Bristol Institute for Learning and Teaching

My interest in this theme comes from being a student during a period when AI has become part of everyday conversations about university work. In subjects like economics and mathematics, working through a problem is often where much of the learning happens. An answer can look straightforward when someone else explains it, but understanding why each step works, and being able to apply it elsewhere, is a different challenge. That makes me curious about how assessment can capture students’ understanding when tools can produce convincing answers so quickly.

Before coming to Bristol, I worked as a Responsible AI Intern at Sheffield’s Centre for Machine Intelligence. I compared approaches to AI governance across public sector organisations, exploring how they were responding to the opportunities and challenges these technologies bring. Although the context was different, it left me interested in questions that also matter in education: what does responsible use look like in practice, how do we communicate expectations clearly, and whose experiences are considered when decisions are made?

I’m looking forward to exploring these questions from a student perspective at BILT. I’m particularly interested in the distinction between using AI to support learning and using it in ways that bypass the learning itself. How can assessment encourage students to question, interpret and explain what they produce? How can we make room for useful applications of AI while ensuring that students develop the knowledge and judgement they will need beyond university?

My experiences as an Academic Representative and a Teaching Assistant at Sheffield also contributed to my interest in this role. Listening to students and supporting undergraduate workshops gave me different perspectives on learning, alongside my own experience of being assessed. As an international student, I’m also aware that students arrive with different educational backgrounds and expectations. I’d like to understand how those differences shape their confidence in navigating AI guidance and assessment requirements.

During the year, I hope to hear from students across disciplines about how they use AI, what they find helpful, and where they feel uncertain. I’m keen to explore assessment approaches that give students opportunities to demonstrate their reasoning, apply their knowledge and reflect on their choices. I also want to understand what makes an assessment feel meaningful to the person completing it, and how students can contribute to its design.

Outside my studies, I enjoy poker, which fits quite well with my interest in decision-making and uncertainty! I’m also looking forward to exploring Bristol and getting to know people beyond my course.

I’m excited to work with the BILT team and the other Student Fellows this year. If you have thoughts about AI and assessment, or experiences you’d like to share, I’d love to chat!

Connect with Samita on LinkedIn.