Teaching with Responsible AI Network (TRAIN)

Great teaching has always been about people.

The Teaching with Responsible AI Network explores how AI can enhance, not replace, human learning by supporting ethical practice, critical thinking, and meaningful educational experiences.

Teaching and Learning Scenarios

This collection of teaching and learning scenarios has been carefully developed to support rigorous research into the Scholarship of Teaching and Learning (SoTL), with a particular focus on the role of AI governance in educational settings. Accessible via the drop-down menu in the taskbar (the Scenario Bank) and below, these scenarios are grounded in evidence-based pedagogy and policy-aligned frameworks to guide educators, researchers, and students in navigating the ethical, practical, and pedagogical complexities of AI integration. 
The Misinformed Machine
This scenario-based learning activity invites K–12 students to investigate the myth that Artificial Intelligence (AI) is always right. Through a guided exploration, students will learn that AI tools are trained on historical data, can make mistakes (including hallucinations), and may reinforce existing biases. The scenario encourages critical thinking, digital literacy, and ethical awareness. Students engage in a classroom activity where AI tools are used to answer questions, then evaluate those answers through discussion and comparison with trusted sources. The goal is to foster a balanced understanding of AI’s capabilities and limitations in education.
AI Lesson Planning
AI and Assessment
This case study explores the tension between efficiency-driven AI educational tools and the deeper pedagogical values that underpin contemporary teaching—particularly student agency and classroom dialogue. Drawing on Chen et al. (2025), the scenario positions educators in a decision-making role where they must evaluate AI-generated lesson plans for alignment with school values. Participants engage in analysis, reflection, and redesign activities that foster ethical, values-led adoption of educational AI, supporting critical digital pedagogy. The case is designed for use in teacher education, educational leadership programs, and professional learning contexts to prompt consideration of governance, design ethics, and pedagogical integrity in AI adoption.
This scenario explores how institutions can responsibly integrate GenAI into assessment reform while maintaining strong alignment with existing accreditation and regulatory frameworks. It highlights the role of good governance — based on transparency, consultation, and risk management — in ensuring that technological innovation supports, rather than undermines, established professional standards. The scenario invites critical reflection on how governance structures can proactively maintain trust and compliance during rapid technological change.

Outreach: AI and Assessment

This video offers a snapshot of the AI and assessment ecosystem as it stood in 2025. While we present a basic scaffold for assessment, we do so in the context that AI could be viewed as an ever-evolving sociotechnical system.

Researchers

Dr Amanda Muscat
Dr Janine Arantes
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Steven Kolber
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Acknowledgement of CountryWe acknowledge the Ancestors, Elders, and families of the Kulin Nation, who are the Traditional Owners of the land where this work has been predominantly completed. As we share our own knowledge practices, we pay respect to the deep knowledge embedded within the Aboriginal community and recognise their custodianship of Country. We acknowledge that the land on which we meet, learn, and share knowledge is a place of age-old ceremonies of celebration, initiation, and renewal, and that the Traditional Owners’ living culture and practices continue to have a unique role in the life of this region.
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