Logo

Harness human and artificial intelligence to improve classroom debates

A guide to using artificial intelligence to support nuanced class debates that train students’ critical thinking and communication skills

Elmar Kutsch's avatar
Cranfield University
26 Sep 2023
copy
0
bookmark plus
  • Top of page
  • Main text
  • More on this topic
A robot holds up a sign showing two people talking

You may also like

Planning and facilitating quality discussions
How to plan and facilitate student discussions via online classes

Popular resources

Structured classroom debates enrich not only intellectual capacities but also the emotional intelligence of students. Through robust discourse, these debates encourage students to delve deep into topics, synthesising information from various sources to present well-reasoned arguments. This exercise naturally fosters critical thinking and refines communication skills, particularly in articulating complex ideas coherently and persuasively.

By confronting alternative viewpoints, students engage in active listening and cultivate open-mindedness – an invaluable trait in an increasingly polarised world. Structured debates also imbue participants with greater awareness of the complexities, risks and uncertainties inherent in any given topic, thereby elevating their collective mindfulness. Hence, structured in-class debates are not just intellectual jousts but crucial andragogical tools that facilitate a comprehensive range of skills, from analytical rigour to emotional and social acumen.

I have employed structured debates to encourage nuanced discussions on the subject of organisational resilience at multiple levels of an organisation, as part of an Executive MBA module. Central to this method are “constructive” and “rebuttal” phases of debate.

The constructive phase

During the constructive phase, students are tasked with building comprehensive arguments to address the layers of resilience – operational, strategic or tactical – supported by data, real-world case studies and theoretical frameworks. Here, students can use ChatGPT for rigorous fact-checking, data collection and argument formulation, enabling them to engage with the complexities inherent in organisational resilience.

Using AI exclusively in the constructive phase harnesses the strengths of human and machine intelligence. AI can assist with data collection and fact-checking to help form strong, evidence-based arguments. This can enable students to focus on honing their argumentative skills, enhancing their understanding of the topic and developing persuasive rhetorical strategies.

However, keeping AI out of the direct rebuttal phase is also crucial for several reasons.

The rebuttal phase

Spontaneously responding to an opponent’s argument is essential in a debate that relies heavily on human cognition and emotional intelligence. Real-time decision-making, understanding nuanced arguments and employing persuasive tactics cannot yet (and should not) be fully replicated by AI. Moreover, the aim of debate extends beyond just winning an argument; it is also about engaging in meaningful dialogue, building rapport and showing empathy – all areas where the human touch is irreplaceable.

Excluding AI from directly aiding in the rebuttal phase of debates preserves the irreplaceable elements of impromptu human cognition, flexibility and emotional intelligence, which are paramount for interpreting nuanced arguments and making real-time decisions.

Post-debate reflection

The utility of AI can be maximised in the constructive as well as post-debate process through the principles of reflect, reassess, reengage and co-create. Following the debates, AI tools can assist students in revisiting their performance and the subject matter through detailed analytics, speech evaluation and sentiment analysis. This facilitates more profound reflection, allowing students to reassess the strengths and weaknesses of their arguments. The technology can further provide insights or resources that encourage re-engagement with the topic from alternative perspectives. As students revisit the subject matter multiple times in preparation for their assignments, an evolving and rounded view can be co-created between the student and the AI, each iteration benefiting from the unique strengths of both human and machine intelligence.

In my scenario of facilitating post-reviews following a debate, students are tasked with capturing their key insights by completing a meta-cognitive journal. Within this journal, they are encouraged to jot down a few salient bullet points. They have the option to use Chat GPT to transform these bullet points into a more coherent and nuanced understanding of organisational resilience.

AI in future debates

It is worth noting that future iterations of these debates could benefit from using more advanced AI technologies. In the run-up to debates, AI-powered speech analysis could provide invaluable feedback during practice sessions, scrutinising elements such as tone, pace and the overall strength of arguments. This would enable participants to refine their delivery and strengthen content. During the live sessions, AI’s real-time capabilities could come into play through instant fact-checking, sentiment analysis and pattern recognition. This would provide unprecedented rigour by evaluating the arguments’ accuracy, relevance and emotional resonance. Such instantaneous feedback would also allows students to gauge the impact of their points on the audience in real time. By melding human intellectual and rhetorical capacities with the computational prowess of AI, the overall experience and outcomes of structured debates could be substantially enhanced.

The use of ChatGPT in the constructive phase of debate planning has led to a marked improvement in the quality of structured debates; students employed a broader array of case studies and presented a more diverse range of arguments. However, some students took certain information at face value without adequately scrutinising its merit for shaping their constructive arguments. It has been illuminating to witness these unexamined assumptions being dissected during the cross-examination phase and, most notably, in the impromptu rebuttals, for which no preparation time and AI are allowed.

Elmar Kutsch is an associate professor in risk management at Cranfield School of Management.

If you would like advice and insight from academics and university staff delivered direct to your inbox each week, sign up for the Campus newsletter.

Loading...

You may also like

sticky sign up

Register for free

and unlock a host of features on the THE site