Summary

This case study explores how Generative Artificial Intelligence (GenAI) can be embedded into legal education through structured classroom debates that position the AI as a live debating opponent. The rationale for this approach is grounded in the need to develop law students’ digital capability, critical reasoning, and professional adaptability in response to rapid technological change. Drawing on pedagogical principles of constructive alignment and experiential learning, the design requires students to prepare arguments independently, engage in real-time debate against a GenAI opponent, and reflect critically on the process. Student feedback indicates that this format increases engagement and confidence, while also sharpening awareness of both the strengths and limitations of GenAI in legal reasoning. The model demonstrates clear potential for scalability across disciplines, alignment with institutional digital capability agendas, and sustainable integration into curricula. By linking individual classroom practice with broader strategic goals, the contribution highlights the value of GenAI not only as a teaching tool but as a means of preparing students for a technology-driven future in professional practice.

Introduction

ChatGPT, a Generative AI chatbot developed by OpenAI, is introduced into law seminars to foster active learning through structured debates. In small groups, students are tasked with developing arguments around a legal topic. This first stage allows for collaboration in preparing arguments without the use of GenAI. Once the preparation phase concludes, the entire seminar discusses and prioritises arguments. Oros (2007) identifies seminar debates as a learning method, using the term ‘structured classroom debates’ (SCDs), and explores how this is a valuable method for developing critical thinking. SCDs promote an inclusive classroom by encouraging contributions from a wider range of students, rather than relying on students who typically lead discussions. This case study builds on SCDs by introducing GenAI. Once prepared, the next stage involves the lecturer launching ChatGPT, visible on screen, and providing an introductory briefing of the technology to the seminar. While many university students use GenAI – as many as 88% have used it in some form, according to Freeman (2025) – it is important to ensure that those encountering the technology for the first time have some understanding of GenAI. The lecturer starts the debate by presenting ChatGPT with a prepared prompt that positions the GenAI as an opponent to the students’ prepared arguments.

The intervention

To provide authenticity and deepened engagement, ChatGPT is enabled with voice activation (samples of these voices are available on the OpenAI (2023) product page). After a formal opening statement by ChatGPT, the lecturer assumes the role of facilitator, feeding student arguments to ChatGPT. This real time dialogue creates a dynamic environment that mimics the unpredictable nature of legal advocacy. Zhou (2023) supports the idea that AI is increasingly acknowledged for its ability to stimulate creativity, with growing pressure to incorporate technology into teaching methods to better prepare students for success in an interconnected and globalised world (Khalid, 2018). The responses provided by ChatGPT play a crucial role in reinforcing the principles of active learning. Students are challenged to defend their positions against a GenAI opponent, adapt their reasoning, and assess the strengths and weaknesses.

After the debate concludes, the class participates in structured reflective sessions, first in small groups and then individually. These sessions are designed to encourage deeper analytical thinking and critical self-assessment along with evaluation of the GenAI technology.

The rationale behind integrating GenAI into legal debates is supported by Coles (2009) who argues that the use of digital tools in legal education enhances interactive learning experiences and deepens student engagement. Similarly, Zhou (2023) emphasises that GenAI can stimulate creativity in legal environments. By introducing ChatGPT as an active debate opponent, this approach aims to provide students the opportunity to refine their arguments, adapt their reasoning in real time, and evaluate GenAI outputs.

The real time nature of the debate, with its need for spontaneous rebuttals and critical analysis, reflects the dynamic environment in which legal practitioners operate. It demands not only a deep understanding of legal principles but also the ability to adapt quickly to evolving arguments. O’Leary (2020) advocates for the integration of technology into traditional legal assessments, arguing that such innovations prepare students for the realities of a technology-driven legal landscape. The approach is informed by pedagogical theories such as Biggs’ (2003) constructive alignment and Kolb’s experiential learning theory (Kemp, 2016). These theories assert that learning is most effective when educational activities are directly aligned with the desired learning outcomes and when students are actively involved in the learning process. A debate format, enhanced by the integration of GenAI, applies both these principles by requiring students to construct, defend, and refine their arguments in a manner that simulates (to some extent) the skills of legal practitioners.

Guo (2023) introduced a debate approach using GenAI to support students in generating arguments. Guo’s method had three stages: students first used the chatbot Argumate to generate ideas, then discussed them with peers, and finally debated against other groups. While students effectively generated ideas in the initial phase, they did not consistently incorporate the chatbot’s suggestions later. Despite this, they responded positively, appreciating its ability to spark ideas, create engagement, and offer a low-pressure learning environment. This case study takes a different approach by positioning GenAI as an active debate participant rather than a preparatory tool. While both methods enhance critical thinking, they differ in execution and student interaction with GenAI-generated content. In Guo’s (2023) model, debates remain student-led, with GenAI playing no direct role beyond preparation. The study found that students often failed to integrate GenAI-generated ideas into live debates, suggesting a disconnect between preparation and performance. By contrast, this case study uses a structured debate model which introduces ChatGPT only during the live debate, ensuring students independently develop arguments before encountering GenAI-generated counterarguments.

Student feedback

Ethical approval for the use of student evaluation data, granted by the University Ethics Panel (Application No. 7583), allows for the inclusion of feedback from students. Students expressed positive feedback, demonstrating the value of integrating GenAI into the seminar. They noted that the presence of a GenAI opponent removed some of the social pressures associated with traditional debates. One student remarked, ‘It was really cool, definitely something different from the usual seminars.’ Another reflected on the GenAI’s performance, stating, ‘I was actually impressed by how well it debated, it made some good points.’ Others commented on the realism of the experience, with one noting, ‘The voice was really clear; it actually sounded like a person.’

However, students recognised the limitations of the GenAI, with one observing, ‘At times, it clearly didn’t get what we were arguing, but it was fun to challenge it.’ Despite these moments, students found the exercise beneficial for developing confidence in their debating. As one said, ‘Initially, I wasn’t a fan of debating an AI, but it really pushed us to articulate our points better.’ Another student reflected, ‘The AI’s responses were well organised, yet it struggled to apply legal principles with any real depth.’ The exercise allows for critical comparisons between human and GenAI reasoning. One student noted, ‘While ChatGPT could generate responses quickly, it failed to apply the point in the way a human would.’ Another student stated, ‘ChatGPT was good at coming back with counterarguments quickly, which made me think on my feet more.’

Students were critical, saying, ‘At times, the AI’s responses felt generic, requiring me to reframe my argument so it understood the point.’ This recognition of GenAI’s limitations contributes to the student’s digital skill development. Another student reflected, ‘Debating against ChatGPT made me more aware of how I construct arguments and helped me be more concise.’ Beyond individual skill development, the debate experience encouraged broader reflection on GenAI’s role in legal practice. One student observed, ‘This made me consider how it could be used in a law firm, to help speed up work, but it still lacks the ability to apply legal judgment in the way a human would.’

Inclusivity, sustainability and transferability considerations

This case study is an example of active learning in practice. Unlike traditional teaching, which can isolate students to the role of passive listeners, the debate format places students at the centre of the learning process. While no different to typical debates, the added element of GenAI develops digital skill, awareness of GenAI technologies, and helps to mitigate social pressures, creating a more equitable platform for participation. Unlike traditional debates, where more dominant speakers may overshadow others, the GenAI does not exhibit this style. One student observed, ‘The AI doesn’t judge; it simply responds. This made it easier for everyone to speak up.’ This demonstrates an opportunity to start a discussion on the use of GenAI and to what extent this technology is biased.

Zare (2013) argues that debate methods accommodate students with differing learning preferences. This case study builds on this, catering to diverse learning preferences by combining visual elements (projected GenAI responses) with auditory inputs (voice activation) with the initial stage of debate preparation in groups and the final stage of structured reflection. This multi-staged approach ensures that students with different learning preferences can engage with the learning effectively. By fostering an environment where students feel capable of contributing, the approach enhances overall classroom inclusivity.

The United Nations (2025) Sustainable Development Goals, a set of 17 global targets established in 2015 aimed at addressing environmental, social, and economic challenges, link to this teaching method which is achieved pragmatically through its low resource requirements and inherent adaptability. Once the necessary GenAI infrastructure is established, tools like ChatGPT can be integrated with minimal additional costs, indeed many universities have explored alternatives such as Microsoft CoPilot or Google Gemini (Nikolic, 2024). From an environmental perspective, the energy impact of GenAI is consciously minimised in this design, as only the educator interacts with the tool during preparation and facilitation, rather than multiple students querying the model individually. Institutional sustainability is further reinforced by the continuous feedback loop established between students and staff. Evaluations and reflective sessions provide valuable insights that can be used to refine the approach over time. Beyond individual seminar practice, this approach aligns with wider institutional digital capability agendas by embedding structured, reflective use of GenAI into teaching. The debate format itself is highly adaptable; it can be incorporated into multiple modules within a legal curriculum and tailored to different educational contexts, where debates are utilised. This develops students’ digital skills in line with institutional strategies for employability and digital literacy. Educators in fields that rely on SCDs, critical discussion, or real-time problem solving can modify the approach to suit their own seminar learning objectives (Brown, 2016). For example, in business, the model could simulate negotiation scenarios; in philosophy or ethics, it could present opposing viewpoints on moral dilemmas; and in political science, it could be used to debate public policy proposals (Omelicheva, 2007).

Concluding remarks

This case study demonstrates that integrating GenAI into SCD is a viable and effective approach to active learning. By combining traditional legal argumentation with innovative digital engagement, this method transforms the classroom into an interactive, inclusive, and sustainable learning environment. The approach contributes to a student’s analytical capabilities and helps prepare them for a technology-driven future in legal practice. Feedback from students indicates that the method offers advantages over established SCD techniques. The use of GenAI helps to mitigate social pressures and creates a more equitable space for participation. The sustainable nature of the approach, stemming from its low resource requirements and inherent adaptability, further reinforces its potential for long term institutional integration. As digital technologies continue to evolve, so too must our approaches to teaching and learning (Haleem, 2022). Integrating tools like ChatGPT into the educational process represents a promising step towards a more dynamic, inclusive, and sustainable academic future.

Key takeaways

• Engaging with AI in debates fosters critical thinking, legal reasoning, and digital skill development.
• This method is scalable and adaptable across disciplines.
• Ensuring inclusivity and sustainability requires clear facilitation and integration.

References

Biggs, J. (2003). Aligning teaching and assessing to course objectives. Teaching and learning in higher education: New trends and innovations, 2(4), 13-17. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=1aa6531a3ec223588e907c7180c307047b84b00d

Brown, Z., & Wilson, M. (2016). The complexity of in-class debates in Higher Education: student perspectives on differing designs. Educational Futures, 7(2), 14-28. https://educationstudies.org.uk/?p=5400

Coles, C. (2009). The role of new technology in improving engagement among law students in higher education. Journal of Information, Law and Technology, 2009(3). http://go.warwick.ac.uk/jilt/2009_3/coles

Freeman, J. (2025). Student Generative AI Survey 2025. Higher Education Policy Institute. https://www.hepi.ac.uk/reports/student-generative-ai-survey-2025/

Guo, K., Zhong, Y., Li, D., & Chu, S. K. W. (2023). Investigating students’ engagement in chatbot-supported classroom debates. Interactive Learning Environments, 32(9), 4917–4933. https://doi.org/10.1080/10494820.2023.2207181

Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable operations and computers, 3, 275-285. https://doi.org/10.1016/j.susoc.2022.05.004

Kemp, V., Munk, T., & Gower, S. (2016). Clinical legal education and experiential learning: looking to the future. https://doi.org/10.13140/RG.2.2.17617.74085

Khalid, J., Ram, B. R., Soliman, M., Ali, A. J., Khaleel, M., & Islam, M. S. (2018). Promising digital university: A pivotal need for higher education transformation. International Journal of Management in Education, 12(3), 264-275. https://doi.org/10.1504/IJMIE.2018.092868

Nikolic, S., Sandison, C., Haque, R., Daniel, S., Grundy, S., Belkina, M., & Neal, P. (2024). ChatGPT, Copilot, Gemini, SciSpace and Wolfram versus higher education assessments: an updated multi-institutional study of the academic integrity impacts of Generative Artificial Intelligence (GenAI) on assessment, teaching and learning in engineering. Australasian journal of engineering education, 29(2), 126-153. https://doi.org/10.1080/22054952.2024.2372154

O’Leary, D. L. (2020). ” Smart” Lawyering: Integrating Technology Competence into the Legal Practice Curriculum. UNHL Rev., 19, 197. https://heinonline.org/HOL/P?h=hein.journals/plr19&i=207

Omelicheva, M. Y. (2007). Resolved: Academic debate should be a part of political science curricula. Journal of Political Science Education, 3(2), 161-175. https://doi.org/10.1080/15512160701338320

OpenAI. (2023, September 25). ChatGPT can now see, hear, and speak. https://openai.com/index/chatgpt-can-now-see-hear-and-speak/

Oros, A. L. (2007). Let’s debate: Active learning encourages student participation and critical thinking. Journal of Political Science Education, 3(3), 293-311. https://doi.org/10.1080/15512160701558273

United Nations. (2025). The 17 Sustainable Development Goals. https://sdgs.un.org/goals

Zare, P., & Othman, M. (2013). Classroom debate as a systematic teaching/learning approach. World Applied Sciences Journal, 28(11), 1506-1513. https://doi.org/10.5829/idosi.wasj.2013.28.11.1809

Zhou, W. (2023). Chat GPT Integrated with Voice Assistant as Learning Oral Chat-based Constructive Communication to Improve Communicative Competence for EFL earners. ArXiv. https://doi.org/10.48550/arXiv.2311.00718

About the author

Craig Smith is Lecturer in Law at the University of Salford and Senior Fellow of Advance HE. His research focus on generative AI, legal education and digital skills includes publications in journals, book chapters and conferences. He delivers keynotes and public presentations, contributing to ongoing debates on AI.

c.a.smith3@salford.ac.uk