Practical Workshops

Build your school’s AI roadmap: a strategic framework for school leaders

Workshop Leaders:

Jamie Toner,  Director of Technology & Innovation, Singapore American School, Singapore
Chris Ippolito,  Emerging Technology Coordinator, Singapore American School, Singapore

"As artificial intelligence moves from novelty to necessity, educators face a triple challenge: How do we use it, how do we teach it and how do we evolve alongside it? This immersive, hands on workshop invites participants to view the AI revolution through three distinct lenses designed to provide both immediate utility and long-term strategic clarity.

First, we explore Teaching with AI, where participants engage in "Speed-Design" sessions - using generative tools to automate administrative workflows, differentiate materials in seconds and spark creative lesson hooks. 

Next, we pivot to Teaching about AI, defining what true "AI Fluency" looks like. We move beyond prompt engineering to discuss algorithmic bias, data privacy and the mechanics of LLMs, ensuring students are critical consumers of technology. 

Finally, we address Teaching in the Age of AI. This reflective segment tackles the human-centric core of education: How does the role of the teacher shift from content provider to high-level mentor? What uniquely human skills - like empathy, ethical judgment and complex collaboration - must we double down on to prepare students for an AI-augmented workforce?

Designed for secondary educators and school leaders, this workshop balances high-energy practical application with strategic foresight. Attendees will not just ""see"" AI; they will build a personal AI roadmap. You will leave with a curated toolkit of strategies and a clear vision for maintaining the human heart of the classroom in an AI-saturated world."

Key takeaways include:

• Identify everyday planning and admin tasks where AI can reduce workload and free up time for teaching and student support
• Design age appropriate lessons that help students understand, question and use AI responsibly and ethically
• Apply teaching strategies that build skills AI can’t replace, such as critical thinking, creativity, empathy and ethical decision making

Intended Audience: K-12 Educators and Leaders

Designing active learning with the CLEAR pedagogical framework

Workshop Leader:

This workshop is designed for educators who are interested in implementing an active and authentic approach to teaching and learning within their courses. In the course, participants will be introduced to a dynamic pedagogical approach that weaves together active learning, authentic assessments and peer learning through Contextualised Learning via Enquiring, Answering, and Reflecting (CLEAR) to increase student agency.

In this workshop, Assoc. Prof. Stephen Tay will share results from a six year journey in the implementation of CLEAR across courses, Departments, Colleges and Institutions with triangulated measurements (i.e. assessment scores, student feedback, sample of students’ work and feedback from lecturers). Briefly, CLEAR was developed from the existing student generated questions (SGQ) approach in literature through the following three improvements: 1) utilisation of higher orders of Bloom’s taxonomy, 2) development of answers to the questions developed and 3) employing industry as contexts for the questions for authentic assessments. 

Drawing inspiration from the experience and case studies shared during the workshop, participants will create personalised lesson/assessment plans and collaborate with peers to share innovative ideas for achievement of the desired learning outcomes. 

By the end of this workshop, participants will be empowered with practical strategies to create an engaging learning environment with CLEAR to foster teaching and learning in their respective classes.

Key takeaways include:

• Identify the elements and articulate the impact of CLEAR implementation across disciplines
• Develop personalised lesson/assessment plans to adopt CLEAR in their teaching
• Share and receive feedback to help improve the developed lesson/assessment plans

Intended Audience: Higher Ed Educators

Taming the algorithm: maintaining pedagogical integrity in AI assisted lesson planning

Workshop Leader: 

Simon Hornbrook,  Head of Digital Integration,  St. Joseph's Institution International School, Singapore

The promise of the "10-second lesson plan" is alluring, but it brings a critical fear: are we sacrificing deep, constructivist pedagogy for behaviourist convenience? Early research suggests that without guidance, Generative AI defaults to formulaic, teacher-centred instruction. However, a recent study of experienced IB educators in Singapore reveals a different reality: expert teachers are actively "taming" the AI to serve, rather than replace, their pedagogical values.

In this intensive 2 hour workshop, we move beyond generic prompting advice to apply four evidence-based strategies derived from this "Human-in-the-Loop" research. First, participants will adopt the "Critical Curator" stance, engaging in a "Pedagogical Turing Test" to diagnose hidden bias in AI output. Next, they will practice "Pre-loading" (injecting pedagogical context before the prompt) and "Iterative Dialogue" (treating AI as a thought-partner rather than a vending machine) to restructure their planning workflows. Finally, the session culminates in "Transformative Design," where attendees flip the script to design student-facing AI tools that drive inquiry rather than just delivering content.

Attendees will leave not just with a lesson plan, but with a replicable framework to ensure their use of AI enhances, rather than dilutes, student agency and inquiry.

Key takeaways include:

• Confidently assess AI outputs to ensure they support strong pedagogy, not just speed or convenience
• Structure prompts so AI aligns with specific teaching approaches before generating classroom materials
• Design AI-supported activities that promote student thinking, inquiry and independence rather than passive use

Intended Audience: K-12 Educators (Middle/High School focus), Curriculum Coordinators and EdTech Integration Specialists

Beyond chatbots: designing and building learning centred AI agents

Workshop Leader:

Mui Kim Chu,  Associate Professor, Deputy Director of SIT Teaching & Learning Academy (STLA), Singapore Institute of Technology, Singapore

Generative AI is rapidly entering university classrooms, yet many educators remain uncertain about how to move beyond using AI as a general-purpose chatbot or productivity aid. When AI is introduced without pedagogical design, it can unintentionally reduce student thinking, over-scaffold learning, or undermine intended outcomes. This hands-on workshop addresses this challenge by guiding educators through a pedagogy-first process for both designing and building AI learning agents.

The workshop begins by reframing AI agents as pedagogical artefacts, not tools. Participants will learn how to identify authentic learning problems, specify the target thinking they want students to develop, and select instructional strategies that legitimately benefit from AI support. Using a structured Faculty Design Input Template, participants will articulate the agent’s pedagogical role, boundaries, guardrails, conversation control logic, and fading mechanisms to ensure students ultimately perform independently.

Crucially, the workshop goes beyond design. Participants will translate their completed templates into actual system prompts and use them to build and test a working AI agent during the session. Through guided testing, participants will observe how different design choices affect agent behaviour, including when the agent should probe, redirect, summarise, or end an interaction. Common pitfalls—such as over-helping, answer dumping and dependency—are surfaced and corrected through live iteration.

By the end of the session, participants will leave not only with a pedagogically sound design blueprint, but also with a functional AI learning agent that is aligned to their teaching context and ready for classroom use or further refinement.

Key takeaways include:

• Identify appropriate learning problems and pedagogical strategies 
• Design and document a pedagogically supported AI agent 
• Build a working AI learning agent that supports defined learning outcomes

Intended Audience: Higher Ed Educators