Research Projects

This project will inform the School of Education, and other stakeholders, how to better prepare and support pre-service and in-service teachers for encounters with radicalized students beyond the current scope of curriculum planning and design. This is a rapidly developing phenomena, and to ascertain how to respond, it is important to gather as much data as possible. Media reports and other relevant literature indicate a growing problem globally, however, little is known regarding detail of the nature of the local situation.

Research output: Two articles in The Conversation: May 2024 and Aug 2024. Publication forthcoming.

Teaching Impact: This project informs teaching content for pre-service teachers across multiple courses.

Strategic impact: This project has informed community discussion on the topic through radio interviews and media articles .

This project explores concepts and insights regarding the interaction between Artificial Intelligence (AI) and creative industries. This will inform the researchers on the role of creative practitioners and how they engage with technology in order for the University of Adelaide to be part of the future in Creative Industries through meaningful collaborations.

Research output: This project has been presented as a 3 minute pitch to the CSIRO OnPrime program. Research Paper is forthcoming.

Teaching impact: Preliminary findings have been introduced into first year and Masters Education courses

Strategic impact: Industry collaboration with a range of colleagues across the sector both nationally and internationally. Has fed into discussions around the Signature research them for Adelaide University on Creativity

eMedici, an online assessment platform incorporating multiple choice questions and case studies, is aimed at medical students and graduating doctors with content 'crowd sourced' from contributors, who are usually medical students. eMedici’s content is aimed at medical students and graduating doctors. The study compares human- generated multiple choice questions (MCQs) with those generated by ChatGPT. A 'Worklist' function enables editors to specify content that is required in the item bank. Submitted content undergoes a rigorous review process using peer and expert reviewers. Reviewers are medical practitioner clinicians who are subject matter experts. Reviewers interact directly with the question author to edit the content. The review process from submission to finalisation for publication can take 1-2 months. The study compares the quality of human-generated MCQs with those generated by ChatGPT.

Research output: Preprint Article: Article submitted to International Journal of Artificial Intelligence in Education.

Teaching impact: This project identifies the capacity of AI to develop assessment materials of high quality for formative and summative assessment.

Strategic impact: The findings of this project feed into ongoing policy discussions on learning and assessment in an AI environment.

This systematic review examines the role of prompt engineering during interactions with Generative Artificial Intelligence (GAI) in higher education to discover potential methods of improving educational outcomes. Drawing on a comprehensive search of academic databases and relevant literature, key trends, including multiple framework designs, are presented and explored to review the role, relevance, and applicability of prompt engineering to purposefully improve GAI-generated responses in higher education contexts. Multiple experiments using a variety of prompt engineering frameworks are compared, contrasted and discussed. Analysis reveals that well-designed prompts have the potential to transform interactions with GAI in higher education teaching and learning. Further findings show it is important to develop and teach pragmatic skills in AI interaction, including meaningful prompt engineering, which is best managed through a well-designed framework for creating and evaluating GAI applications that are aligned with pre-determined contextual educational goals. The project findings outline some of the key concepts and frameworks that educators should be aware of when incorporating GAI and prompt engineering into their teaching practices, and when teaching students the necessary skills for successful GAI interaction

Research output: Under revision with Artificial Intelligence in Education

Teaching impact: The findings will inform curricula re Prompt Engineering skills for students. e.g. The Common Core course at Adelaide University on AI

Strategic impact: The outcomes of this project will support students in being better prepared for using AI in their careers

Research in Artificial Intelligence in Higher education has led to the development of two short courses. The courses offer practical insights into ethical decision-making processes in the context of AI. Interactive hypothetical scenarios have been designed to enhance students’ and professionals’ ability to identify and address ethical dilemmas. The courses incorporate ethical decision-making models, real-world AI ethical dilemmas, and concepts around academic integrity, plagiarism, data manipulation, and authorship attribution in interactive branching scenarios narratives.

Research output: Course design reflection publication forthcoming.

Teaching impact: A course on Ethical AI for Students (Canvas & edX).

Strategic impact: This project supports the strategic direction of the University to ensure students are informed of the ethlcal issues around the use of AI. It also engages industry in the development and use of the forthcoming course for professional. 

In collaboration with Google, this project aims to 

• To generate deep insights into how schools adopt technology within the local cultural, political, and economic context.
• To measure impact on teachers and students and their experiences adopting technology for learning.
• To measure change in digital maturity of staff and students and impact of technology using a digital maturity model and the SAMR framework, which categorises four different degrees of classroom technology integration.
• Evaluate the key requirements of professional development and how it is received and matches expectation

Research output: A publication on the evolution of digital maturity in teachers and students is forthcoming.

Strategic impact: This project is a collaboration between schools, government and industry showcasing the University's commitment to engage in world leading research.

At the turn of the Twenty-First century, Gordon McCalla published an article in the International Journal of Artificial Intelligence in Education in which he attempted a ten-year forecast of the character of learning, teaching and technology with a focus on implications of AI in education. Now, a quarter of a century later, with ever evolving technological developments, constant flux in online environments, and recent dramatic advancements in AI, a revision of McCalla’s predictions are overdue.

Research output: International Journal of Artificial Intelligence in Education (Q1)

Teaching Output:

Strategic output: Equity of access to technology in HE (Vulnerable students, Digital Divide)

The project has the following research objectives: 1) To examine how CoPs operate and in what ways teaching and learning knowledge is created and shared within CoPs and relevant teaching communities. 2) To identify key factors that enhance knowledge creation and dissemination within and through CoPs to teaching communities, and 3) To provide key lessons about CoPs as knowledge management and sharing and academic development tools to the HERDSA community, educators and other CoPs. We utilised the community of experts and practitioners of HERDSA but also local ones such as HERGA to gather views and ‘best practices’ about knowledge sharing within CoPs and between CoPs and the teaching community. The identified Milestone 4 of the application – dissemination of findings – has already started with the presentation of the findings at the 2023 HERDSA Conference; and a draft of a paper completed.

Research output: Publication in HERD, Presentation at HERDSA conference and workshop at HERGA conference.

Teaching Output:

Strategic output:

Recent developments in Artificial Intelligence (AI) suggest that it will likely change the way Universities design, construct and assess their courses. The main outcome of this project will be the development of a risk assessment tool that can be quickly applied to identify courses where learning may be at risk.

Research output: Publication in Q1 journal, Presentation at Conference.

Teaching Output: Redesign and update EDUC7063OL, Reviews of assessment practice

Strategic output:

Anne Frank, a young victim of the Nazis in World War 2 has been made famous in many media including a virtual reality (VR) experience available free on the Oculus 2 platform: Anne Frank House VR. This project is measuring empathy for Anne Frank based on users’ experiences in this VR scenario.

Research output: Publication in Q1 journal, Presentation at Conference.

Teaching Output:

Strategic output:

This project will survey and interview academics across disciplines and discover how they develop and implement videos in their teaching and their understanding of pedagogical issues related to its use Videos in HE. The aim of this project is to understand academics’ use of video in a higher education context and their understanding of the pedagogy behind its use. Video is a key component of learning and teaching in the 21st century. However, there appears to be minimal understanding of the best pedagogical use of video recordings, the format, the content and delivery. The differences between positive and poor pedagogical design in video content and use can have a significant impact on the ability of video to support learning. Carmichael et al.’s 2018 white paper found videos show “high levels of demonstrable impact” (p.16) in HE by contributing positively to students’ confidence, motivation and performance levels. However, they conclude: “there is much more to be learned about the measures of success” (p.16).

Research output: Publication in Higher Education journals.

Teaching Output:

Strategic output:

This project will interview key educational influencers across disciplines and discover their perceptions regarding their personal role in education and how they frame their online presence to facilitate those goals. Educational influencers are prevalent in social media and can have positive impact on learning of children and adults alike. Social media can play a significant role in learning and teaching, however, there is little empirical research on the motivations of content creators or approaches to this task. Since the advent of social media, influencers have played a role in communicating to the general public and have been utilized for supporting tertiary learning. Some of these influencers focus on educational content although this represents only a small amount of the content on YouTube. There is substantial research on the use of YouTube on several topics including politics and lifestyles, but this is often carried out from the users’ perspective or based on analytics taken from social media channels. This project aims to focus on educational influencers and their motivations and practices on YouTube to gain knowledge of pedagogical value.

Research output: Publication in Higher Education journals.

Teaching Output:

Strategic output:

The main aim of this project is to gather and evaluate staff and student views and experiences about two different aspects of their learning: (i) collaborative and enquiry-based learning (students working in groups to research and analyse issues related to the course content and (ii) using generative AI for academic research, writing and assessments in university courses. The project has the following research objectives:

1. To gather the views and experiences of staff and students using generative AI for their academic work (this may include, but is not limited to; tutorial work, assessments, test preparation, essays, projects, and any creative task where GenAI could be employed) and learning in University courses;

2. To gather the views and experiences of staff and students about collaborative and enquiry-based learning (EBL); and

3. To provide key lessons and strategies for how best to use EBL and generative AI as part of student learning in University courses

Research output: Publication in Higher Education journals.

Teaching Output:

Strategic output:

This study analyses the potential application of ChatGPT in assessing and reviewing university course outlines across all discipline areas of a leading university in Australia. The purpose of the review was to evaluate and critique course outlines regarding their cultural literacy. The sample comprised 584 subject course outlines, which included the synopsis and intended learning outcomes from each discipline offered by the university. Data analysis focused on the investigation of aspects of cultural literacy via the use of Open AI’s Large Language Model ChatGPT3.5 to test its function as a useful tool to evaluate the extent of cultural literacy that may be evident in the delivery of the subject. ChatGPT was also used to develop a framework for assessing cultural literacy content which was then used as the metric in this study. It has been revealed in the study that ChatGPT has generated an appropriate level of quality evaluation in assessing and reviewing the evidence of cultural literacy from the university’s course outlines. It needs to be iterated in this study that ChatGPT is useful in providing preliminary analysis and that the ultimate judgement of the necessity of embedding cultural literacy is still assigned to the course coordinator(s) to ensure the credibility and reliability of the response from ChatGPT.

Research output: Publication in Higher Ed journal.

Teaching Output:

Strategic output:

Over the last few decades in education, there has been a progressive change towards more student-centred and self-directed learning. Teaching and learning is moving from teacher centred pedagogies and practices to personalised learning in which students are more actively involved in the learning process and where students demand more flexibility through online and blended university courses. Many recent reports (see Gordon 2014; Ryan and Tilbury 2013) stress the importance about more ‘flexible pedagogies’ in which flexible institutions, flexible teachers and flexible students come together to increase the quality of the learning experiences for the students. This includes personalised learning through more flexible content, delivery and assessment (Gordon 2014, p. 10). Personalising education and learning means that the “learner is central” in that the needs, interests, backgrounds and learning styles of individuals are placed at the centre, and students are more empowered through more “choice and voice” in their learning (Keamy et al., 2007, p. 2). Making learning more flexible and personalised is about ‘learner empowerment’ in their learning journeys (Ryan and Tilbury 2013, p. 5).This project aims

• To investigate students’ views and experiences about personalized learning, self-directed learning, and student involvement in undergraduate online and on campus courses in the Faculty of Arts
• To provide key strategies teachers for implementing personalized flexible learning for students in undergraduate courses

Generative AI technologies have brought new opportunities and intensified existing difficulties in the realm of assessment and instruction in higher education. The rise of AI has led to concerns around assessment reliability, susceptibilities to cheating, and the authenticity and relevance of examinations (French et al., 2023). Much is at stake as learning in higher education is not just driven through curriculum, but by how educators assess (Soledad Ibarra-Sáiz, et al., 2021).

By leveraging systematic review findings (Palmer et al., 2022), this project analyses the shifting practices of assessment in higher education. With traditional assessment approaches weakened by the threats posed by generative AI (Lodge et al., 2023), assurance is needed that high quality learning is taking place and assessment processes play a meaningful role int hat process. 

The introduction of ChatGPT in November, 2022 has brought a new level of Artificial Intelligence (AI) to the public attention and accessibility. As a result, it has been adopted in academia by students, some of whom have been found to submit works generated by AI. Universities have been employing TurnItIn as a plagiarism checker and this service has recently added an AI detection mode. However, as this is fairly new, it is worth double-checking any suspicious submissions with a third-party AI detection tool. This report details a research project testing five free online AI detection tools and their ability to assess AI content in two simulated academic assignments.

Research output: Article in The Conversation (THE Campus) https://www.timeshighereducation.com/campus/how-hard-can-it-be-testing-dependability-ai-detection-tools

Conference Paper: Lee D. How_hard_can_it_be? Testing_the_reliability_of_AI_detection_tools. Based on paper presented at HERGA Conference, Adelaide, 2024

Teaching Impact: Reviews of assessment practice. Content introduced to multiple courses across the University and feeding into conversations around Common Core courses

Strategic Impact: Findings feed into ongoing strategic discussions on the use of AI across the University and internationally

Lecturers in an Australian university’s preparatory/enabling program have observed reduced engagement with course readings by the student cohort. Proposed solutions included formative quizzes based on the readings and including TED-talks as course readings. This research explored the validity of employing ChatGPT to design formative assessments to  measure student learning and engagement with TED-talks. Transcriptions of TED-talks were submitted to ChatGPT along with prompts engineered to elicit maximally valuable formative assessment questions. Three levels of prompts were developed from very basic to progressively more detailed and contextualised. The research addressed the following questions: Can GenAI develop meaningful assessment questions to assess the level of engagement and/or  understanding of TED-talk content?, and: Does more detailed Prompt Engineering result in more valuable responses?

The research found ChatGPT required well-crafted prompts and progressive training to generate meaningful and relevant responses. Although ChatGPT can produce potentially viable draft formative quiz questions, strategic prompt  engineering with detail and context produces more valuable results. However, they will still need further human input to make them meaningfully useable. This reflective autoethnography offers a unique insight into multiple factors of interest. The prompt engineering experiment demonstrates practical models. Using TED talks as course readings engages with contemporary resources. The overarching perspective of engaging preparatory students brings unique perspective.

Research output: Publication in Artificial Intelligence in Education. HERDSA Conference Paper.

Teaching impact:

Strategic impact: Festival of Teaching and Learning 2024

Research is being conducted to investigate the immediate and long-term implications on learning and teaching of both staff and students engaging with Artificial Intelligence (AI). Findings of this research is providing guidance to staff and students by examining current practices and making recommendations regarding assessment, curriculum design, and Learning and Teaching (L&T) activities (AI CoP).

Research output: At least 2 journal outputs (Staff/Student). Multiple conference papers

Teaching impact:

Strategic impact: Strategic Pathway

Supporting personalised learning is frequently highlighted as a key advantage of GenAI chatbots in education. This project will assess the readiness and effectiveness of GenAI chatbots for personalised German learning by evaluating their implementation, ethical implications, and potential benefits versus drawbacks, as well as developing metrics to measure their quality in supporting personalised German experiences.

Project Lead: Yuran (Beta) Wang

Supervisors: Edward Palmer, Simon Walsh

Despite the relatively widespread use of blended learning approaches in higher education, learning analytics have traditionally been a by-product of student learning activity. Although largely decoupled from educational and learning theory, these analytics have been used in many studies to identify students that are deemed to be ‘at risk’ and to predict their final results. A common goal has been to prevent withdrawal from study and address aspects of wellbeing however, there is little evidence to suggest that these interventions have a positive correlation with successful student learning outcomes. Precision Education has promised to address these shortcomings and offer greater personalisation of learning however, it remains an emerging field and is yet to be implemented at scale.

This study will analyse deidentified matched data from the University of Adelaide LMS and Student Management System to investigate relationships between student demographics with learning behaviours and outcomes. This data will be compared to information collected separately through surveys and interviews with teachers and students using demographics as the constant. It is anticipated that this research will assist the development of resources supported by artificial intelligence that enhance teaching and learning pathways for future students.

Project lead: Shaun McCarthy

Supervisors: Edward Palmer, Nick Falkner

There has been an increase in the use of Virtual reality (VR) in schools, yet due to a gap in the literature educators andresearchers have a limited understanding of how VR contributes to the development of schema and impacts on the humancognitive process (Albus et al., 2021).

This research aims to determine if VR has a positive impact on achievement and determine how VR effects the cognitive loadof students compared with traditional teaching methods.

It is hypothesised that VR will enhance achievement and reduce effect on students’ cognitive load due to the vivid and lifelikesimulations which afford students the ability to assimilate new learning to previous knowledge.

Project Lead: Jaclyn Stefan

Supervisors: Edward Palmer, Nicole Nelson, Ancret Szpak

This research will investigate the feasibility of using a biometrically enabled gaze-based tracking engine within a VR simulation to train and assess SA (Situation Awareness).  By tracking where users look and what they interact with, the purpose-built simulation has the ability to not only provide reflective feedback mechanisms in regard to SA, but in addition, trigger events and outcomes in real-time within the simulation itself.

Project Lead: Steve Cook

Supervisors: Edward Palmer, Anna Ma-Wyatt

Undergraduate student paramedics undertake approximately 300 Work Integrated Learning (WIL) hours with a jurisdictional ambulance service during their studies (Council of Ambulance Authorities, 2018 ).  The clinical environment is complex and fraught with an array of complex challenges which impact upon their learning experience. 

This research explores how Immersive Virtual Reality (IVR) can be used to bring student paramedics together in an online immersive virtual environment to participate in a VR Community of Practice (CoP). 

The research will establish the contemporary challenges facing student paramedics during WIL, will identify how Australian Universities support their students to get the moist from their WIL experience, and will evaluate the strengths and limitations of using IVRCoP for supporting students during WIL.

Project Lead: Sam Willis

Supervisors: Edward Palmer, John Rae, Lyn Karstadt

This research addresses critical challenges in constructing lunar infrastructure to help ensure the success of upcoming lunar programs by NASA and the Chinese Space Agency. It aims to enhance astronaut training and real-time decision-making in lunar construction tasks. Rooted in the Construction 4.0 framework, it integrates advanced technologies such as XR, AI, and robotics. It uses XR simulations to analyze the impact of extended reality on astronauts’ task performance in human-robot collaborative lunar habitat construction. Beyond developing safe and effective methods for lunar habitation, it offers potential applications in terrestrial industries, including construction, mining, and healthcare.

Project Lead: Albert Rajkumar

Supervisors: Amit Srivastava, Anna Ma-Wyatt, Edward Palmer

The proposed study investigates secondary students’ behavioural engagement in online mathematics classes. It seeks to develop a detector (an online learning website) that can automatically report students’ off-task behaviours by accessing data from the log. This study also analyses the factors of such behaviours and provides suggestions to improve students’ online engagement.

This study will fill a significant gap in engagement theories by proposing the conceptualisation of students’ online engagement at the classroom-level, including its definition, facilitators, outcomes, and aligned measurement. This study will also narrow the proposed conceptualisation down to the content delivery stage within the online classes to provide an educational theoretical ground for intelligent detectors. This underlying solid support from an educational perspective will fill an essential gap and add knowledge to the basement of detector studies. Furthermore, a new framework for building up the detector will be proposed to make a further step in this area.

Project Lead: Yang Li

Supervisors: Igusti Darmawan, Edward Palmer

Remote learning used to be a blended teaching mode for students to learn asynchronously and synchronously (Burdina et al., 2019). It has proved to be advantageous for a multitude of students. By using technologies in education, students are able to learn flexibly and improve problem-solving skills, self-determination abilities and critical thinking (Simpson, 2010).

However, the outbreak of COVID-19 reshaped the teaching mode as fully home-based online learning. The new experience created more challenges for teachers, parents and students, such as teachers lacking knowledge in using online resources, students lacking independent skills for self-managing and parents lacking time to support (Carpenter & Dunn, 2020).

This study aims to explore remote learning in Central China during COVID-19 pandemic through the perspectives of students, parents and teachers to determine how online learning can be effectively developed in the future. Findings of this research will provide significant implications for teachers, school leaders and policy makers, refreshing their understanding and aiding them in making effective educational decisions regarding online learning and teaching. 

Project Lead: Mengyuan He

Supervisors: Edward Palmer, Chris Boyle, Walter Barbieri

Global commentators discuss innovation in emerging economies and education as essential, valued and desired. On a regional and state level, policy faces challenges in scaffolding innovation and evaluating improvements as a result of it. Critical examination of education-specific examples of innovation and the processes enacted to establish these approaches is essential to bridging the gap between aspirations of innovation and their implementation in complex systems such as schools.

Processes associated with implementing innovative education will be analysed within a variety of sites. Particular areas of interest will include identifying commonalities in motivations for innovation, implementation frameworks and technical skill development. Such commonalities will provide thematic evidence for facets of an education specific model of innovation requires

Project Lead: Kristy Rose Davis

Supervisors: Edward Palmer, John Willison

Miscommunication of forensic evidence can result in disastrous consequences, from miscarriages of justice to innocent people being convicted. But communicating complex subject matter is no easy feat, and is further complicated by people being unaware of their own biases and lack of knowledge. While existing literature has examined the effect of factors such as crime show viewing on perceptions of guilt or innocence, very few studies directly measure the beliefs and perceptions that people hold of forensic evidence processes or their awareness of their own knowledge. This PhD aims to explore people’s metacognition, examining whether how much people think they know about forensic processes is calibrated with what they actually know, and whether this affects their evaluations and perceptions of forensic evidence. Finally, this PhD will explore educational and narrative interventions that can aid in the communication of forensic evidence with accuracy and comprehensibility.

Project Lead: Daniella Chiarolli

Supervisors: Rachel Searston, Edward Palmer

This research will conduct quantitative and qualitative research methods to investigate the roles and impacts of SPOCs on flexible learning in Chinese higher education context. It has two objectives:

• To examine how SPOCs contribute to personalised learning experiences and engagement from the perspectives of SPOCs users (students).
• To collect feedback from SPOCs stakeholders (teachers and institutions) to provide insights into the effectiveness of SPOCs in Chinese higher education context.

Project Lead: Yali Chen

Supervisors: Edward Palmer, Thomas Wanner