By Keith Taynton (Learning Technology Support Officer)
In the ever-changing world of the Higher Education sector, Artificial Intelligence (AI) is no longer a futuristic fantasy; it’s rapidly becoming a present reality. Yet, for many of us in academic life and professional services, the initial reaction is often a blend of curiosity and caution. Is AI a revolutionary tool, or a potential disruptor to be wary of? If you find yourself still on the fence, wrestling with these questions, you’re not alone!
Meet Rosemary, an academic colleague here at Derby, who by her own admission, started her AI journey as a staunch sceptic. She wasn’t one to jump on the early curve of adoption, confessing to initial feelings that AI was “a bit dodgy, a bit scary.” This honesty resonates with many of us who approach new technologies with a healthy dose of apprehension, particularly those tools and platforms that have the potential to be disruptive and even perhaps threaten academic integrity. But Rosemary’s journey is a compelling one, because it charts a path from initial scepticism to becoming a daily AI user, and it offers valuable insights into how AI can genuinely enhance academic productivity and even reshape our approaches to teaching and learning.
So, what transformed Rosemary’s perspective? It wasn’t grand pronouncements about the future digital landscape or abstract pedagogic theory, but practical experience. She began exploring AI, specifically Microsoft Copilot, to tackle everyday academic challenges, and the results surprised her. Firstly, Rosemary ventured into the often- time intensive realm of qualitative data analysis with AI in mind. Thematic analysis, while intellectually rewarding, can be incredibly time-consuming. Intrigued, she decided to experiment, feeding anonymised interview transcripts into Copilot and asking it to identify emerging themes. The outcome was striking. AI identified themes that aligned with her own analysis, offering a reassuring validation of its capabilities. But even more interestingly, it also presented these themes with slightly different perspectives, akin to having a fresh eye on the data. “It was almost like having a colleague working on it with me” Rosemary observed, capturing the collaborative feel of using AI in this way. It wasn’t about replacing her analytical skills but augmenting them with a digital partner capable of offering a new lens on complex information.
In everyday life as an academic, the quest for the perfect reference and paper is a familiar one. We’ve possibly all experienced that frustrating moment of knowing a paper exists, remembering the authors and general topic, but the title and how to find it remains elusive. Rosemary discovered that AI excels at this too. By inputting authors, approximate date, and subject matter, Copilot began to locate references. She jokingly likened it to a “hyped up librarian,” referencing its speed and efficiency in source retrieval. This seemingly small task, when streamlined by AI, frees up valuable time and cognitive energy for more demanding professional pursuits.
Perhaps one of the most universally relatable struggles to anybody that has to draft documentation is the dreaded blank page. Whether it’s planning a new lecture, writing a research proposal, or tackling the rationale for a new project, that initial inertia can be hard to overcome. Rosemary found AI to be an effective antidote to this creative/writer’s block. Instead of staring blankly at the screen, she began using AI as a starting point, posing questions and prompting it to generate initial ideas. “AI is a great starting point to actually give you those ideas rather than staring at the flashing cursor on a blank piece of paper,” she explained. It’s not about outsourcing creativity, but jumpstarting the process, providing a springboard for original thought and development.
Rosemary’s journey is more than just a list of use cases; it’s a story of an evolving perspective. She moved from initial apprehension to recognising AI as a powerful tool to enhance, not replace, human academic work. She now integrates AI into her daily routines, appreciating its ability to handle administrative tasks and free her up for the more creative and intellectually demanding aspects of her role. Crucially, she maintains a balanced approach which emphasises the continued need for human oversight and critical evaluation. “There’s still, I absolutely think, the need to check all output, because obviously we can’t trust it totally at this moment in time,” she wisely points out. AI is a powerful ally, but human expertise and judgement remain more essential now than ever.
Looking ahead, Rosemary is thoughtfully considering how to integrate AI into her teaching. Rather than fearing AI as a potential source of negative disruption, she sees it as an opportunity to develop crucial 21st-century skills in her students. She’s adapting assignments, not to avoid AI, but to encourage critical engagement. For instance, she envisions students using AI to generate infographics, but then critically evaluating these AI-created outputs as visual essays. “How would you improve it? … critically evaluate, is it correct or not?” she prompts, pointing out the importance of developing critical thinking skills in our students. She understands that in a world increasingly shaped by AI, our students need to be not just confident users of AI platforms, but discerning and analytical graduates.
Rosemary’s journey offers a compelling and practical roadmap for her colleagues at Derby. It’s a reminder that AI, when approached with thoughtful experimentation and a critical eye, isn’t a threat, but a powerful ally and critical friend. It’s a tool that can genuinely enhance our productivity, enrich our research, and empower us to prepare our students for a future where AI literacy is not just a ‘nice to have’, but a core graduate skill. Perhaps, like Rosemary, it’s time for us all to move beyond our initial scepticism and explore the unexpected practical ways AI can support and enhance our work in higher education. What small step will you take today to explore the potential of AI in your professional life?
Important note for colleagues at the University of Derby
Use of AI for qualitative data analysis, e.g., summarising interview transcripts, should be considered as part of the ethical approval of your research, see Use of Gen AI and Research Ethics Applications. Microsoft Copilot is within the University digital infrastructure and therefore has greater protection of your data. For example, your data entered into this service will not be used to train their foundation models. Working within the University infrastructure provides protections; however, the basic principles of the University data protection policy still need to be applied as would be the case for all other University systems, alongside appropriate research ethics.