AI and Education Fellows: Dr Jillian Terry and Dr Chris Blunt

Being able to introduce so many first-year students to Claude has been really valuable, helping students to develop their AI literacy and expertise that they can take into the rest of their courses and experiences while at the School

Dr Jillian Terry, Associate Professor (Education) and LSE100 Co-Director

Overview    

Jillian and Chris are integrating and providing scaffolded support for the optional use of LLMs across LSE100, the School’s flagship interdisciplinary course taken by all LSE undergraduates (approximately 2,000 students each year). The work focuses on embedding AI in ways that aligns with LSE100’s flipped-class model, supporting inclusive teaching and building students’ critical AI literacy. 

What have they been using AI for so far?   

In Autumn Term 2025, Chris and Jillian introduced Claude as an option within the interdisciplinary commentary assessment. Students could choose to conduct the conversation component of the assessment with Claude, which role-played as an interview partner from another discipline.  

Around 300 students (15%) chose the Claude option, demonstrating stronger than anticipated uptake. 

Wider plans for AI integration 

Seminar preparation and flipped learning:  

They are designing seminar preparation activities links to course worksheets, supported through  shared access to a Claude project (for example, a Weekly seminar prep Claude project).

Students use Claude to check and consolidate their understanding of key concepts from the slides before each seminar. This approach supports LSE100’s flipped classroom model by enabling students to engage with core ideas ahead of class and use in-person seminars for higher-order, collaborative work.

It is particularly beneficial for students who feel less confident contributing in seminars, allowing them to build understanding and confidence before attending.  

AI-assisted interdisciplinary research tasks 

Chris and Jillian are also exploring how LLMs can support AI-assisted interdisciplinary research tasks, particularly during the early stages of the group project.  

Planned examples include: 

  • A Claude artefact to support reading and division of key texts across the groups ahead of their first seminar, helping students develop AI-supported reading practices.  

  • A second artefact to support preparation for the next seminar by guiding students in using Claude to research and refine their group’s focus problem or research question.  

They see these tools as part of a wider menu of learning support available throughout the group project, potentially extending to idea generation and development, exploring disciplinary perspectives, stress-testing proposals for change, and rehearsal for group presentations. 

These ideas are current at an early stage of development, with a view to potential implementation for the 2026/27 cohort.  

Redesigning group projects   

LSE100’s flipped classroom model is particularly well suited to using LLMs to support autonomous learning while freeing up in-person time for collaboration. As part of a wider redesign of the group project, Jillian and Chris are embedding activities that build students’ critical skills in working with LLMs, including:  

  • curating reference materials for a shared Claude Project  

  • using Claude to extend on visualisations created by groups in seminars (e.g. systemic risk maps, radar chart diagrams)  

  • critically verifying AI-generated outputs   

Lessons learned and next steps

Reflecting on their work so far, Jillian highlights the value of exposing students to Claude’s features beyond the standard chat interface, particularly Artifacts and Projects which have proven more versatile than expected. 

For Chris, the most significant success to date has been the AI-enabled conversation pathway:  

"It was interesting to see this being more popular than expected with students, with 15% taking up that option."

Read about the work of the other LSE AI and Education Fellows