Use Cases for Teaching and Learning

As students prepare to enter a world where generative AI is embedded in everyday professional practice, what they contribute begins to shift — from producing responses to exercising critical evaluation and sound judgment. 

Justyn Olby, Head of the Centre for English Communication, shares how this is developed in practice: 

• In modules such as Writing and Reading, AI literacy is integrated through a focus on critical thinking 
• Students use tools like a synthesis matrix to compare sources, identify patterns of agreement and disagreement, and verify AI-generated claims against credible evidence 
• AI outputs are treated as texts to be evaluated — students critique them using the same standards applied to human writing 

Through this, students learn to use AI judiciously: refining what it produces and recognising when outputs should be questioned or rejected outright. To learn more about how Justyn Obly integrated AI literacy into modules such as Writing and Reasoning, Virtual Business Professional, and Professional Writing, watch this interview.  
 

Today’s workplace demands professionals who can work effectively alongside AI. This places a clear responsibility on educators to redesign courses and assessments — so students learn to use AI thoughtfully and strategically, not just efficiently. 

Senior Lecturer Shyamala Deenathayalan outlines how the team has adapted their approach: 

• Students are encouraged to use generative AI in assessments and in-class activities, with an emphasis on full transparency 
• Assessment rubrics have been redesigned to focus less on language (where AI can assist) and more on how well students manage the task — their thinking, decisions, and approach 
• Open-ended oral assessments are used to: 
  • prompt real-time thinking 
  • test how students respond to follow-up questions 
  • surface their individual perspectives 
• Tasks are tested against AI to ensure they cannot be completed by AI alone 

This approach ensures that students are not just using AI but demonstrating how they work with it — making their judgment, adaptability, and ownership of ideas visible. To learn more about how Shyamala and her team redesigned their assessment rubrics and learning activities for the Management Communications courses watch this interview.   
 

Take-home essays remain one of our strongest assessment tools for helping students engage in independent, higher-order thinking. They ask students to formulate arguments, weigh evidence, make connections across ideas, and develop a position over time. In an AI-mediated environment, the challenge is not to abandon the take-home essay, but to strengthen the conditions under which students can demonstrate genuine intellectual ownership.

Matthew Hammerton, Associate Professor of Philosophy and Associate Dean (Education), and Jacqueline Ho, Assistant Professor of Sociology, School of Social Sciences, share how oral assessments can help preserve the value of the take-home essay:

• Rather than relying on unreliable AI detectors or surveillance of the writing process, they use oral examinations to help students explain and defend ownership of their work
• The focus of the oral assessment is not to “catch” AI use, but to test ownership 
• This shifts assessment towards evaluating the student’s grasp of ideas, judgment, and ability to think with the material

This approach helps save the take-home essay by preserving what makes it valuable: sustained independent thinking, careful argumentation, and meaningful engagement with complex ideas. Instructors do not need to prove whether AI was used; they need to create assessment conditions where students can demonstrate that the work is genuinely theirs. You can learn more about how you can implement oral assessments through this recorded workshop. 
 

As higher education evolves alongside rapid technological shifts, the classroom is becoming a laboratory for human-machine synergy. This transformation focuses on moving beyond simple automation to foster a deeper sense of inquiry and collaborative problem-solving among students. 

Professor Mark Chong, Dean of Students and Professor of Communication Management at SMU, has pioneered the integration of Generative AI into the classroom to transform how students approach storytelling and intellectual risk-taking. By treating these tools as creative partners, he helps students navigate the intersection of technical skill and human expression. 

• Utilizes tools like ChatGPT and Runway in his "Storytelling with AI" course to help students script and produce narrative films. 
• Leverages AI to lower the "social risk" of failure, allowing students to attribute early drafts to the machine and experiment more freely. 
• Shifts the focus of academic assessments toward reasoning, originality, and ethical judgment rather than just the final generated content. 

To learn more about how these methods are reshaping the student experience and the research behind them, read the full article: SMU Impact Stories: Eating, Creating, Believing – Professor Mark Chong Makes Sense of How People Respond to Novel Technologies. 
 

Many leading AI tools, such as ChatGPT and Gemini, now make it straightforward to customise chatbots for specific teaching purposes. This typically involves defining a clear set of instructions to guide how the chatbot interacts and curating a knowledge base it can draw on when generating responses. 

Rafael Barros, Senior Lecturer at the School of Computing and Information Systems (SCIS), shares one such use case: 

• He developed a custom chatbot that acts as a mentor, guiding students as they formulate analytical questions  
• The chatbot is structured around the ABCDEF framework:  Audience, Business Question, Category, Data, Ethics, and Formulating Analytical Questions  
• This builds on the foundational CAPS framework (Context, Audience, Purpose, Structure) taught in the core writing and reasoning course, with added emphasis on:  
  • data  
  • ethics  
  • business context  

Through this approach, the chatbot supports students in developing more structured, context-aware, and critically grounded analytical questions. Learn more about the ABCDEF chatbot here. 
 

Video content plays an important role in many students’ learning experiences. At the same time, producing high-quality videos can be time-consuming as it requires equipment, a suitable recording setup, multiple takes, and re-records when content needs updating. 

Tamas Makany, Associate Professor of Communication Management at the Lee Kong Chian School of Business, shares how he approaches this differently: 

• He uses HeyGen to create AI avatar videos of himself quickly and with less production overhead  
• This reduces the need for repeated filming and makes it easier to update content over time  

This approach allows him to maintain a visible presence in the course while creating more opportunities to connect with students and support their engagement. Learn more about the how Tamas Makany utilised HeyGen to create AI avatar videos of himself here. 
 

Well-designed questions are central to effective learning. They help students test their understanding, surface gaps in knowledge, and stay engaged through active participation. However, creating high-quality questions—especially at scale—can be time-intensive. 

Chris Poskitt, Associate Professor of Computer Science at the School of Computing and Information Systems (SCIS), shares how he addresses this: 

• He uses generative AI to create multiple-choice questions (MCQs) more efficiently  
• AI supports the generation of a wider range of question types and variations  
• This allows him to focus on reviewing and refining questions, rather than starting from scratch  

As a result, question design becomes both more manageable and more varied, supporting deeper student engagement and more effective learning checks. Learn more about how generative AI was used to create MCQs here.