Sessions
All sessions run on Day One as extended three-hour workshops. The program is built around three session blocks — the three tracks below — with four workshops in each. Each session is a mix of hands-on work, short presentations, and open discussion, with the balance varying from one session to the next.
The program is to be confirmed. Sessions, presenters, and scheduling are subject to change.
Sessions at a glance
AI & Tools Track
Sessions in this track are workshop-style and practical. You will leave with something you built, configured, or tested yourself.
Build Your Own AI Research Assistant
Daniel Ebbert
You don’t need to be a developer to build a tool that works for your research. This session walks you through designing and deploying a simple AI assistant tailored to your own workflow — literature review, data coding, writing support, or something else entirely.
Day 1TBC
Deploy Your AI Agent: From Prototype to Practice
Vitomir Kovanovic
Building an AI agent is one thing. Getting it to work reliably in a real research or teaching context is another. This session covers the practical decisions that sit between a proof-of-concept and something you can actually use — and trust.
Day 1TBC
Evaluating AI Agents: How Do You Know It’s Working?
Srecko Joksimovic
If you’re using an AI agent in your research or practice, how do you know it’s doing what you think it’s doing? This session introduces evaluation frameworks for AI agents — from basic output checks to more systematic approaches for assessing quality, consistency, and alignment with your goals.
Day 1TBC
Coding Qualitative Data with AI: Faster, Smarter, Still Rigorous
Ryan Baker & Linxuan Zhao
AI tools are changing how qualitative researchers work with data — but not always in the ways people expect. This session examines what AI can and can’t do in qualitative coding, with hands-on practice and an honest discussion about rigour, transparency, and what you still need to do yourself.
Day 1TBC
Research Practice, Ethics & Partnerships Track
Sessions in this track are research-facing and applied — the practice, ethics, and partnerships that surround real-world educational research, from classroom prototypes and AI teaching simulations to working with schools and government.
The Sandbox Student: Designing AI Simulators That Push Back
Kristina Raave
Can a simulated student prepare educators for the emotional realities of the classroom? This hands-on session introduces AI student agents as pedagogical simulators for practising de-escalation and adaptive instruction. You’ll compare rule-based and LLM-driven agents, see how silent observer agents can give real-time feedback, and confront where productive friction ends and oversimplification begins.
Day 1TBC
A Working Prototype for Real-Time Surfacing of Learning Dispositions in K-12 Collaborative Learning
Andrew Zamecnik & Jarrod Johnson
A working prototype that puts AI agents into a K-12 classroom in real time — aligned to curriculum frameworks, surfacing learning dispositions as they emerge in discourse. This session covers what it takes to make it work: the infrastructure, the tradeoffs, and the adoption challenges of bringing a prototype into a real school.
Day 1TBC
Leading in Academia: Building Partnerships with Schools and Government
Maria Vieira, Rebecca Marrone & Shane Dawson
Research that matters usually involves partners outside the university. This session draws on direct experience of building and sustaining partnerships with schools and government — what works, what doesn’t, and what you need to put in place before you start.
Day 1TBC
Data Ethics in Education: Consent, Privacy, and the Datafication of Learning
Oscar Deho
As education becomes more data-rich, the ethical stakes rise. This session examines the practical and philosophical dimensions of data ethics in educational research — informed consent, data sovereignty, the risks of surveillance, and what it means to do data-intensive research responsibly.
Day 1TBC
Methods, Measurement & Analytics Track
Sessions in this track are hands-on and technical. They work through the methods, measurement, and analytics that turn messy educational data into defensible findings.
Tracing Self-Regulation: Analysing Process Data in Learning Research
Flora Jin & Linxuan Zhao
Self-regulated learning is one of the most studied constructs in educational psychology — and one of the hardest to measure well. This session focuses on process data approaches: how to move beyond self-report, what temporal and sequential analyses can reveal, and what the data can and cannot tell you about how learners actually regulate.
Day 1TBC
Designing Your Research Instrument: From Construct to Question
Phuong Pham
A research instrument is only as good as the thinking behind it. This session walks through the process of moving from a theoretical construct to a set of items or measures that actually capture what you intend — with attention to common failure points and how to avoid them.
Day 1TBC
What Are We Actually Measuring? Validity, Constructs, and the Hard Problem of Learning Data
Florence Gabriel & Abhinava Barthakur
Measurement in education is harder than it looks. This session takes seriously the question of what it means to measure learning, engagement, anxiety, or wellbeing — examining construct validity, the gap between what we measure and what we care about, and what good measurement practice looks like in practice.
Day 1TBC
Design-Based Research in Action: Lessons Learned from the Play My Math Use Case
Eric Roldan Roa
This workshop/talk targets participants interested in or already applying a Design-Based Research methodology in their work. The session offers insights into the theoretical, practical nuances, and challenges encountered when engaging in the six DBR phases (i.e., Focus, Understand, Design, Conceive, Build, and Test) and conducting this type of research in multicultural contexts. The participants will experience, learn, and discuss from the journey of an EdTech tool combining music and mathematics called Play My Math, which has completed a total of three successful DBR cycles in Mexico, the UK, and Brazil. As such, the participants can profit from the PMM experience and have a reference for their own research.
Day 1TBC