Annual Learning and Teaching Conference and Teaching Excellence Awards

Dr Ellen Buck, PVC Education and Student Experience, Middlesex University

Is AI making us dumber? Personal reflections and strategic questions for harnessing GenAI in learning, teaching, assessment and research

Speaker

Dr Charles Knight, Director, Leadership, Governance and Management, Advance HE

Location:  50 minutes presentation

Overview: The proliferation of Generative AI prompts a crucial, perhaps unsettling, question: Is it making us dumber?

This keynote tackles this provocation head on, using a personal journey of integrating AI into professional life as a starting point to explore the big questions facing Higher Education as we harness GenAI.

Moving beyond immediate reactions, through reflections on his own evolving AI usage, Charles will guide the audience to consider some big questions for the sector:

• How do we adapt when AI assistance is ubiquitous, impacting how students – and we ourselves – learn, think and research?
• What cognitive and critical skills must we now prioritise to work with AI effectively?
• How do we navigate the ethical and equity dimensions?

Speaker

Laura Milne, Head of Digital Education, Centre for Academic Innovation and Development, University of Chester

Location: C201

Delivery: 40minutes presentation

Overview: We are all recovering from some of the fastest changing years in Higher Education, but we can’t afford to slow down yet! This session will explore how we might approach assessment raking into account careful use of Generative AI, with care being at the heart of it, both in terms of caution for a novel technology, and care for people involved in assessment. Rather than focusing on academic misconduct issues, this session will review how AI might be a support to students and staff during assessment, while keeping the human in the loop.

Jen Andersen, Senior Lecturer and Programme Leader at pointblank Music School, London

Location: C104, 20 minutes presentation

Overview: This session explores the integration of AI into the Marketing and Branding module at pointblank Music School, aligning the curriculum with industry practices while addressing concerns around academic integrity. The revised module introduces a two-step assessment process, where students first generate an AI-driven marketing plan, critically assess it, and then create their own marketing plan based on insights from the evaluation. This method reflects the real-world use of AI for idea generation, promoting critical thinking and original research.

The expected outcome is that students will develop stronger research, analytical, and practical skills with AI tools, while reducing academic misconduct by encouraging ethical AI use as a support tool rather than a shortcut for original work. This approach bridges academic learning with industry standards, preparing students for professional applications of AI in music marketing.

The results are expected to show that AI, when used responsibly, is a valuable educational tool. The revised assessment model serves as a potential framework for future curricula, and ongoing iterations will refine AI integration to further enhance marketing education.

Speaker

Dr Barbora Cherifi, Senior Lecturer in Tourism, Middlesex University London 

Location: C106, 25 minutes presentation

Overview: Changes within the educational landscape as a result of AI are unprecedented and fast-paced. There are many ways in which teaching and learning can be adapted to react to these changes. Whilst one way is to adopt AI to create learning experiences with high AI intensity, another option is to create experiences with low AI intensity. It is argued that such variety in learning experiences can be highly beneficial to students in attaining different skills. This presentation explores the latter approach - with focus upon developing learning experiences that are overwhelmingly complementary to working intensively with AI. The aim of the presentation is to focus on the application of practice-based experiences that require students to reflect on personal experience of field trips embedded within a module and apply these experiences to their recommendations for business development. The innovative approach that this presentation adopts, presents an alternative way of radical acceptance of AI within learning and teaching. Implications for adoption of this approach within different subject disciplines, beyond tourism, is also discussed. Evidence of impact is also explored.

Presenter

Dr Giacomo Nalli, Lecturer in Computing Science, Middlesex University London

Contributors

Proffesor Serengul Smith, Professor and Director of Programmes in Computer Technology and Multimedia Tech,  Middlesex University London

Dr. Kelly Androutsopoulos, Senior Lecturer in Computing Science, Middlesex University London

Michael Heeney, Technical Tutor in Engineering and Computer Science

Location: C107, 25 minutes presentation

Overview: Lack of student engagement is a common challenge that many educators face, particularly with large cohorts. This can have a negative impact on student performance. Several strategies have been adopted to try to improve student engagement, such as the use of collaborative activities based on heterogeneous groups, which enhance students’ knowledge and skills. However, collaborative activities have not always produced the expected results, especially when the groups have been randomly selected. This work presents our experience of using an AI prediction model to create heterogeneous groups of students for a collaborative Wiki-based activity.

Initial feedback shows positive outcomes, with the majority of the students believing that this increases student engagement (64%), motivation(68%) and group composition (70%) which are elements that that contribute to a positive impact on student performance.

Reflections from an ongoing professional dialogue between Early Childhood Studies and Social Work

Speakers

Dr Angela Scollan, Professor in Early Childhood, Middlesex University London

Dr Helen Hingley-Jones, Associate Professor in Social Work, Middlesex University London

Location: C107, 25 minutes presentation

Overview: This session aims to explore how students engage with AI in their summative assignments. This topic can be described, using Rittel and Webber words (1973) as a  ‘wicked problem’ extending to interconnected issues which are relevant for all academic subjects such as students’ engagement with quality checking of references; blandification of writing; sterilisation of individual critical thinking, engagement with module literature. A pressing question thus concerns the impact of the use of AI, as currently observable at the level of real-world practices, on the student-centred approach advocated by the MDX 2031 Learning Framework, in particular with regard to the promotion of critical thinking, creativity and employability in students, as well as with regard to the imperative of preserving academic rigour.

An ongoing collaboration between the areas of Early Childhood Studies and Social Work has opened cross-disciplinary spaces for collegial reflection, sharing teaching practice and comparing assessment outcomes. This collaboration is allowing tutors to benefit from a professional dialogue (Bohm, 1987) that explores the intersection between students' engagement with AI and their learning experience. In particular, this session discusses two of the themes emerging from the dialogue between ECS and SW tutors (i) ethical and moral dilemmas related to academic rigour (ii) impact of the use of AI on the development of employability skills and professional standards of students, and its implication on practice and stakeholders beyond the programme.

Speakers

Alicia Wright, Senior Academic Developer, Centre for Academic Practice Enhancement, Middlesex University London

John Parkinson, Senior Academic Developer, Centre for Academic Practice Enhancement, Middlesex University London

Location: C106, 40-minutes Workshop

Overview: Generative AI offers innovative solutions for developing educational materials and enhancing the teaching and learning experience. In this session, we will focus on how you can harness generative AI to develop effective pedagogical strategies for your practice. You will be introduced to Co-Pilot, a generative AI tool available to staff and students at Middlesex University through our Microsoft enterprise license that provides greater data protection than other freely available third-party GenAI tools. This interactive session will provide a hands-on opportunity to explore the educational benefits (and challenges) of Co-Pilot (so please bring along an internet-enabled device).

There will also be opportunities to discuss and share best practices with colleagues. By the end of this session, you will have gained practical insights into using Co-Pilot alongside new strategies for integrating GenAI into your teaching.

Jack Tims, Head of Careers and Employability, Middlesex University London

Location: C122, 25 minutes presentation

Overview: Middlesex University’s Graduate Competencies were co-designed with leading employers and student groups across our global campuses to reflect the essential skills and attributes needed for the future workplace. These competencies are embedded within our course portfolio, but do our community fully recognise where these are developed within a specific programme? Can students clearly identify the learning, activities, and assessments that demonstrate their graduate competencies? More importantly, can they confidently articulate these strengths to employers? In this session, using AI-powered platforms, we will guide staff to confidently map Graduate Competencies within programme activities and assessments ensuring students can see the real-world value of their learning. By making these connections explicit, we can boost student confidence, enhance employability, and align academic experiences with industry expectations. We will analyse academic journeys, assessments, modules, and wider co-curricular experiences, helping students present their value in job applications, interviews, and networking opportunities. 

By integrating AI into our programmes, we can provide students with deeper insights into their competencies and a clearer roadmap to success. Join us to discover practical strategies for embedding AI into your teaching and support systems - empowering students to take ownership of their career development with confidence and clarity.

Professor Rafe Hallett, Director of Learning and Teaching, Middlesex University

Location: C122, 25 minutes presentation

Overview: Professor Rafe Hallett (Director of Learning and Teaching) will present a brief, critical survey of emergent HEI approaches to AI, looking at the spectrum of policies, terminology and tone used as universities guide their students and staff on its use. Looking across the sector, the presentation will take a sample of institutional policies (and principles) relating to the educational use of AI, examining the way they frame its ‘appropriate’ and ‘ethical’ use by students as part of learning and assessment.

Speakers

Professor Kevin McDonald, Professor of Sociology, Middlesex University London

Ionela Frigura, BA Criminology with Policing Student in 3rd Year and Senior Student Learning Assistant, Middlesex University London

Location: C133, 25 minutes presentation

Overview: The session will explore the ways more mature policies also offer guidance to staff in integrating AI in assessing student work, constructing learning resources and modelling its progressive use. The talk will conclude with case-studies of universities who are building pathways and clusters of modules that oblige the interdisciplinary exploration of GenAI’s role in knowledge construction, and which stage its experimental use and reflective critique by students as a core part of assessment.

Speakers

Ruth Bonazza, Lecturer in Academic Writing and Language, Learning Enhancement Team, Middlesex University London

Peter Thomas, Senior Lecturer in Academic Writing and Language, Learning Enhancement Team, Middlesex University London

Dr Mark Wilkinson, Lecturer in Academic Writing and Language, Learning Enhancement Team, Middlesex University London

Location: C133, 25 minutes presentation

Overview: This presentation, given by lecturers from Academic Writing and Language (AWL, Learning Enhancement), explores the integration of GenAI in their teaching across the University at a time when we are all questioning what it means to be a writer in the age of GenAI. We explore this through a collection of practice examples. 
One of the module leads for SAT Foundation Year will discuss how students review the importance of understanding and utilising feedback on their language and writing with the assistance of GenAI. They explore how Microsoft Copilot supports this process, and analyse its limitations. In addition, the AWL lecturer supporting embedded sessions in ACI programmes covers using GenAI in writing, creating prompts, evaluating outputs, balancing AI and personal input, as well as ethical and environmental considerations. These students’ interactions with Copilot and their evolving relationship with AI as student writers will be discussed. Additionally, Copilot is embedded in the AWL ‘Grammar and Vocabulary’ short course to enhance communicative ability while acknowledging its limitations. Copilot's integration aims to provide students with critical awareness of writing development while also developing practical tools for improving their language skills and fostering a deeper understanding of grammar and vocabulary. The lecturers will explain their sessions and discuss student engagement.

Speaker

Dr Can Baskent, Senior Lecturer in Computing Science, Middlesex University London

Location: C104, 25 minutes presentation

Overview: In the past decade, academic prose has changed dramatically. Academics have started to find their own voice and style of academic prose. We have started to read peer-reviewed articles with 'I', written with a style of a first-person narrative. Once contrasted with the mechanical style of LLMs, it can be argued that academic writing is changing – both for machines and people. This is, however, not surprising when we remember how LLMs are "trained". As artificial models, LLMs heavily depend on the data they are trained with. Along this process, it fails to develop a voice. Apart from the fact that how far it is from "general intelligence", it can be argued, particularly within the domain of academic writing, how lacking LLMs are in terms of a voice and a stylistic prose. In this work, I will consider various examples from well-known academics and compare it with the prose of LLMs, underlying the increasing need for the academics and students to find their own writing style and voice. I will argue LLMs fall short from teaching students how to write, and more importantly, how they can find their voices. Finding their voices is essential for students to write in a way that distinguishes them from their colleagues and peers, giving them a competitive advantage in the job market.

Speakers

John Magpayo, Lecturer in Accounting, Middlesex University London

Shan Wang, Senior Lecturer in Accounting, Middlesex University London

Location: C104, 25 minutes presentation

Overview: This session delves into integrating artificial intelligence (AI) into accounting and finance education, from departmental policy development to practical application. The first part of the presentation discusses creating an AFE Departmental AI acknowledgement policy. This policy aims to balance AI's transformative potential with academic integrity. It outlines acceptable AI use and sets restrictions to prevent misuse, such as over-reliance on AI-generated content without critical evaluation. These measures ensure originality in student work, promote ethical practices, and enhance analytical skills. The second part of the presentation showcases practical AI applications in teaching and assessment, with examples from relevant modules:

• Theoretical understanding: AI is used to gain insights into key accounting theories
• Synthetic data generation: Students use AI tools to create synthetic data simulating real-world financial scenarios for financial modelling
• PROPER framework application: Students apply this framework to craft effective AI prompts for financial data analysis
• Critical assessment: Emphasis on evaluating AI-generated responses to build analytical thinking
• Ethical research: Engagement with Trailhead (recommended by Advance HE) to explore AI fundamentals and ethical considerations in the accounting and finance sector
• Industry reflections: Insights from industry experts shape the curriculum, preparing students for digital accounting practices rather than traditional approaches.

Claire Milburn, Senior Account Manager at Turnitin

Dr David Pike, Head of Digital Learning Systems, University of Bedfordshire

Location: C106, 40 minutes presentation

Overview: This presentation explores the University of Bedfordshire’s experience of enabling Turnitin’s AI detector, reflecting on the past, examining the present, and exploring the possibilities for the future of AI in assessment.

In the past, we consider what led the University to pursue AI detection in the first place: what were the concerns, hopes, and hesitations of academic staff around generative AI? We will explore the questions raised, the challenges anticipated, and how both staff and students were prepared for this shift – leading to the institutional decision to Turn-it-on.

In the present, we reflect on the reality of implementation. What did switching on the AI detector reveal about our practices, assumptions, and assessments? What were the surprises, the things we would do differently, and what surprised us when we worked with students? We will also share insights into how we communicated with staff and students, what we might have done differently, and what others – including colleagues at Middlesex – may wish to consider if AI detection is activated.

Looking to the future, we ask: what are the opportunities to engage with the idea that AI is Assistive Intelligence, or is this the beginning of the end? As AI and Generative AI tools become increasingly embedded in learning and assessment, what role might Turnitin play in helping institutions adapt? How can we move from reactive detection to proactive, ethical integration?

Join us as we explore what academic integrity means in this brave new world of algorithms, authorship, and AI.

Speaker

Dr Bastien Chabe-Ferret, Senior Lecturer in Economics, Middlesex University London

Location: C107, 25 minutes presentation

Overview: This session explores the impact of AI use on two dimensions of assessment: how well students perform and how efficiently and fairly they are graded. It builds on two case studies from the school of Business and Law to discuss opportunities and risks of integrating AI in the assessment process. Through critical reflection on our own practice, it aims at opening up the conversation around best practices for AI use in assessment. In particular, we will share how we deal with the questions of which AI tool to use (whether input data is used to train algorithms, GDPR concerns), but also report on the improvement in learning and student experience, as well as instructor experience.

Speakers

Dr Lyubomira Gramcheva, Senior Lecturer in Law, Middlesex University London

Dr Vesco Paskalev, Senior Lecturer in Business and Law, Brunel University of London

Location: C107, 25 minutes presentation

Overview: We will present the final results of a pilot research project aimed at studying how actual students use ChatGPT, funded by the Middlesex RFF scheme and QAA Scotland. We conducted experiments with students sitting different kinds of summative assessments (coursework and an invigilated exam) at Middlesex University, Brunel University, and Dundee University. Having submitted their actual summative assessments, participating students were asked to submit their assessments again, yet this time they wrote them using ChatGPT. In a focus group discussion, students were encouraged to share their experience of using ChatGPT and their perception of whether they performed better with its help. The assessments (real and experimental) were marked by research assistants who were asked to indicate which of them were written with the help of ChatGPT. The assistants were then interviewed to gain an understanding of what influenced their decision.
 
We show that a student who is not sufficiently prepared to pass an assessment may perform only a little better when using ChatGPT and for the better-prepared students, the ChatGPT effect is even negative. 

Speaker

Dr Clare O'Donoghue, Senior Lecturer in English for Speakers of Other Languages

Location: C109, 20 minutes presentation

Overview: ChatGPT ‘arrived’ 30/11/2022. By May 2023, Professor Richard E. Baldwin was warning at the World Economic Forum, “AI won't take your job. It's somebody using AI that will take your job.” Undergraduate university entrants in October 2024 have had two years to familiarise themselves with Generative AI tools. Some believe inputting an assignment task instruction into ChatGPT and paraphrasing the output is sufficient to succeed at levels 4-7 in HE.

This shows a gross misunderstanding of Professor Baldwin’s characterisation of the world of work in a GenAI-enabled world. Human-in-the-loop working with AI requires human qualities such as perceptive insight, critical thinking, ethical value judgements, logically consistent positionality, holistic problem-solving, creativity and embodied knowledge. That is to say, it requires far more than the ability to just paraphrase GenAI output.

This paper is a case-study of a first-year module in an Education Studies degree programme which integrated the use of GenAI as part of seminar and assignment tasks in order to help students develop their human-in-the-loop skills in a GenAI-enabled world. Examples of tasks and analysis of student observations about AI will be presented, as will recommendations for future practice. These findings are transferable to other disciplines.

Speakers

Naomi House, Senior Lecturer in Interior Architecture, Middlesex University London

Jason Scoot, Senior Lecturer in Interior Architecture, Middlesex University London

Location: C109, 25 minutes presentation

Overview: As part of the teaching and learning strategy in Y3 BA Interior Architecture we have been pioneering the use of GenAI across both design and research modules, asking students to use image generators such as Midjourney and Leonardo, alongside text generators including ChatGPT and Copilot to converge design thinking and design practice.

In a discipline where full-scale prototyping is impossible, students and practitioners alike have relied on a range of strategies to simulate design proposals to clients, users as well as to themselves. But with the introduction and fast-paced evolution of AI platforms the intersection of design-led research with the complex ideation of space and form are leading to design outcomes that are more refined and less constrained by existing skills and knowledge. Two years of anecdotal evidence suggests that using AI to scaffold students’ learning through the design process promotes risk-taking and embeds confidence in new technologies. Further, it facilitates a synergy across design and writing outcomes that is altering students’ - and our own - perception of how design is generated. This relates to disciplines such as Architectural Technology, Product Design, Branding and Digital Media, Graphics and Communication, to name a few.

Speaker

Dr Nina De Franco, Head of Veterinary Studies, College of Animal Welfare

Location: C122, 25 minutes presentation

Overview: This presentation aims to explore the transformative potential of Artificial Intelligence (AI) in education. The focus will be twofold: challenging traditional teaching practices and harnessing AI within developmental and management observation processes and audits. 

Challenging Teaching Practices: We will delve into how AI can be harnessed to innovate and enhance pedagogical methods. By integrating AI-driven tools, educators can personalise learning experiences, provide real-time feedback, and identify areas for improvement. This segment will highlight some practical examples of where AI can successfully transform teaching methodologies, fostering a more engaging and effective learning environment. Management Audits: On the flip side of this, the session will also cover the role of AI in conducting comprehensive management audits. AI can streamline administrative tasks, analyse performance data, and ensure compliance with educational standards. We will discuss how AI can provide actionable insights, improve decision-making processes, and enhance overall institutional efficiency. Case studies of how AI can review resources, provide feedback and make follow-up action plans will be discussed. Join me to discover how AI can be a catalyst for pedagogical excellence and institutional growth. This session aims to equip educators with the knowledge and tools to leverage AI for a transformative impact on teaching and management practices.

Speakers

Claire Defries PgDip, DipAVN (Medical), RVN, FHEA - Programme Leader, College of Animal Welfare

Lauren Norton MScCAB BSc (Hons), RVN CertVNEXX, FHEA - Lecturer in Veterinary Nursing, College of Animal Welfare

Location: C106, 50 minutes presentation

Overview: This presentation examines the integration of Artificial Intelligence (AI) within teaching and learning to facilitate the review of academic literature. The rapid advancement of AI technologies presents both opportunities and challenges in educational settings. This session compares traditional and AI-assisted review methods.

First-year BSc veterinary nursing students were introduced to academic literature and initially applied the Caldwell et al. (2005) framework using traditional review methods. In a subsequent lesson, AI tools were introduced to assist in their literature review process. Second year veterinary nursing students were introduced to AI tools as part of their module journal club. The integration of AI aimed to enhance students' analytical skills and efficiency in reviewing complex academic texts.

Students were asked to reflect on the risks and benefits of both approaches. This reflective process provided valuable insights into the effectiveness, benefits, and limitations of AI integration in academic settings. The session aims to highlight how AI can be leveraged to support student learning while addressing potential challenges such as accessibility, reliability, and the need for critical thinking skills.
By sharing these findings, this presentation seeks to contribute to the ongoing discourse on the role of AI in education and its potential to transform traditional teaching and learning practices. Leveraging AI can enable educators across various disciplines to enhance their teaching methods, improve student engagement, and foster a deeper understanding of complex subjects. This session aims to showcase these benefits and encourage the adoption of AI tools in diverse educational settings.

Speaker

Dr Annie Hughes, Head of the Learning and Teaching Centre, Kingston University London

Location: C133, 50 minutes presentation

Overview: Generative artificial intelligence (GenAI) poses a significant challenge to Higher Education (HE). Published research already claims to have invalidated University assessment systems (Scarfe et al. 2024). Add to the mix, the expectation of employers that graduates will be able to use GenAI effectively, there is a pressing need to rethink our teaching and, more specifically, our assessments, to ensure their validity in an AI-enabled world. This crisis could, I argue, return us to and reinforce key enhancements in higher education. I discuss two. The first is a prompt to go ‘back to basics’ and secondly it is an opportunity for a deeper recognition of the value of diversity and difference. By ‘going back to basics’ I am referring to the deep dive that is required to reflect on the skills that we are teaching and assessing in HE. If a machine can write an essay, or conduct the basic research, then why should we recognise and reward that ability as a higher skill? Secondly, I argue that GenAI challenges us to find ways to assess the authentic voices our students and to build on the inherent value of their diversity. Points for discussion will include: rethinking the balance between academic writing and oral and dialogic traditions, assessment process vs its product and the assessment of critical thinking through authentic mediums. In Summary, I argue that GenAI gives us significant opportunities to revitalise how higher education is delivered and assessed, freeing our students (and us) to think for (our) themselves.

Scarfe, P. Watcham, K., Clarke, A. and Roesch, E. (2024) A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study.

Speakers

Dr Kelly Androutsopoulos, Senior Lecturer in Computer Science, Middlesex University London

Dr Francois Chadebecq, Lecturer in Computer Science, Middlesex University London

Location: C104, 25 minutes presentation

Overview: Generative AI (GenAI) tools are advancing rapidly and performing well, especially in the context of computing. These tools can solve most introductory programming problems quickly and accurately while providing explanations for each line of code. This has an impact on teaching and assessment. Computer science educators have different approaches, e.g. from finding ways to integrate the use of GenAI tools, to banning their use altogether. 
 
In the first year Computer Science programming module, we have chosen to teach students good ways of using GenAI tools with programming, e.g. to understand a program, to generate trace tables and test cases, and even find the location of a bug. We also highlight concerns with using these tools, such as over-reliance and hallucinations. We adopt a competency-based assessment approach based on (Student Observable Behaviours) SOBs and allow the use of GenAI tools if students declare them and the extent of their use. Students are encouraged to take responsibility and be aware of the skills they are learning, i.e., programming or prompt engineer. We will present examples of how we teach students the use of GenAI tools in our teaching and our approach to assessment. We will also show some examples of how we use GenAI tools to support teaching that can be applied in other disciplines.

Speakers

Dr Lynda Hyland, Head of Careers and Employability Department, Middlesex University Dubai

Mariam Abonil, Lecturer in International Foundation Programme, Middlesex University Dubai

Location: C104, 25 minutes presentation

Overview: Many in the teaching profession report intrinsic rewards related to their role in the classroom (Watt & Richardson, 2020). One of these rewards is seeing the development of ideas and skills in students as the academic year progresses and recognising the academic achievement which follows from that development. To promote these outcomes, teachers invest time and effort in creating authentic learning environments for improved results. With the increase in student access to AI, faculty may feel unable to bridge the gap between their authentic interactions and objectives and the ‘artificial’ responses seen on coursework assessments (Corbin et al., 2025). 

With the multiple benefits that can be harnessed from the judicious use of AI in teaching and learning, the social impacts on a traditionally human profession must also be addressed. Faculty may previously have viewed student output as reflecting teaching efforts and engagement with AI in coursework preparation may dilute the evidence of learning outcomes as well as the role of teachers in student attainment. This interactive presentation aims to explore the effect of student use of AI on faculty motivation and sense of reward, and to discuss curricular and classroom changes that might offset the challenges posed by increased AI usage and access. In addition to all stakeholders in educational institutes, this topic may be of relevance to practitioners in wellness spaces.

Speaker

Dr Phil Barter, Academic Director, Middlesex University Mauritius

Mariam Abonil, Lecturer in International Foundation Programme, Middlesex University Dubai

Location: C106, 25 minutes presentation

Overview: As Artificial Intelligence (AI) becomes increasingly embedded in global education systems, transnational education (TNE) must navigate the tension between maintaining consistent academic standards and adapting to diverse local contexts. This session explores how Middlesex University Mauritius can strategically integrate AI into TNE while balancing Middlesex consistency with cultural, infrastructural, and ethical localisation.

Dr Noha Saleeb, Associate Professor in Creative Technology and Digital Creativity, Middlesex University London

Location: C107, 25 minutes presentation

Overview: Drawing on recent policy research from HEC Mauritius and the Commonwealth of Learning, the presentation highlights key findings on AI awareness, policy gaps, and stakeholder readiness. It introduces a practical framework for developing institutional AI policies that are inclusive, ethical, and context-sensitive. Participants will gain insights into stakeholder-specific competencies, policy development processes, and the role of governments in supporting equitable AI adoption.

Speakers

Dr Nishtha Lamba, Associate Professor in Psychology, Middlesex University Dubai

Dr. Sameer Kishore, Associate Professor in Robotics, Middlesex University Dubai

Location: C107, 25 minutes presentation

Overview: Pedagogical agents are increasingly used in online education, particularly for self-paced learning, yet their effectiveness based on their perceived human-likeness and ability to foster engagement remains to be explored further. This two-part research study examines how design of pedagogical agents of varying race and gender influences students’ perceptions of instructional quality and engagement and compares avatar evaluation with their real counterparts.

In Study 1, we evaluated four different pedagogical agents (Male/Female and White/South Asian) using the Agent Persona Instrument to measure perceived human-likeness. Results showed that male and South Asian agents were rated significantly higher in human-likeness than the others. Based on these findings, Study 2 used a South Asian male instructor and created a highly realistic doppelgänger avatar to deliver the same five-minute online lecture on introductory social psychology via a video call interface. A between-group design (n = 403) was employed, where participants watched either the real instructor or the lookalike avatar and completed a post-lecture evaluation. While no significant differences were found in learning-related aspects such as attention, comprehension, and reflection, the avatar was rated lower in personality-related traits, including enthusiasm, expressiveness, and human-likeness.

These findings suggest that pedagogical agents can effectively deliver instructional content but may lack interpersonal qualities that make human instructors engaging. As virtual teaching tools become more prevalent, ensuring pedagogical agents convey personality and relatability will be essential for maximising their impact on student learning.

Speaker

Kate Coulson, Associate Dean, BPP University

Location: C109, 50 minutes presentation

Overview: As artificial intelligence becomes an unavoidable presence in higher education, many educators find themselves uncertain, overwhelmed, or even resistant. This session offers a human-centred reflection on the journey from scepticism to strategic adoption of AI in teaching. Rather than focusing on the technicalities, this talk explores the emotional and cultural shift required to integrate AI meaningfully and ethically. With practical tips, real-world examples, and guidance on how to support hesitant colleagues, this session empowers attendees to foster curiosity, confidence, and community around AI in their institutions.

Speakers

Dr Ioana Mitea, Subject Liaison Librarian, Middlesex University London

Simbo Ajayi, Head of Peer-Supported Learning, Middlesex University London

Hrutuja Baikal, Senior Student Learning Assistant, Middlesex University London

Ionela Frigura, Senior Student Learning Assistant, Middlesex University London

Location: C122, 25 minutes presentation

Overview: The findings of our research on students’ use of AI tools conducted in 2024 indicated that more support and clarity were needed to increase students’ confidence and awareness in using AI for research and writing. Following on from this research, our session focuses on Student Learning Assistants (SLAs)’ and Librarians’ activities to guide students towards ethical and responsible AI integration in their academic work. We will present insights drawn from SLAs’ and Librarians’ experiences with supporting students. Both teams promote responsible AI practices through formal and informal interactions, facilitation and events, signposting students to sessions and resources while emphasizing the potential of AI for enhancing learning and research. Two of the presenters, Hrutuja Baikal and Ionela Frigura, are Senior SLAs and will contribute unique insights from their extensive practice supporting students from various programmes across Middlesex University Hendon campus. The session will be beneficial to colleagues from various disciplines by bridging perspectives on AI use, enhancing awareness of students’ perspectives, as well as promoting an inclusive pedagogy.

Speakers

Cariona Flaherty, Interim Head of Nursing & Midwifery, Middlesex University

Sue Bailey, Deputy Academic Registrar, Middlesex University London

Location: C122, 25 minutes presentation

Overview: Artificial Intelligence (AI) tools are increasingly accessible to students for academic writing. Last academic year, the Nursing and Midwifery Department noted a rise in referrals to the Academic Integrity Tutor (AIT) due to suspected AI use. While the mere use of AI doesn't inherently indicate plagiarism, some students had relied on it to compose significant portions of their written work, with a few using it to write entire essays. During viva examinations, it became clear that these students were unaware of the implications for academic integrity, especially concerning the Nursing and Midwifery Council (2018). In response, the department introduced training sessions during the induction for second- and third-year BSc Adult Nursing students. This initiative resulted in fewer AIT referrals and improved adherence to ethical AI use. Teaching students, the responsible use of AI will also better equip them for clinical practice, where AI integration is rapidly growing (Lane et al., 2024). This presentation aims to discuss the training initiative used within Nursing and Midwifery and offer insights to help academics in other fields adopt similar strategies.

Speakers

Dr Katerina Loukopoulou, Senior Academic Developer, Centre for Academic Practice Enhancement, Middlesex University London

Location: C133, 25 minutes presentation

Overview: "In the age of AI, oral presentations (vivas) have emerged as the proposed refuge for authentic assessment and academic integrity. Is Higher Education ready for this shift in assessment practices after centuries of academic ‘literacy’ equated with writing? This workshop will start with a brief presentation on debates about oracy in HE and on oral assessment variations (Heron et al, 2022). Participants will also have the chance to discuss and reflect on the influential framework produced by Oracy Cambridge in 2020. Moreover, alternative frameworks will be considered, by drawing on Ian Cushing’s (2024) critique of the ‘deficit foundations of oracy’. For example, sociolinguists have for long grappled with Noam Chomsky’s controversial notion of ‘negative data’ to categorise spoken communication that consists of ‘ill-formed sentences’. However, this workshop proposes to explore if so-called ‘negative data’ of spoken language might come of positive use in two fields of oral assessment:

1. to distinguish human agency from the seemingly perfectly-formed AI grammatic articulations and epistemologies;
2. to accommodate ‘oracy diversities’, resulting from neurodiversity and multi-lingualism. 

Through scenario-based activities and drawing on Middlesex case studies, participants will collaborate to explore inclusive and scalable models of oracy for the future of academic integrity. Participants are encouraged to engage with one of the resources before the workshop.

Speaker

Kate Vasili, LLB, LLM - Copyright Officer, Middlesex University London + Chair of the UUK and Guild HE Copyright Negotiation and Advisory Committee CNAC

Location: C133, 25 minutes presentation

Overview: The rapid advancement of artificial intelligence (AI) technologies has brought significant challenges and opportunities in the realm of copyright law. This presentation will explore the contentious debates and evolving legal landscape surrounding AI and copyright, focusing on the legislation in the United Kingdom and the possible impact of the current consultation on Copyright and AI, while also comparing the EU’s AI Act, and AI legislation in other key jurisdictions such as the US and Japan. The UK government’s goal is to achieve a fair balance between the rights of creators and creative industries, while also encouraging innovation and attracting AI developers to our shores. With the opposing sides so far from agreement, the only winners could well be the licensing bodies and large corporations. Universities are in a unique position in that their staff and students represent all stakeholders as both creators and users of copyright content in their substantive activities i.e. learning, teaching and research, research and development collaborations and knowledge transfer activities with universities and organisations both in the UK and overseas. Therefore, it’s crucial that the government strikes the right balance to avoid inadvertent negative impacts on key sectors like universities who also contribute considerably to the UK economy.

Speakers

Dr Phil Barter, Academic Director, Middlesex University Mauritius

Professor Danny Liu, Professor of Educational Innovation, University of Sydney

Location: C106, 25 minutes presentation

Overview: How do we assure and grow the value of our programmes and qualifications at a time of great upheaval and rapid change? In this session, we’ll explore practical strategies that are grounded in reality, to ensure the integrity and relevance of what, how, and why we teach and assess. Through the perspectives of our ‘two-lane approach’ to assessment design and a practical framework that focuses on establishing culture, rules, access, familiarity, and trust, we will discuss how to move from a mindset of policing the use of AI to thoughtfully engaging with its possibilities.

Hosted by:

Professor Kurt Bartling, Deputy Dean (Research and Knowledge Exchange) in Faculty of ACI, Middlesex University London

Location: C211

Panellists:

Dr Ellen Buck, PVC Education and Student Experience, Middlesex University London

Dr Charles Knight, Director, Leadership, Governance & Management, Advance-HE

Professor Rafe Hallett, Director of Learning and Teaching,  Middlesex University London

Camelia Purwanto, Head of Communications and Insights at Student's Union, Middlesex University London

Professor Tenia Kyriazi, Deputy Director Teaching and Learning, Law and Social Sciences, Middesex University Dubai

Dr Jim Graham, Deputy Dean: Education, Middlesex University London.