Centre for Engineering Education Blog

Tag: Generative AI

  • Attitudes Towards Generative AI: A Study with First-Year Computer Science Students

    Varvara Papazoglou is a Teaching Associate in the School of Computer Science, University of Sheffield. In this post Varvara shares the work she led to investigate student perceptions of AI that found growing confidence, excitement and acceptance. The work was presented at the 18th annual International Conference of Education, Research and Innovation (ICERI 2025).

    The study started during the academic year 2023-24 and was intended to track how the perceptions, expectations, and technical understanding of our undergraduate students shifted as they gained direct experience with GenAI technologies. With a team that included Alex Lucas and Prof. Rob Gaizauskas, we redesigned the first two lab sessions for a first-year module called Machines and Intelligence so that they included a practical introduction to Generative Artificial Intelligence (GenAI). Our study spanned two academic years, and tracked how the perceptions, expectations, and technical understanding of students shifted as they gained experience with GenAI technologies . To measure this, we invited volunteer participants from both cohorts to complete two online surveys, one before and one after engaging with the GenAI-focused curriculum of the module.

    Students on laptops in a classroom setting

    These questionnaires were administered three to four weeks apart, using unique IDs to match participant responses while preserving their anonymity. Structurally, they consisted of 13 core questions common to both iterations. Questions identified the specific GenAI tools students utilised and their typical purposes for doing so with, and 5-point Likert scales were used to evaluate viewpoints on GenAI’s performance, the identification of AI-generated content, and general feelings of excitement or concern. The perceived impact of AI on future careers, potential job obsolescence, and the ethics of GenAI use in university and workplace settings were explored. To ensure a comprehensive analysis, most of these questions included non-mandatory open-ended sections for qualitative insights, concluding with a final opportunity for participants to offer additional comments.

    Testing Turing

    The first lab focused on a practical adaptation of the Turing Test.

    Turing Test Diaghram

    Students were split into groups of 6-7, paired with another group to play the roles of “interrogator” (C in Turing’s original formulation) and “interrogated” (both A (the man) and B (the woman/machine)) interchangeably.

    To maintain anonymity and remove visual cues, all communication happened through a shared online document. The “interrogated” groups were tasked with choosing whether to provide the answers of an actual team member or to use ChatGPT or Gemini to produce human-like responses. The latter required students to act as prompt mediators; for example, they might instruct the model to adopt the persona of a 20-year-old first-year computer science student while keeping answers within a specific word count. This exercise forced students to grapple with the actual capabilities and flaws of these models. For their assessment, students submitted reflections on the following:

    ●      As interrogators, whether they successfully identified the machine and what specific linguistic cues or mistakes led to that conclusion.

    ●      As the interrogated group, whether they successfully deceived the interrogators into making the wrong identification, and whether this success was attributed to the AI’s capabilities or their own careful prompt engineering or other factors.

    ●      Whether the Turing Test remains a valid benchmark for machine intelligence, based on their experience with the given task.

    The second lab shifted towards the ethical and practical implications of AI in Higher Education. After reviewing online University resources regarding guidelines and policy on the use of GenAI, students analysed and critically evaluated 10 short descriptions of use cases on GenAI in Higher Education, split into two groups of five, involving use by educators and five use by students, ranging from AI-generated lecture content to code authoring with GenAI.

    Groups debated the advantages and disadvantages of these scenarios, helping them develop an informed, critical perspective on how to use these tools responsibly throughout their degree.

    Confidence, Excitement and Acceptance

    Students working on a drone

    To understand how these labs changed perspectives, we conducted pre- and post-task surveys, analysing 33 matched responses from the 2023-24 and 2024-25 cohorts. The results revealed the following in student literacy:

    ●      Initially, students were fairly confident that GenAI could handle complex tasks. After the labs, this confidence actually dropped (from an average of 3.8 to 3.5 on a 5-point scale), suggesting that students gained a first-hand understanding of the inherent “hallucinations” and limitations.

    ●      Student confidence in their ability to identify AI-generated content (based on cues such as unnatural or “over-polished” text) rose slightly, from an average of 3.2 to 3.5. Overall, as indicated by their responses to our survey questions, most participants had some experience and a good understanding of cues that can reveal GenAI output before our teaching interventions. However, among participants with no prior experience, greater confidence in recognising AI-generated material was observed.

    ●      Interestingly, despite becoming more aware of the risks, students’ willingness to use GenAI in their studies increased (from 3.7 to 4.3). In addition, in their comments, students emphasised that, because GenAI tools and technologies are here to stay, the priority must be acceptance and education, so people are aware of how to use them effectively to maximise utility while minimising risk.

    ●      While the media often portrays AI as a threat to jobs, our students largely viewed it as a transformation. Many saw the obsolescence of certain tasks not as a negative, but as an opportunity for new roles and increased productivity. Interestingly, students expressed similar feelings of excitement and acceptance for GenAI use in both Higher Education and the workplace.

    Computer image of a face with letters coming out of it
    Conclusion

    Our findings suggest that early, structured engagement with GenAI, tied to subject-specific material, can foster more balanced and informed perspectives among students. Students with more awareness of risks and limitations seem to be more optimistic of the impact and potential of GenAI. However, we are mindful of the modest scope of our current research. Given the relatively small sample size and the specific context of our introductory module, these results serve as preliminary insights rather than definitive conclusions. We have identified areas for improvement, particularly in deepening students’ awareness of ethical and societal risks while reducing the likelihood that students feel overly confident about their ability to identify and manage AI-generated content without necessarily being aware of the full range of risks.

    Varvara Papazoglou is a Teaching Associate in the School of Computer Science, University of Sheffield. Her research interests include Artificial Intelligence, Music Information Retrieval, Computational Linguistics and Natural Language Processing, as well as Educational Research in Computer Science.

    When citing this work, please use the following citation:
    Papazoglou, V. (2026). “Attitudes Towards Generative AI: A Study with First-Year Computer Science Students” Centre for Engineering Education Blog, The University of Sheffield, Sheffield, UK. June 2026.     https://ceesheffield.co.uk/2026/06/09/attitudes-towards-generative-ai-a-study-with-first-year-computer-science-students/

  • Engineering and Teaching Shorts: Keeping CPD Bite-Sized and Impactful

    Michael Trikić explores how Engineering and Teaching Shorts (EATS) provides informal, accessible professional development for academic and professional services staff at the University of Sheffield. Established to encourage the sharing of teaching ideas and practical experience, the programme covers topics ranging from inclusive teaching and student wellbeing to digital skills and generative AI. The blog looks at how EATS responds to staff interests, works with the Centre for Engineering Education (CEE), and supports small changes in teaching practice through discussion, collaboration and shared learning.

    In Higher Education time is always in short supply, so finding space for meaningful professional development can be a challenge. That’s where Engineering and Teaching Shorts (EATS) comes in: a bite-sized, informal Continuing Professional Development (CPD) series that makes space for reflection, inspiration, and conversation, all over a buffet lunch.

    Led by Michael Wright, Faculty Education Advisor for Engineering, EATS offers a practical and engaging route into continuous learning for both academic and professional services staff. “It’s very much not a one-size-fits-all message,” Michael explains. “You’re not being told to do X or Y.” Instead, sessions are built around shared stories and practical examples designed to spark new ideas in day-to-day teaching.

    What is EATS? A format that sticks

    EATS is a CPD initiative established in the early 2010s by Professor Stephen Beck, here at the University of Sheffield. It was created to encourage peer-led development through practical sessions that highlight different approaches to teaching and learning, and since inception over 200 have been held.

    University of Sheffield staff attending an EATS session

    Sessions are shaped around key themes in engineering education, from inclusive design and mental health support to generative AI and feedback strategies, and led by a mix of internal and external speakers.

    What sets EATS apart is its format. The programme is intentionally flexible, welcoming, and non-prescriptive, a structure that encourages ideas to circulate without pressure. “It’s informal,” Michael says. “You can engage as much as you like. You can sit at the front and ask questions… or just quietly absorb what’s going on.”

    How Topics Are Chosen: A Finger on the Pulse

    While some themes, such as mental health, international student support, or library updates, are recurring staples in EATS, the wider calendar is shaped by what’s current, timely, and useful to staff. Michael draws inspiration from university education conferences, listening for topics that spark discussion across faculties, and often invites speakers to adapt and re-share presentations for the engineering context.

    University of Sheffield staff attending an EATS session

    This responsive model ensures that EATS stays relevant. Some sessions are prompted by sector-wide developments, like the introduction of Blackboard Ultra or the growing interest in generative AI.

    Others respond to quieter but meaningful shifts. For instance, after noticing staff concerns about students’ digital readiness, Michael invited colleagues from the 301 Academic Skills Centre to showcase training resources in tools like Excel, helping staff to meet students’ digital training needs.

    Ideas also emerge from informal channels. Conversations with colleagues and staff simply asking, “Could we have a session on this?”. That mix of structured insight and on-the-ground curiosity allows EATS to remain grounded in real teaching needs while reflecting broader trends in higher education. If you have any ideas for sessions, get in contact with Michael.

    Collaboration with CEE

    The collaboration between EATS and the Centre for Engineering Education (CEE) allows ideas from conferences and faculty projects to circulate more widely, with EATS sessions used both for sharing insights and testing new material.

    EATS sessions are also used to support both preparation for and reflection on conference participation. Staff who receive CEE funding to attend events are often invited to share their insights afterwards. For example, Professor Emma Norling shared her reflections from the Innovation and Technology in Computer Science Education (ITiCSE) conference with colleagues while Dr Michael Trikić used his inclusive engineering session to gather examples and refine his talk ahead of presenting at the SEFI conference.

    The initiative has also offered space for experimentation. A recent hybrid session on generative AI brought together staff from The University of Sheffield and University College Dublin, with both groups gathered in their respective locations and linked via video call—the first of its kind for EATS. “That was a really nice way to broaden the remit and deliver something engaging,” Michael said.

    The Impact: Small Bites, Big Shifts

    EATS sessions have prompted meaningful changes in teaching practice, from day-to-day adjustments to broader shifts in mindset. Staff shared their approaches to effective assessment in a well-attended EATS session, Assessment and Feedback at Scale. The following year, student feedback on that area improved in the NSS—a change Michael sees as “one of the contributing factors that maybe helped.”

    Sessions on cultural awareness and name pronunciation have also had a practical impact, especially in preparation for student-facing events like graduation. Staff have reported feeling more confident supporting international students and recognising the value of small details, such as learning how to pronounce Chinese names correctly.

    Others have taken away tools they can apply immediately. After attending a generative AI session, one staff member began using Google Gemini to assist with writing tasks, a tool Michael himself has adopted in his work. Sessions on student wellbeing have also helped staff feel better equipped to signpost mental health support and recognise when to seek help on a student’s behalf.

    Through these small but cumulative changes, EATS continues to shape a more responsive, inclusive, and thoughtful teaching environment. One practical session at a time.

    Citation:
    Trikic, M. (2025). “Engineering and Teaching Shorts: Keeping CPD Bite-Sized and Impactful” Centre for Engineering Education Blog, The University of Sheffield, Sheffield, UK. November 2025. https://ceesheffield.co.uk/2026/10/29/engineering-and-teaching-shorts-keeping-cpd-bite-sized-and-impactful/