, this project involved the integration of two learning design principles, Universal Design for Learning (UDL) and the Cognitive Theory of Multimedia Learning (CTML) (CAST, 2024; Mayer, 2024), that were foreign to the SMEs, and learning technology that had not been used previously at the Institution in the form of lightboard video recordings. In the initial stages of this project, the Institution’s LD team encountered many of the issues previously reported in literature regarding working with SMEs, such as ambiguity of roles and tasks, power struggles between SMEs and LDs, and SME resistance to the use of new education technology and pedagogies (Chen & Carliner, 2020; Tay et al., 2023). To overcome these issues and to ensure the success of the project, a new approach was developed that prioritised clarity, communication and the common goal of building an excellent learner experience. The new approach drew on research into the factors that facilitated or hindered the relationship between SMEs and LDs, and included the following core principles: Mutual respect: LDs worked to build an environment where the expertise and time commitments of both SMEs and LDs were acknowledged and valued (Tay et al., 2023). Shared commitment: Processes were introduced to ensure that project goals were well defined and that a shared vision for the learning modules was established to foster a strong investment in the project's success (Chen & Carliner, 2020). In particular, we placed the learner experience at the centre of decisions regarding module design, by setting the student as the core “stakeholder” in design workshops. Common language: Steps were taken to establish a common language between SMEs and LDs by defining terms and processes to facilitate clear communication (Gottler, 2023). Empowering expertise: Both SMEs and LDs were empowered to contribute their unique skills to the project and given autonomy to make decisions during the design and implementation process (Chen & Carliner, 2020). For example, we acknowledged the expertise of our SMEs in classroom teaching and chose to record teaching videos without a formal script, yet based on an agreed scope and examples. This presentation will expand on how these principles were enacted practically to foster a strong partnership between SMEs and LDs characterised by effective communication, positive relationships and a strong sense of ownership of the project. The presentation will conclude by illustrating how this collaborative approach ultimately led to the successful completion of the project within constraints such as competing priorities and firm deadlines.

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• Exploring the relevance of Universal Design for Learning implementation in the post-secondary landscape from the perspective of sustainability

  Frederic Fovet

  This presentation showcases findings from a Canadian study which was carried out through 2023-24. This project explores an innovative facet of the momentum around sustainability within higher education, one that goes beyond the focus on environmental and operational preoccupations and concentrates on social and pedagogical sustainability. It examines the way the introduction of Universal Design for Learning (UDL) to a campus, through the creation of a cross-discipline community of practice, can (i) empower faculty to develop sustainable accessible practices within their own classroom, (ii) significantly reduce the reliance of the campus on accessibility services and reduce the pressure felt by these services, (iii) successfully integrate accessibility and inclusion within institutional strategic thinking around sustainability. The presentation synthesizes findings from a qualitative action-research project which examined perceptions and experiences of 14 stakeholders with different status and toles across the campus. The study adopted a phenomenological approach to data collection and analysis (Holland, 2014) and explored the participants’ own constructs in relation to the overlap between UDL and sustainability. Accessibility in the higher education has thus far been addressed through a medical model approach focused on retrofitting. In a nutshell, teaching and learning is designed for the ‘traditional learner’ and support services take on the task of supporting students who experience barriers in this design, with remedial, targeted services outside the classroom. The demographics of higher education, however, have changed widely over the last two decades, and retrofitting approaches are no longer sustainable. The volume of demand is growing exponentially, wait times increase, and the cost of Accessibility Services increases in a way that becomes unmanageable within most post-secondary campuses (NEADS, 2018). Universal Design for Learning (UDL) can address many of these strains on resources. Indeed, UDL is an emerging model for the management of diversity in the classroom which equips instructors to remove the majority of barriers to access to learning and support the needs of most diverse learners within the classroom itself (Al-Azawei et al., 2016). The literature highlights that most of the needs of diverse learners can be addressed with ease within the classroom itself once inclusive design and UDL are adopted and integrated as a mindset, across institutions (Baumann & Melle, 2019; Dalton et al., 2019). UDL can therefore address some of the concerns over the sustainability of current disability service provision models. The need for a sustainable lens in this area is therefore tangible and pressing. Accessibility services, student services personnel, and faculty are all painfully feeling first-hand the inability of the current structure to meet the needs of diverse learners and to address the volume of service requests. UDL has the potential to address this strain on support services and to re-empower faculty to create inclusive provisions within the classroom space. A practical example of this would be the considerable pressure placed on accessibility services to digitalize printed material or to seek alternate versions of PDFs that are shared in class but are not accessible with reading software. This is an example of costly, repetitive use of resources that can be solved sustainably by empowering instructors to use the UDL principles in their class design and not rely on print only or on non-accessible digital documents. This has immediate resource and funding implications. UDL integration represents a clear example of sustainable transformation: an initial focus on professional development with faculty leads to a reduction in spending and resources that are non-renewable (Fovet, 2017). The presentation showcases the wider implications for UDL development across the sector.

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• Artificial Intelligent Branching Simulations (AIBS) in Critical Care Neonatal Nursing

  Dan Laurence, Helen Patterson

  Roleplaying, simulations and branching scenarios are among the most authentic, critical and effective educational experiences, though have seen limited adoption due to the expense of creating, staffing, adapting and sustaining them over time (Davies, 2013). The new generation of large language models have made possible new affordances that enable delivering scenario based roleplaying experiences more sustainably. This Pecha Kucha charts the development process, frontier technology and the positive outcomes of an artificial, intelligent branching simulation (AIBS) a in critical care neonatal nursing simulation. Critical care disciplines and nursing have a tradition of using expensive in-person simulations and labor-intensive, high-stress scenarios to prepare students for the workplace (Jefferies, 2020). After such training, nurses undergo rigorous, high pressure in-person evaluations, such as the ANSAT (Ossenberg, Mitchell & Henderson, 2020), which they must pass in order to practice. Foundational reading about nursing practices and reviewing practice manuals is a step towards passing such evaluations, but these more theoretical learning practices don’t constructively align with the situational, authentic skills that are demanded in practice. With few learning experiences that can scaffold towards critical in-person evaluation, students often report high levels of anxiety and that they feel inadequately prepared for in-person evaluation, sometimes failing and leaving their studies and aspirations entirely (Cornine, 2020). Mindful also of an industry wide shortage of critical care nurses, there is a clear need to find bridging solutions that can affordably and effectively prepare trainee nurses for demanding in-person workplace evaluations. This Pecha Kucha charts the development of AIBS that was designed to bridge a learning gap between more theoretical training methods and high stress in-person training evaluations. The increasing popularity of conversational agents powered by large language models on web-based platforms like Character.ai (Sarkar, 2024), suggests that students might find a chatbot an approachable, engaging and an increasingly familiar experience. Initial tests directly prompting ChatGPT and Claude.ai both showed promise, but also raised some issues around reliability which mandated more direct and qualified oversight of teaching staff. A technical solution was required as an intermediary between the students and the LLMs that enabled ‘human-in-the-middle’ (Mollick, 2024) oversight. After an extensive review, the educator created tool ‘Cogniti’ was selected due to it’s ability to provide a seamless, pretrained scenario chat experience, while also enabling student account integration, data governance, supervisor oversight and privacy controls. The prompts used to instruct the Cogniti AI agent were developed using the RTRI prompting framework (Lui 2023, Hardman, 2023). By separating parts of the scenario into sequential chunks, each with a series of ‘expected responses’ it became possible to create and align an improvisational prompting script that resembled a sequence from a typical hospital procedures manual and that aligned to the prescribed ANSAT placement evaluation framework (Ossenberg, Mitchell & Henderson, 2020). Allocating specific roles to the AI agent and to the trainee nurse within a framework of expected responses enabled the narrative to resemble an authentic interaction, but within a safe environment. Prompting the AI agent to progress the narrative under specific conditions and to provide structured feedback to students, enabled a cohesive educational experience that was able to address specific gaps in student knowledge of neonatal practice and procedure. Staff and student feedback demonstrated positive results in terms of engagement, satisfaction, academic performance and student well-being.

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• Bridging Cultures, Advancing AI: Insights from an International Higher Education Community of Practice

  Nick McIntosh

  In an era where generative AI (AI) is reshaping education at breakneck speed, how can institutions keep pace while also ensuring authentic learning? Our international Community of Practice (CoP) offers a compelling answer. Spanning Australia and Vietnam, this unique collaboration has not only navigated cultural differences but leveraged them to create a rich tapestry of AI integration strategies in HE. From unexpected synergies to challenging assumptions, our journey offers crucial insights for educators worldwide grappling with AI's transformative power. Established in April 2023, our CoP has grown to approximately 500 members drawn from multiple campuses across Australia and Vietnam. This cross-cultural collaboration aligns with Wenger's (1999) Communities of Practice theory and demonstrates a novel approach to harnessing global collective intelligence in HE. Our CoP has critically examined the impact of AI on HE, exploring its transformative potential and challenges in teaching methodologies, learning experiences, and assessment practices. Our discussions have extended to the ethical and environmental considerations of increased AI adoption in education, aligning with the growing need for sustainable technological integration in academia. Key outcomes of the CoP include: Development of AI-integrated curriculum frameworks and co-creation of staff training materials, enhancing institutional readiness for AI integration; Design and implementation of innovative learning tools, such as AI-generated interactive personas, enhancing student engagement and outcomes; Facilitation of research collaborations, resulting in both publications and multiple conference presentations; Exploration of AI-enabled learning analytics for personalised learning, with initial implementation across different cultural contexts; and Amplification of public awareness about AI in Southeast Asian education, as evidenced by extensive media coverage in Vietnam. Our CoP's activities, including monthly expert-led meetings and weekly newsletters, have catalysed significant advancements in Technology Enhanced Learning (TEL) research and practice. The initiative's success aligns with the TPACK framework (Mishra & Koehler, 2006) and social learning theory (Bandura, 1977), supporting contextualised AI integration in pedagogy and andragogy across diverse educational settings. Our CoP has overcome significant challenges, including sustaining engagement across time zones and sourcing diverse expert speakers, through dedicated leadership and strong institutional support. The CoP's impact led to its official recognition and the formation of a cross-school steering committee, further amplifying its influence and demonstrating its strategic importance to the institution. This presentation will share key insights from our journey, including strategies for fostering engagement in a remote, cross-cultural CoP focused on rapidly evolving technology. We will discuss successful AI-enabled pedagogies implemented by CoP members, how challenges were addressed, and the impact of diverse cultural perspectives on AI adoption. A key lesson learned is the importance of balancing AI integration with maintaining academic integrity and authentic assessment in the rapidly evolving landscape of educational technology. By sharing our experiences, we aim to provide a model for other institutions seeking to harness collective intelligence in shaping the future of AI in HE, while addressing critical issues such as appropriate AI use, systemic approaches to programmatic assessment, and the process of learning and teaching in an AI-enhanced environment.

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• Data-Driven Teamwork: Navigating the Barriers to Effective Student Collaborations in Large Cohorts

  Angela Sun, Helen McGuire

  Group assignments are a staple in higher education, providing opportunities to enhance collaboration and communication skills. However, we frequently encounter grievances related to group work as coordinators of large STEM units (800 students). Our student survey identifies work ethic and communication discrepancies between group members as barriers, often leading to uneven workloads, dissatisfaction, and diminished collaborative learning (Bacon et al., 1999). Common mitigation strategies to address work ethic discrepancies, like group charters and peer evaluations, often prove ineffective, since they could be ignored if not properly followed up or enforced (Chang & Brickman, 2018). Another barrier to group productivity lies in the team formation process itself. Traditional team formation methods – self-selection, random assignment, or instructor-led grouping – each present inherent limitation. Self-selection often results in homogenous groups susceptible to "groupthink" (Janis, 1982), limiting the diversity of thought essential for creative problem-solving. Random assignment, while seemingly impartial, can lead to imbalanced skillsets and an uneven distribution of workload (Bacon et al., 1999). While instructor-led grouping might seem ideal, it is logistically impractical within large cohorts (Decker, 1995). Computer-aided team selection offers a promising alternative. Its automated process streamlines team formation, generates diverse teams, and allows instructors to focus on teaching, despite concerns about increased workload (Cavanaugh et al., 2004). To address these group work challenges, we have developed a multi-pronged strategy integrating computer-aided team selection with a comprehensive follow-up and feedback framework. Our goal is to transform group work from a source of anxiety to a rewarding learning experience. Our approach combines technology with strategic interventions: Computer-aided Team Formation: We utilise Gruepr, an open-source team selection software (Hertz, 2021), to generate groups based on student preferences including work styles and meeting preferences (Cavanaugh et al., 2004). Gruepr integrates seamlessly with our learning management system, Canvas. Structured Communication, Collaboration, and Proactive Monitoring: Regular temperature-check surveys deployed through Canvas allow students to rate their group's progress and workload distribution. This data enables early identification of potential issues. To encourage group dialogue, the aggregated and anonymised outcome is shared with team members Facilitating Peer Feedback and Communication through SRES: The Student Relationship Engagement System (SRES), a learning analytics tool (Liu et al., 2017), was used to communicate aggregated peer feedback to individual group members, encouraging constructive dialogues regarding group progress. Our evaluation compared student performance, feedback, and complaints from the current year to previous years, alongside an estimation of staff workload. Preliminary findings demonstrate a reduction in staff time spent on group formation using Gruepr's automated grouping, highly contingent upon accurate survey design. Complaints, though still reported, were less severe, suggesting that regular temperature checks promoted proactive communication. Importantly, student feedback provided valuable insight, with many groups identifying the need for increased in-person interaction and improved scheduling strategies to accommodate diverse commitments. Our presentation will elaborate on these results, showcasing both successes and challenges, and propose a refined workflow to further enhance collaborative learning experiences.

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• Harnessing AI: Seamless Digital Tool Integration for Enhanced Educational Outcomes

  Enosh Yeboah, Carlos Prieto Alvarez

  Integrating digital tools in education is essential for innovative teaching and learning (Msafiri et al., 2023). However, their mere availability does not ensure effective implementation. This presentation explores the development of an AI-powered chatbot designed to assist academics and learning designers in effectively using digital tools. Guided by the Technological Pedagogical Content Knowledge (TPACK) model and the Teaching Enhanced Learning Accreditation Standards (TELAS) framework, this project aims to bridge the gap between tool availability and effective usage. Effective implementation of digital tools begins with human factors, precisely the vision and expertise of educators. To achieve this, the TPACK model highlights three critical domains: technological knowledge, content knowledge, and pedagogical knowledge (Mishra & Koehler, 2006). These domains are critical to the effective and successful implementation of digital tools in the teaching-learning ecosystem. Our AI-powered chatbot leverages the TPACK model to connect educators’ pedagogical and content knowledge by conducting a needs assessment based on user-provided inputs and recommending suitable tools for enhanced teaching and learning. The chatbot interacts with users through precise, conversational inquiries, gathering detailed information on course titles, learning objectives, students' expectations, delivery methods, interaction types, desired tool functionalities, and accessibility considerations. This comprehensive approach ensures the chatbot provides well-informed, contextually relevant responses and resources to the users, thereby enhancing instructional effectiveness. By offering continuous support through our self-enrolled teaching support Canvas site, the chatbot ensures educators have access to assistance when needed, making it particularly beneficial for busy academics and learner designers. This then breaks the traditional barriers of time and place and offers users flexibility and real-time quality digital tool solutions. The chatbot knowledge base is built from a comprehensive tool document that maps each available tool at the [university name] to the TELAS framework. This framework sets rigorous standards and criteria for evaluating the quality of online environments, making it ideal for assessing tools across critical domains, including the online learning environment, learner support, learning and assessment tasks, and learning resources. By configuring this quality resource, the chatbot empowers educators to develop a deeper understanding of effectively integrating technology into their teaching practices for a successful learning experience Additionally, the chatbot provides real-time solutions on available tools, supporting continuous professional development and helping educators stay updated with the latest digital tools for their teaching needs. It offers use cases and knowledge base articles, addressing fragmented knowledge, time constraints, and technical expertise gaps, making it a valuable resource for newly recruited learning designers or academics to easily familiarise and induct themselves in the digital tool space. It offers quality assurance in tool usage by employing the TELAS framework. Moreover, the user data collection can provide insight for organising tailored training and support for academics. In conclusion, this presentation demonstrates the practical application and benefits of our AI-powered chatbot to improve digital tool integration in education. Using the TPACK and TELAS frameworks, the chatbot provides personalised support, helping educators seamlessly incorporate technology into their teaching and offering real-time recommendations to address digital tool challenges. It helps both new and experienced educators enhance their teaching, combining technology, pedagogy, and content knowledge for effective learning.

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• Strengthening social presence and connectedness in 100% online courses through CONNECT

  Tracey Ahern, Tracey Gooding

  Over recent years, higher education has seen a significant shift toward online courses. Factors driving this change include digital technology ubiquity, diverse student populations, workforce demands, and the increasing need for more flexible learning environments (Serrano et al., 2019). However, while online course enrolments are rising faster than on-campus courses, retention rates remain lower (Australian Government, 2021). Evidence suggests that online education can negatively impact students’ sense of connection, leading to feelings of isolation and disempowerment (Roddy et al., 2017). This is also reflected in the Australian University Mental Health framework (Orygen, 2020) which emphasises creating supportive online learning environments that promote student well-being. The Australian Universities Accord (Australian Government, 2024) calls for universities to embrace TEL. However, given that research has shown the need for more professional development (PD) and support for online educators (Ahern and Biedermann, 2022; 2023), innovative, evidence-based strategies are needed for organisations to build capacity in online teaching. Drawing on a comprehensive review of literature, the authors developed CONNECT: a framework to enhance social presence and connectedness in online learning (Ahern et al., 2024). Grounded in research underpinned by Garrison et al.’s (2000) Community of Inquiry (CoI) framework, the principles of Universal Design for Learning (CAST, 2018) and leveraging TEL, this framework offers educators a roadmap for nurturing a sense of community that positively influences student well-being, engagement, and overall success. Key components of the CONNECT framework are: C - Communication is responsive and supportive O - Optimal online presence N - Nurture educational and professional growth N - Networking opportunities fostered E - Engaging communities of learning C - Contemporary and authentic content T - Timely and effective feedback for learning (Ahern et al., 2024). The study follows a quasi-experimental design to evaluate the effectiveness of CONNECT in guiding teaching staff to use evidence-based strategies to promote belonging and connectedness in online education. In phase one, CONNECT was implemented within a 100% online postgraduate (PG) subject. This presentation will showcase online teaching strategies used to apply all elements of CONNECT as implemented in phase one. Phase two, also showcased, involved creating and releasing an online short course as professional development for teaching staff across two PG online courses at the authors’ university: Master of Nursing (MN) and Graduate Certificate of Diabetes Education (GCDE). After these implementation phases, the third phase will measure the effectiveness of CONNECT across the two PG courses. Data will be collected via (i) a student survey and (ii) a staff survey. Data analysis will compare the experimental group (participants enrolled or teaching in MN or GCDE) against the control group (participants not enrolled or teaching in MN or GCDE). Data will be collected from students and teachers across Australian universities offering 100% online courses. We hypothesise that by implementing CONNECT, the study will (1) Show improved student satisfaction in the experimental group and (2) Add to the body of evidence to inform and support teaching staff to develop strategies that can help build connectedness and social presence in online learning.

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• Students as collaborative partners: Embedding AI literacy in higher education

  Yasaman Mohammadi, Shayaan Malik, Antonette Shibani

  In contemporary society, Artificial Intelligence (AI) pervades numerous facets of our lives and is likely to impact many sectors and professions, including education. Tertiary-level students in particular face challenges regarding the use of AI for studies and assessment, including limited understanding of AI tools, as well as a lack of deep critical engagement with AI for learning (Shibani et al., 2024). To respond to emerging developments in generative AI, the recent Australian Tertiary Education Quality and Standards Agency (TEQSA) report suggests tertiary-level learning and assessments be designed to foster responsible and ethical use of AI (Lodge et al., 2023). This involves the development of AI literacy among students to engage with AI in critical, ethical ways that aid their learning and not hinder it. Our project aims to narrow the AI literacy gap among students from diverse study backgrounds by providing foundational knowledge and developing critical skills for practical use of AI tools for learning and professional practice, in collaboration with students and academics as part of a Students as Partners (SAP) initiative. Staff bring expertise in AI critical engagement and students bring practical, first-hand experiences of learning in this collaboration, supported by the university’s SAP program. Building on the current UNESCO recommendations for the use of generative AI in education (UNESCO, 2023) and prior theoretical frameworks on AI literacy (Chiu et al., 2024; Ng, et al., 2021; Southworth et al., 2023) we target key skills that higher education students should develop to meaningfully engage with AI. By creating accessible and engaging resources, such as instructional videos and comprehensive guides on generative AI applications like ChatGPT and ways to prompt for enhancing learning, we introduce existing AI tools and teach students to use them effectively, promoting a hands-on learning environment. Using learning design principles, the developed curriculum will be presented in an AI Literacy module on a Canvas site, with supporting instruction workshopped with student participants for evaluation. Student cohorts recruited from diverse disciplines will pilot and assess the effectiveness of the program, and qualitative methods such as focus groups and interviews will be used for evaluation of our intervention and continuous improvements. Findings will inform tertiary students’ current level of AI literacy and the effectiveness of interventions to improve key skills beyond their disciplinary knowledge, better preparing them for life beyond university. Indeed, the implementation of similar AI literacy courses has demonstrated statistically significant improvements in AI literacy and understanding of AI concepts amongst university students (Kong, Cheung, & Zhang, 2021). Our approach underscores the importance of relational engagement in higher education with students as partners (Matthews, 2018) and participatory design with students in a topic that is significant in the current age of AI (Laupichler et al., 2022). The course's flexibility to be accessed directly or embedded into other curricula ensures scalability and broader impact, solidifying the validity of our multifaceted approach. Through utilising relevant research methodologies and learning design principles, we endeavour to create an AI literacy course that is robust, accessible, educational, and engaging to use by tertiary-level students from diverse study backgrounds.

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• Designing platforms for digital object-based learning

  Jessica McKenzie, Michael Rampe

  Over the last decade, object-based learning programs have become a staple of museum collections. These programs encourage and allow patrons to engage with a series of curated objects, offering educational experiences through tactile exploration. Naturally, they are focused on having their audience engage with the physical objects themselves (Chatterjee & Hannan 2016). Applying museological practice and object-based learning in the digital context requires not just presenting digital replica of physical objects, but scaffolding their presentation and platform with purpose, intent, and understanding of the strengths and pitfalls of digital delivery (Beetham & Sharpe 2013; De Kluis, Romp, & Land-Zandstra 2024). As such, digital object-based learning platforms and programs purposefully designed for remote learning and online delivery fill a unique niche in the higher education space and are beginning to come into their own. At Macquarie University, objectbasedlearning.com (an initiative of the Faculty of Arts and stewarded by its Learning Design and Production team) was relaunched in late 2023 following an extensive redesign, with learning designers, academics, and students now working together to provide new remote learning opportunities and experiences for the classroom. This presentation introduces the audience to the refurbished website, explains the ethos behind its redesign with an eye to evolving learning spaces and remote learning, and explores the site’s current and future applications and projects as a case study for designing digital object-based learning. The site was designed with future utility and outreach at its core, offering flexibility in how it presents and categorizes digital objects, and a site layout which reflects the needs of its target audience – schoolteachers. The NSW Stages 5 and 6 Curriculum informs the website’s design, determining how objects are grouped, how users navigate the site, and what information and metadata is prioritized, developed, and displayed. Since its relaunch, the website has been utilized in schools and faculties in NSW to deliver object-based learning experiences and classes. While it is too early to publish on outcomes of the project, early feedback has been positive, and new teaching initiatives have developed around the platform. In 2024, student interns at Macquarie were challenged to develop educational materials, lessons, and workshops which took advantage of the potential of technology-enabled object-based learning. These artefacts were designed to give students a unique object-based learning experience, removing the boundaries of physical distance, financial constraints, and fragility of objects. Moreover, student interns involved in the photogrammetric scanning of objects for the website were themselves enjoying an object-based learning experience, engaging with their materiality and learning how best to present the object in a digital environment.

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• Games: The WD-40 of Learning : Unlocks Engagement, Smooths Collaboration!

  Nirav Parikh, Pete Fernandes, Leona Norris, Tran Thuy Nguyen, Nick Lekakis, Mark Brown

  The educational landscape has undergone a paradigm shift in recent years, particularly due to the COVID-19 pandemic. The rapid transition to remote learning environments, while ensuring educational continuity, may have inadvertently compromised the development of essential soft skills necessary for in-person interactions, such as communication, collaboration, and teamwork—skills that are vital for success in the workplace (Knight et al., 2021). While games have long been used in education (Conney & Darcy, 2020; Pagel et al., n.d.; Yuan et al., 2020), this study explores the potential of modernizing traditional game-based learning by integrating digital consoles and physical games into contemporary business classroom settings. This approach leverages the inherent appeal and engagement of games (Conney & Darcy, 2020; Hunicke et al., 2004), while fostering the development of critical soft skills. Building upon established frameworks for evaluating educational games, we explore the effectiveness of collaborative games in promoting positive learning experiences. Studies have shown that GBL can enhance motivation, knowledge retention, and problem-solving skills (Lester et al., 2023). Furthermore, collaborative games, by their very nature, necessitate effective communication, teamwork, and strategic planning among players (Pagel et al., n.d.). This project delves deeper into this aspect, investigating the potential of collaborative games to specifically address the regression of soft skills observed in the post-pandemic era. The initial pilot phase of this research focused on Pico Park on the Nintendo Switch and the Team 3 board game as potential collaborative games to cultivate soft skills. Using the MDA Framework (Hunicke et al., 2004), a well-established educational game evaluation tool, we assessed the games' ability to foster desired soft skills. Both games require effective communication, coordination, and strategic thinking, which are essential for fostering teamwork, collaboration, and problem-solving. Additionally, their accessibility and diverse formats (digital and physical) offer opportunities for students to practice soft skills in different learning environments, ultimately contributing to the research's goal of investigating the effectiveness of collaborative games in promoting positive learning experiences. The pilot involved approximately 50 students across three classes of the same course. Anonymous open-ended feedback was collected from participants using a survey questionnaire adapted from Conney and Darcy's (2020) design, which was based on the Kirkpatrick Four Level Evaluation Model (Kirkpatrick & Kirkpatrick, 1959, 1994). Participants were asked to provide their perceptions of the games, what they learnt, and the potential impact on their future group work. Preliminary findings from the pilot data are promising. Students found the games "fun", "different learning", “useful”, “refreshing”, "amazing", "engaging", "excellent for communication" and more (n=50). 98% of students (n=50) felt more confident in their ability to collaborate with others after playing the games and nearly 95% (n=50) indicated that it helped them identify potential teammates for their group assignments. Anecdotal evidence from academics and students corroborates the quantitative results, reporting increased motivation, improved team dynamics, and a more positive overall learning experience, suggesting that these activities significantly improved teamwork skills. To compliment this qualitative feedback, academics (n=3) observed a decrease in group issues and an increase in grades of around 5% for the major group assessment, bringing the average up from 60% in previous semesters to 65% in the trial period. This research aims to contribute to the existing literature on educational games and soft skills development. By demonstrating the positive impact of collaborative games on student engagement, teamwork, and soft skill development, we hope to encourage further exploration and implementation of this approach in classrooms. The findings of this pilot study highlight the potential of games to not only revitalise traditional pedagogy but also exhibits how technology can be used to address the critical need of fostering essential soft skills in a post-pandemic educational landscape.

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• Gen AI and student perspectives of use and ambiguity: A multi-institutional study

  Tim Fawns, Michael Henderson, Kelly Matthews, Glenys Oberg, Yifei Liang, Jack Walton, Thomas Corbin, Margaret Bearman, Simon Buckingham Shum, Trish McCluskey, Jan McLean, Antonette Shibani, Aneesha Bakharia, Lisa-Angelique Lim, Nicole Pepperell, Christine Slade, Jen Chung, Ari Seligmann

  Advances in generative artificial intelligence (GenAI) have created uncertainties and tensions in higher education, particularly concerning learning, equity and quality. Despite emerging empirical research, much current policy is based on assumptions about how and why students are using GenAI. This Pecha Kucha reports on 20 online focus groups involving 79 students from four Australian universities. Each focus group represents a mix of disciplines and levels of study (including undergraduate and postgraduate). We conducted reflexive thematic analysis, adopting a relational view of AI (Bearman & Ajjawi, 2023) that supports a nuanced examination of how AI uses are enacted, understood, and contested within educational settings. Our study shows that students use GenAI in diverse and complex ways and their beliefs about GenAI contain ambiguity, contradictions, and tensions. In this pecha kucha we focus on five interrelated tensions, identified across participants, and selected as particularly significant and challenging for educators. The salience of these tensions varied across participants but, together, they paint a complex picture of student engagement with GenAI. Tension 1 is between student perceptions of AI in terms of enhanced efficiency and concerns about academic integrity. Students reported that GenAI tools could speed up writing, editing, summarising, and simplifying complex materials. However, many also feared that short-cuts and efficiencies could lead to accusations of cheating. Tension 2 is between widespread adoption of GenAI tools and ambiguous policy around acceptable use. Many students used a diverse range of GenAI tools, yet a number of participants voiced uncertainty about allowable use of GenAI in assessments. A perceived lack of clear and detailed guidance from universities created confusion and anxiety, and the development of personal rules to avoid accusations of academic misconduct. Tension 3 is between empowerment and dependency. AI tools were sometimes seen as reducing inequalities (e.g. for international students or those requiring language support). On the other hand, some students expressed concerns about becoming dependent on GenAI tools where tasks were made too easy, undermining learning and skill development. Tension 4 is between access and equity. Closely related to tension 2, here, the reduction of barriers to academic writing and accessing educational resources is contrasted with concerns around exacerbating inequalities due to variation in access and support. These concerns are amplified through diversity of engagement, beliefs of students and educators around acceptability, and contextual pressures (e.g. fear of being left behind, time pressures, the perceived stakes of assessment). Tension 5 is between beliefs about deepened engagement with learning materials and reduced quality or accuracy of GenAI output. Some students reported that GenAI tools could provide useful perspectives on resources or simplify complex texts. However, many voiced frustration that GenAI tools sometimes provided incorrect information, required verification or “missed the point”, which could lead to significant additional work. These tensions highlight areas where students need additional support and guidance. The overlaps and entanglements of these tensions make their navigation in higher education particularly complex. These findings suggest practical implications for educators, policymakers, and institutions. For instance, to better support students, institutions should continue to develop clear, context-sensitive guidelines that resolve ambiguities around acceptable use (Tensions 1 and 2) and provide concrete strategies to balance the benefits of efficiency with concerns over academic integrity and dependency (Tensions 1 and 3). Additionally, efforts should be made to ensure equitable access to GenAI tools and support (Tension 4) while helping students critically assess the quality of AI-generated content (Tension 5).

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