University of Greenwich Journals and Working Papers
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Pausing to Be Human in the Neoliberal University: Relational Pedagogy and the Politics of Presence
No full textWhen higher education is increasingly driven by metrics, efficiency and performative productivity, what does it mean to pause, to slow down, to feel... to be, simply, human? This opinion piece explores how relational pedagogy, grounded in presence and affect, offers a quiet but powerful form of resistance within the neoliberal university. Drawing on recent research and practice, I argue that pausing is not a retreat from the demands of academic life, but an intentional pedagogical act, one that re-centres connection, care and co-presence in our teaching and learning environments. In doing so, we begin to reimagine not only how we teach, but what kind of academic cultures we wish to cultivate
FYiMaths (First Year in Mathematics) New South Wales 2024 Meeting Report
No full textThis article provides a report of the recent First Year in Mathematics New South Wales (FYiMaths NSW) meeting held in Sydney, Australia, in December 2024. Nine talks were presented, with an overall theme of, How should we teach and assess maths and stats to improve student outcomes? An overview and background of FYiMaths and the recent FYiMaths is provided, followed by a summary of each of the nine talks presented at the meeting. Finally, a summary of the day is provided which includes emerging themes, key takeaways and lessons learned
Designing the Student Learning Journey: A Practical Approach to Integrating Generative AI within Higher Education
No full textGenerative AI technologies are reshaping higher education, transforming how students access knowledge, engage with learning, and complete assignments. While institutional responses have largely focused on academic integrity and assessment security, this paper argues for a proactive, programme-level approach that embeds generative AI thoughtfully and ethically across the student learning journey. Drawing on examples from the mathematical sciences, it presents a practical framework to support curriculum teams in aligning AI use with programme outcomes, disciplinary values, and assessment design. Key recommendations include designing progression from foundational to advanced AI-supported tasks; fostering coherent, programme-wide expectations for ethical and transparent AI use; and developing students’ critical AI literacy as a core graduate attribute. The paper also highlights the importance of equitable access to tools, respecting disciplinary contexts, and rethinking assessment formats to promote higher-order thinking. A programme-level checklist is provided to guide planning and implementation. By integrating generative AI with intentionality, institutions can move beyond reactive policies towards learning environments that prepare students for a future in which human and AI capabilities will increasingly work in partnership
Student and staff expectations of university life - a pilot study.
Full text linkStudent expectations of university lack clarity, yet unmet expectations may negatively impact upon satisfaction, attainment and progression. This questionnaire-based pilot study explored student and staff expectations, in a large English widening participation university. In all, 65 students and 27 staff participated. Most notable was the similarity of student responses regardless of demographic characteristics. However, students already in paid work were significantly more likely to agree that they liked the university and found it easy to make friends. Students who might consider taking on paid work expressed significantly more concern that they may struggle with their academic work whilst those not in paid work had significantly more concerns about exams and self-directed learning. In terms of transferable academic skills, Black students were significantly less likely than white students to expect to make detailed class notes for themselves, albeit within this small sample size, while those first-in-family identified more academic skills needs than other student groups. Significantly more staff than students considered classroom attendance necessary. This pilot study suggests future research directions, including the impact of paid work and ethnicity on specific academic skills and underlines the importance of student support.
Using Generative AI to help with statistical test selection and analysis
Full text linkOne of the most common questions that students ask statistics advisors is ‘What test should I do?’ This paper explores the use of generative AI chatbots, specifically ChatGPT, as a tool to assist students, in particular those with limited experience in statistics, in selecting appropriate statistical tests for their analyses. Traditional methods, such as flowcharts and online test selectors, require at least a basic understanding of measurement scales and research design, which can be an issue for many students who have limited exposure to statistics on their courses. This research focuses on developing and refining prompts to guide ChatGPT in providing accurate and relevant statistical test recommendations. A hypothetical scenario was used to test the effectiveness of various prompts, ranging from simple, naïve questions to more sophisticated ones utilising specific prompt patterns, such as the ‘context manager’ and ‘flipped interaction.’ These patterns were selected to enhance the chatbot’s responses and ensure the relevance and accuracy of the test suggestions. The findings suggest that while AI chatbots like ChatGPT can be a valuable resource for students, their effectiveness is highly dependent on the quality of the prompts used. The paper concludes with a discussion on the potential of these AI tools in educational settings, acknowledging the limitations of current technology and suggesting directions for future research and development
Generative AI in Assessment: Towards Understanding the Student View
Full text linkThis case study reports on an intervention that took place within a second-year mathematics module at a higher education institution in the United Kingdom. Prior to completing an essay, students were supported to understand potential benefits and risks of using Generative AI to aid their process. Students were allowed unpenalised use of Generative AI to complete this assessment. They were interviewed to gain an understanding of how they used this technology, and their perceptions of it. A small sample (n=3) allowed for in-depth exploration. All participating students reported using Generative AI in ways which developed their critical awareness of the technology, and the authors believe that the overall value of the assessment to students was enhanced. The case study ends with recommendations for integrating Generative AI into assessment, and directions for further study in this rapidly developing field
What role does Skill Centre based consultancy serve in mathematics and statistics teaching communities of practice?
Full text linkMathematics and Statistics Teaching (MAST) is a staff facing service set up by the University of Bath Mathematics Resource Centre in September 2021. The service was created to collaborate with academics involved in mathematics and statistics teaching in their academic departments. In September 2023, MAST ended its pilot phase and entered a new growth phase fine-tuning existing structures and practices. During the pilot phase, MAST worked with academics consulting on enriching their programme of study and/or teaching practices. Specifically, the key principle that guides MAST is engaging in long-term sustainable collaborations with academic departments. As a means to address the key principle, we explore the potential of building communities of practice and supporting a wider network across the range of disciplines who encounter similar objectives. Facilitating a wider community of practice could be challenging, especially considering the tight schedule of the academics involved. We discuss our plans to cultivate communities of practice within departments and how we are working towards meeting our goal of establishing best practice and collecting evidence to support a wider community
Toward a holistic approach to mathematics support at Munster Technological University’s Academic Learning Centre
Full text linkThis case study outlines plans for a revised approach to mathematics support at Munster Technological University’s Academic Learning Centre. Under this proposed approach, mathematics support – delivered both on a one-to-one basis and in group settings – is to be supplemented by and integrated with learning supports offered by the Academic Learning Centre’s sister programmes, Academic Success Coaching and Navigate Learning Development. This new approach will see the three programmes brought together under the Academic Learning Centre name. In implementing this approach, we have two key objectives: firstly, to determine the impact of this integrated approach on our mathematics support service and on its users – particularly those displaying traits of mathematics anxiety – and, secondly, to assess the extent to which presenting students with one integrated support option may result in increased service access and use
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