Learning Practices Research Articles

AI-based feedback tools in education: A comprehensive bibliometric analysis study

This bibliometric analysis offers a comprehensive examination of AI-based feedback tools in education, utilizing data retrieved from the Web of Science (WoS) database. Encompassing a total of 239 articles from an expansive timeframe, spanning from inception to February 2024, this study provides a thorough overview of the evolution and current state of research in this domain. Through meticulous analysis, it tracks the growth trajectory of publications over time, revealing the increasing scholarly attention towards AI-driven feedback mechanisms in educational contexts. By describing critical thematic areas such as the role of feedback in enhancing learning outcomes, the integration of AI technologies into educational practices, and the efficacy of AI-based feedback tools in facilitating personalized learning experiences, the analysis offers valuable insights into the multifaceted nature of this field. By employing sophisticated bibliometric mapping techniques, including co-citation analysis and keyword co-occurrence analysis, the study uncovers the underlying intellectual structure of the research landscape, identifying prominent themes, influential articles, and emerging trends. Furthermore, it identifies productive authors, institutions, and countries contributing to the discourse, providing a detailed understanding of the collaborative networks and citation patterns within the community. This comprehensive synthesis of the literature serves as a valuable resource for researchers, practitioners, and policymakers alike, offering guidance on harnessing the potential of AI technologies to revolutionize teaching and learning practices in education.

Urban Pre-service English-as-a-Foreign-Language (EFL) Teachers’ Challenges During Teaching Practicum in Rural Schools: A Photovoice Phenomenological Approach

While many previous studies focused on English-as-a-Foreign-Language (EFL) teachers’ teaching practices in urban schools, little study has been indulged regarding pre-service English teachers’ (PSTs) challenges and experiences to practice teaching in a rural school. This study aimed to explore various difficulties encountered by urban PSTs during teaching practicum (TP) in rural schools. A total of seven PSTs enrolled in urban universities were voluntarily involved in a study that involves people’s senses and perceptions, rather than scientific evidence, also known as a phenomenological study. Data were collected through multiple semi-structured interviews, followed by a photovoice approach through which the participants were asked to take emotional photos. The results revealed that the PSTs encountered four main challenges during TP in rural schools, including changes in teacher identity construction, intercultural sensitivity barriers, a lack of supporting resources, and limited teacher professional development. Each challenge was accomplished by photographs representing PSTs’ emotions and feelings, such as a collection of dolls, natural scenery, old-printed books, and blank paper. In conclusion, integrating emotional photos into descriptive exploration is paramount evidence of how the challenges were encountered, managed, and solved for better future teaching and learning practices.

Online Learning and its Transformative Impact on Digital Learning in Higher Education Institutions

The COVID-19 pandemic has catalysed a significant transformation in higher education, accelerating the adoption of digital learning methodologies and challenging traditional pedagogical approaches. This study employs a mixed-methods approach to investigate online education's efficacy during this transition. A questionnaire administered to students (n=36) explores their experiences, challenges and perceptions of online learning, aligned with the TPACK framework. Additionally, semi-structured interviews with teachers examine their strategies, approaches and assessment methods online. By integrating insights from both students and educators, the study aims to provide recommendations for overcoming identified constraints in online education. The research also explores gender differences and motivational levels among participants, offering a comprehensive understanding of factors impacting online education. Findings will elucidate the current state of online education in higher education institutions and identify areas requiring improvement. As academia shifts towards blended learning, open education and digital learning, this study contributes to facilitating the effective implementation of online teaching and learning practices among students and teachers.

The Practice of Project-Based Learning in a Management Information Systems Course for Graduate Students

The Project-Based Learning (PBL) is a contextualized learning method based on constructivist theory, enabling students to learn knowledge by applying knowledge and conducting experiments. Most researcher in PBL focused on the K-12 and undergraude students, less focused on graduate students. This article integrates PBL into the teaching practice activities of a management information systems (MIS) course for graduate students and constructs a PBL process consisting of four stages: startup period, middle period, presentation period, and closing period. It aims to address the practical application of relevant theories of MIS and the application of emerging information technologies in solving practical problems, so as to improve students' active construction ability of course knowledge and effectively enhance their team collaboration ability.

Her Music Academia: A Public Scholarship Initiative

Abstract As a subfield of music theory scholarship, public music theory engages audiences outside of the academy. The onset of the internet has additionally provided new open-access media and sites for music theoretical inquiry. Two ways in which public music theory exists on the internet are in the form of podcasting and blogging. In this essay, I explain the reasons I started my podcast and blog (both titled Her Music Academia), the ways the work has taken shape over the years, and what I have learned so far. Through these projects, I seek to introduce the process of becoming a music theorist to a public audience, highlight my own experience as a Black woman in academia, and create a sense of community around music theory. I continue the practice of learning in public by documenting the development of my research and ideas about music, and I encourage my audience to similarly embark on their own process of learning about music theory. Ultimately, Her Music Academia challenges academic music theorists to reevaluate its definition of scholarship and to consider how these two opposing methods of performing scholarship differ in goals and outcomes.

BLENDED LEARNING IN TEACHING ENGLISH LITERATURE DURING THE COVID-19 PANDEMIC: TEACHERS’ PERCEPTIONS

This study investigates teachers' perceptions of blended learning in the context of English Literature during the Covid-19 pandemic. The research aims to understand how English teachers adapted to the sudden shift from traditional to blended learning environments. The research includes exploring the strategies employed by teachers when integrating literature lessons into a blended learning approach, impacts of blended learning during the pandemic to teachers’ teaching professionalism and problems faced by teachers when designing Literature lessons during the pandemic. Four English Literature teachers from SMK Datuk Peter Mojuntin, Penampang participated in semi-structured interviews, providing different perceptions into their experiences with blended learning. The findings reveal that technology played an essential role in facilitating teaching and learning during the pandemic. The combination of traditional and digital methods allowed for a balanced approach to teaching English Literature, fostering interactive and collaborative learning experiences. Despite these benefits, the transition to blended learning presented significant challenges in terms of adaptation, professional growth and connectivity issues. The study helps to understand the implications of this research especially for researchers, teachers and students. The data gained from this study offer guidance for improving blended learning practices and addressing the needs of students and teachers in a rapidly evolving educational setting.

Responding to AI

The influence of artificial intelligence “has enormous implications for higher education” (Bearman, Ryan & Ajjawi, 2023, p. 369). Those of us teaching in the higher education sector have felt this profoundly: after the rapid uplift in digital teaching and learning practices in response to COVID 19 we are required, yet again, to respond to a new set of challenges brought about by the impact of AI. As an example, chatbot technology is calling into question the reliability of the traditional essay as a valid assessment tool (Stokel-Walker, 2022), requiring significant critical reflection and reevaluation of assessments from teaching academics to ensure course learning outcomes are met. This presentation outlines how a teaching specialist academic working in an initial teacher education (ITE) programme at a South Australian university carried out one such redesign. The focus of the re-design was a ‘unit/year plan’ assessment task for a final year curriculum specialization topic. The redesign aligned with the two guiding principles from TEQSA’s Assessment reform for the age of artificial intelligence (Lodge et al., 2023). The first of these guiding principles: ‘Assessment and learning experiences equip students to participate in a world where AI is ubiquitous’ (p. 2) points to the importance of educating students around AI use relevant to their learning. The second guiding principle: ‘Forming trustworthy judgements about student learning in a time of AI requires multiple, inclusive and contextualised approaches to assessment’ (p. 3) underscores the ongoing necessity for universities to have effective means by which to measure student learning outcomes, especially in accredited courses. The redesign of the assessment task both acknowledged the potential of AI for use in the professional space, and simultaneously sought to ensure assessment validity through the inclusion of an interview with the pre-service teachers. Overall, the redesign of the assessment task incorporated three components. Firstly, a brief introductory module about discipline-specific uses of AI was incorporated into the online course content. Secondly, pre-service teachers were ‘permitted’ to utilise available AI platforms in the creation of their planning task. Thirdly, the assessment process was adapted to include an oral presentation (Gulikers, Bastiaens & Kirschner, 2004) conducted as a panel interview in which each pre-service teacher could provide evidence of the pedagogical perspectives underpinning their plan and subsequently demonstrate the successful achievement of topic learning outcomes. The purpose of the panel interview was to assist assessors in forming a judgement about pre-service teachers’ pedagogical understanding and application, in line with relevant criteria from Matheis and John’s Comprehensive Authentic Assessment Model (CAAM) (Matheis & John, 2024). Autoethnographic reflections on the first delivery of the redesigned assessment are provided, including alternative approaches for future iterations. The learnings from the teaching initiative outlined in this presentation contribute to the growing discussion about how we can develop the capacity of our pre-service teachers as skilled and critical practitioners who can utilize AI as a valuable tool for their ongoing professional practice.

Affinity spaces

This poster (Padlet ‘Collaborative reflection on AI’) showcases a professional development approach that uses Padlet as an affinity space (Gee, 2004; Honeychurch, 2023) for educators to collaboratively explore and reflect on their experiences with Generative AI (GenAI) in education. Following Vallor’s distinction between ease of creation (a key affordance of AI) and challenges of creative expression (a solely human capacity), we found that Padlet was an accessible tool for creating virtual affinity spaces, and that the Padlet format offers a visual representation of a collaborative method of co-creating that ASCILITE attendees can interact with, using a range of multimodal creation tools, including AI-based features available in Padlet (image creator, text-to-speech, and a poll creator). This poster may function as a catalyst for conference attendees to reflect on their own position in this rapidly developing space, and as a model of practice that educators can adapt to their own contexts to design GenAI-integrated learning experiences. Educators need novel ways to make sense of the changing nature of education with GenAI (Vallis et al., 2023) and advance both research and practice in technology-enabled learning. Drawing on a paradigm for academic development that is centred on the notions of construction and co-construction as a process of learning (Pimmer et al., 2016, p. 495), this inquiry used Padlet to provide an affinity space for this sense-making. Affinity spaces differ from communities of practice in having a flat hierarchy instead of a periphery of less experienced practitioners around a core of experts; people enter an affinity space as interactants (“affines”), rather than members (Gee, 2005). In this inquiry, a Padlet provides a “portal” (Calder et al., 2021, p. 448) to an affinity space, a space where contributors who have varying levels of (GenAI) expertise can bond around a shared endeavour (for a comparable use of Padlet to house a ‘thinktank’ for a scholarly project in teaching and learning, see Coleman, 2023). The Padlet serves as both an interactive platform for educators to engage with various perspectives on generative AI in higher education and a model for future learning activities. The aim is to facilitate knowledge sharing and community building around GenAI in education: as Timperley (2008, p.19) states, “participation in a professional community with one’s colleagues is an integral part of professional learning that impacts positively on students”. The collaborative aspect of this inquiry sparked conversations, introduced collaborators to new tools, and stimulated reflection. It encouraged a patchwork of contributions in a variety of formats to provoke more perspectives. It allowed expression of sociotechnical imaginaries about GenAI (Costello, 2024; Dishon, 2024), including themes of “overwhelm to excitement”; “creative potential to concerns of control”; and perceptions of GenAI from “uncanny to real”, and demonstrated that sharing creative practices in a virtual space allows educators to develop new knowledge about their experiences, concerns, and insights about integrating AI into their educational practices.

A risk-based approach to mitigating the Gen(AI) challenge to assessment integrity

In the evolving landscape of higher education, emerging technologies such as Generative AI (GenAI) present both opportunities and challenges. The rapid increase in access to, and sophistication of, GenAI poses significant challenges for our institution and the wider sector (Bearman & Luckin 2020, Bobula 2024, Chan & Hu 2023). The most immediate of these challenges is the increased risk to the existing approaches used to assure that students achieve the stated outcomes of their learning experiences. Director of Higher Education Integrity Unit, TEQSA, Dr Helen Gniel argues ‘We are entering an age where institutions can no longer ensure the integrity of every single assessment, and it makes sense to think at that bigger level […] what are the mechanisms that you have in place to be confident that an individual has demonstrated the learning outcomes to receive that degree’(TEQSA information request: AI risk mitigation, webinar, 21 March 2024). While higher education institutions are exploring opportunities to realise the potential benefits of GenAI, our immediate focus is on mitigating these risks. This poster describes institutional Programmatic Assessment Security Project (PASP) at the University of Newcastle (UON), a pioneering four-stage initiative designed to address academic integrity risks associated with inappropriate uses of GenAI in summative assessment (Lodge 2024). Academic integrity risks in this context refers to the potential for students to engage in academic misconduct by using GenAI tools in ways that violate institutional policies or ethical standards for assessment. These risks pose a threat to the validity and reliability of summative assessments, potentially compromising the integrity of academic qualifications and the learning process itself. Led by the central teaching and learning support unit, in collaboration with the Artificial Intelligence Working Group (AIWG) a group of expert practitioners and academic stakeholders at UON, the PASP aims to secure assessments across a program of study, assuring student attainment of program learning outcomes. This innovative approach aligns with the sector’s focus on programmatic assessment and supports compliance with regulatory requirements, including TEQSA’s mid 2024 request for institutions to submit a detailed action plan to mitigate the risks that GenAI poses to the integrity of awards (TEQSA 2024). This poster showcases exemplary innovation in practice through the PASP, advancing research and practice in technology-enhanced learning (TEL). The PASP employs a risk-based approach, identifying seven risk factors for inappropriate student use of GenAI in assessment tasks. The first step in this project involved Course Coordinators completing an Assessment Reflection Survey, guiding them to reflect on individual assessment tasks in relation to these risk factors. The survey data were then used to compile an understanding of the varying levels of assessment risk across the institution’s programs. The PASP will deliver a defined series of secure assessments, delivered at key moments across a program of study to assure student attainment of program learning outcomes. This poster provides insight into UON’s contemporary and agile approach to TEL and assessment redesign, with potential for staff at other institutions to adopt similar responses.

Assuring and Improving Learning Outcomes

Universities have a responsibility to measure and assure graduate learning outcomes ("Higher Education Standards Framework (Threshold Standards)," 2021; TEQSA, 2017). However, while assuring learning outcomes is a priority across the sector, many universities fail to collect meaningful data on student achievement of these outcomes (Martin & Mahat, 2017). Some institutions are investigating technologically enhanced processes to improve the efficiency and accuracy of learning-achievement data (Burrack & Musselwhite Thompson, 2021; El Marsafawy, 2022). Over the past four years, the University of Technology Sydney (UTS) Business School has made substantial enhancements to assurance of learning (AoL) practices, leveraging learning management system (LMS) functionality and data visualisation software to create a streamlined process, which better facilitates the continuous improvement of programs. This work is of particular interest to academic and professional staff involved in collecting and reporting on student achievement data, in program continuous improvement and evaluation, or in leveraging technology-enhanced learning analytics. The UTS Business School’s AACSB accreditation necessitates the collection, tracking, and reporting of student achievement of program-level learning outcomes (AACSB, 2020). Each program identifies subjects to "develop" and "assure" learning outcomes, with student achievement measured within specific assessment tasks and collated for program-level analysis. This process can be administratively complex, and historically involved multiple manually collated spreadsheets. This represented a substantial time cost for the faculty and often resulted in unreliable data. It was, for example, common practice to report overall subject marks rather than the specific learning outcome to determine achievement level, resulting in assessment practices that diverged from the recommended standards of constructive alignment (Biggs, 2014). In 2021, faculty T&L and central learning technologies teams commenced a pilot using LMS tools and the interactive data visualization tool PowerBI to streamline data collection, collation, and visualisation. Canvas Outcomes set up at the faculty level allows for centralised achievement-data collection, which, when linked to student and program information in PowerBI, can be used to obtain program-level insights. Beyond administrative efficiency, the project was also designed to improve and foreground the constructive alignment (Biggs, 2014) of measured learning outcomes. The revised process requires the embedding of learning-outcome-aligned assessment criteria within rubrics, resulting in improved constructive alignment and data transparency. The initial pilot was evaluated using Human Centred Design (IDEO.org, 2015) methods, which concluded the new system was an improvement on previous processes. Since the pilot, the faculty has completed a full rollout to over 60 subjects and 20 programs. Once this foundational AoL process was in place, program and subject-level continuous-improvement projects could be built upon it. Previous reporting methods had limited usefulness to Program Directors and were no longer fit for purpose due to changes in AACSB requirements. Reporting processes were therefore adjusted to focus on continuous improvement of key program metrics. In the new process, Program Directors and teaching teams review program data to identify curriculum or student-experience improvements that will enhance student achievement of learning outcomes. For example, a master's program identified that a high percentage of students were falling below expectations in two outcomes. Investigating the causes identified a need for substantial changes, with new subjects taking assurance responsibilities, and revisions to the program's overall assessment strategy. Recent data shows significant improvements in the target outcomes. This presentation will outline these updated technology-enhanced AoL processes demonstrating how the collected data can be used to improve university programs and the student learning experience.

The Virtual University as a Frontier for Navigating New Learning Spaces, Pedagogies, and Technologies

We explore the practical and strategic considerations essential for establishing and maintaining a successful virtual university. Building on core concepts from the book, Technology Enhanced Learning and the Virtual University (Sankey et.al., 2023) we highlight the need for strategic approaches to online and digital education. This panel discussion will cover governance, the virtual environment, stakeholder support, the alignment of learning theory and practice, and the preparation of educators for online teaching. It will explore the necessity of collaboration to leverage digital opportunities and mitigate risks. Additionally, the panel will address the transformative impact of artificial intelligence and gamification on online learning and consider academic integrity and student engagement along the way. Our discussion will emphasise the importance of adaptive leadership and robust quality processes. While our focus is on the development of a virtual university, the topics we present are relevant across all aspects of digital education and e-learning, especially as universities adapt to an evolving educational landscape.

Building Bridges

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.

Bridging Cultures, Advancing AI

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.

The Future of Feedback

Research shows that feedback practices significantly impact key student outcomes, including performance, engagement, and satisfaction (Esmaeeli, Shandiz, Shojaei, Fazli & Ahmadi 2023). Feedback is a crucial component of learning in Higher Education (HE) and plays a vital role in developing critical thinking, improving retention, and enhancing student engagement. The importance of timely dialogic feedback in enhancing student engagement and potentially improving retention is well understood (Advance HE 2020). However, academic staff are increasingly time-poor, with reduced opportunities to provide regular in-depth quality feedback outside of that given for summative assessment (Henderson, Ryan & Phillips 2019). Early experimentations with using Generative AI (GenAI) such as ChatGPT to provide feedback for formative assessment recognises that students will learn and work in an AI-enabled world beyond their university studies (Bowditch 2023). GenAI can be leveraged inside and outside the classroom to achieve positive student engagement and improved skill development thereby affording them the skills and knowledge necessary to succeed (Hooda et al. 2022). Engaging with GenAI for feedback purposes offers an opportunity to increase equitable access to feedback across the student cohort, to support and further develop their critical skills and learning outcomes. As Verhoeven and Rana (2023) note, “AI disruption may present an opportunity to shift the focus from assessment of learning to assessment for learning”. Utilising GenAI for feedback purposes can provide rapid, personalised learning support, and aid with planning, drafting, and revising student work. However, this adoption of GenAI for feedback must be driven and developed by the educator, keeping the human in the loop to ensure quality (Atchley, Pannell, Wofford, Hopkins & Atchley). Our project draws on the principles of feedback literacy, current research on using AI as learning tool (Verhoeven & Rana 2023b; Tubino & Adachi 2022) and emphasises student-centred learning through dialogic feedback practices. The project draws on scholarship from Mollick and Mollick’s seven approaches to student use of AI (2023), Perkins, Furze, Roe and MacVaugh’s framework for ethical integration of AI in assessment (2024), and emerging work from Liu, Brightman, and Miller on GenAI and feedback (2023). This presentation addresses the conference theme of Technology, providing an overview and reflection on staff development and adoption of GenAI for feedback processes for the benefit of student learning. We will showcase four use cases of the use of GenAI to design and implement feedback creation for undergraduate formative assessment across the three Colleges at the University of Newcastle. All cases engage innovation in Technology Enhanced Learning (TEL) practice in developing GenAI tools to support student learning via feedback. The presentation addresses the benefits and challenges of each approach. Recognising the value of feedback in student learning, this PechaKucha is aimed at a diverse audience in HE. Our presentation will demonstrate applicability and adaptability to a range of disciplines as we explore the impact new and emerging GenAI technologies can have on HE. We will introduce the possibilities of using GenAI for feedback purposes, and encourage staff to consider experimenting with and adopting their own innovative TEL practices.

Students as collaborative partners

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.

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

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.

MAVR in the Metaverse

Extended reality (XR) technologies, which include virtual reality (VR), augmented reality (AR), and mixed reality (MR), are gaining significant attention from educators for their potential to transform teaching and learning in higher education. According to recent research, XR offers immersive and interactive experiences that enhance student engagement and provide unique opportunities for experiential learning (Merchant et al., 2014; Radianti et al., 2020). In response to this growing interest, various professional organizations have developed virtual communities of practice (Wenger, 1998) to support educators in integrating XR into their curricula. One notable example is the Mixed, Augmented, and Virtual Realities in Learning Special Interest Group (MAVR SIG) of the Japan Association for Language Teaching (JALT). Founded in 2017, the MAVR SIG was created to support language educators interested in adopting XR technologies for language learning (Hawkinson, Mehran, & Alizadeh, 2017). The SIG provides a platform for educators to share their experiences, exchange ideas, and collaborate on research focused on XR in education. This community of practice is instrumental in advancing the integration of immersive technologies in language education, aligning with the broader global trends in educational technology (Ferdig et al., 2020). The MAVR SIG facilitates knowledge sharing and professional development through a variety of events, including research presentations, workshops, symposia, and webinars. Recent workshops have highlighted the pedagogical applications of XR, such as immersive language learning environments, AR-enhanced vocabulary instruction, and the use of VR for cultural immersion. These events not only promote the use of XR in education but also encourage educators to critically assess the affordances and challenges of these technologies in teaching. The positive impact of this community of practice has been evidenced by a growing number of members outside of Japan including the Philippines and Turkiye . Based on interviews from international members, the lack of local groups that support research and collaboration related to immersive technologies for teaching and learning encouraged them to join the Japan-based group. A particularly noteworthy initiative by the SIG is its regular series of events hosted on the Metaverse platform, Frame (https://framevr.io/). Frame offers an immersive and customizable virtual environment where members can meet, interact, and collaborate in real time. The platform’s features, such as virtual rooms, collaboration tools, and generative AI functions, enable educators to experiment with new teaching approaches and test platform capabilities. By leveraging these tools, educators can enhance their teaching practices, receive feedback, and refine their approaches to using XR in language learning. Looking ahead, the MAVR SIG is poised to expand its impact by increasing the number of events, deepening collaborations with educational institutions and professional organizations in Japan and globally and exploring novel applications of XR in both language and interdisciplinary education. As the community continues to support educators and drive innovation, the MAVR SIG is well-positioned to lead the integration of XR technologies into teaching and learning practices worldwide.

Making comedy for learning spaces

Expansion of technology-mediated learning spaces creates opportunities for disrupting traditional learning and teaching norms and practices. Combining technological affordances and humour in online learning environments offers potential gains in student engagement and learning. Current research reports effectiveness of using humour for teaching but less on practical guidance for educators in how to professionally develop this. This paper is a critical autobiographic narrative about the experience of developing short comedy videos for teaching concepts that students commonly struggle with in an undergraduate methods of research course. Insights for practice include a seven-step method and critical reflection for educators interested in developing skills and networks for disrupting traditional teaching methods to create targeted humorous videos for specific concepts in their courses.

Exploring the integration of Generative AI in assessment in a tertiary context

The unprecedented advancements of Generative Artificial Intelligence (GenAI) tools have generated controversies surrounding their potential for transforming educational practices, and democratising knowledge sharing, while acknowledging risks to current educational practices. In order to understand the potential and risks of GenAI tools on educational practices, recent research point to the need to develop student and teacher AI literacy skills and to investigate the impact of GenAI integration in learning and assessment practices. In addressing the call for more research in the field, this study reports on the integration of GenAI tools in an academic assessment in a postgraduate course for pre-service language teachers at an Australian university. Data were collected from students’ reflections of their adoption of GenAI tools for planning their assessment and from qualitative surveys. Thematic analysis was employed to identify students’ perceived challenges and benefits in adopting GenAI for essay writing. Pre-service teachers recognised benefits in adopting GenAI for planning and generating ideas for academic writing but recognised the importance of mitigating risks created by inaccuracies or biases in content. The findings confirm the importance of transparency in the integration of GenAI and developing student awareness of and training in ethical use of GenAI for higher education.

Technology-enhanced Learning in Information Systems Education

The COVID-19 pandemic significantly disrupted higher education but also accelerated the adoption of technology-enhanced learning and innovative teaching practices to promote student-centred learning in higher education. Nevertheless, traditional, didactic, teacher-centred approaches in university teaching are still prevalent. Specifically, Information Systems (IS) and other technology-related disciplines are expected to adopt technological innovations more readily. Moving beyond the pandemic, there is a need to reassess the current state of Information Systems education and explore technologies that have been effectively deployed to identify best practices. This study involves reviewing thirteen subjects as part of a Master of Information Systems course offered by one of Australia’s leading universities. It aims to identify innovative technology-enhanced practices that promote student-centred learning, assess their adoption levels and impact, and reflect on any difficulties hindering their adoption. We identified three innovative technology applications that effectively facilitate student-centred learning: web-based interactive content, online collaborative workspaces, and simulation games. However, we found that these technologies are primarily adopted for tutorials. Nevertheless, the use of technology has led to a notable shift from the traditional teaching approach to a flipped classroom model. The findings highlight the need for university-wide support, policy changes, and investments in time, resources, and staff training to enhance student-centred learning through the use of technology.