Taking a Hypothesis-Based (and Human) Approach to Education in the Age of AI with the EdTech Hub

Group Submission Type: Workshop

Description of Session

Artificial intelligence is reshaping education at a rapid pace, creating both opportunities and challenges for policymakers, practitioners, and researchers. Amid the excitement and uncertainty, one question persists: how do we ensure AI is used in ways that are effective, equitable, and human-centered?

Our workshop will introduce participants to the AI Observatory and Action Lab’s hypothesis-driven approach to navigating AI in education. Rather than starting with technology, this approach begins by understanding the key education levers which could be influenced by AI integration and then proceeds to identify hypotheses to be tested to determine what works, and to support intentional decisions about AI today, while keeping sight of where education needs to go next.

The session will begin by walking participants through the our theoretical framework for considering AI in education, developed as part of our global AI Observatory’s horizon scan. This framework is designed as a navigation tool for decision-makers, combining foresight methods, systems thinking, and participatory futures approaches. It helps education leaders consider not only how AI is being used today but also how it might reshape classrooms, systems, and roles in the future.

After this introduction, participants will engage directly with the hypothesis-based method. Facilitators will guide participants in identifying AI-related ideas or hypotheses that are most relevant to their current work—whether at the level of classroom practice, policy, system design, or research. For example, hypotheses might include:

- If Ministries of Education are given adequate support to test AI for real-world delivery challenges, then they will build lasting capabilities to prototype, govern, and scale responsible AI use in education, and achieve more with less.
- If teachers are meaningfully engaged in shaping how AI is used across education systems, we will unlock more effective, equitable, and grounded approaches that improve teacher wellbeing, enhance teaching, and strengthen learning outcomes.

Working in small groups, participants will select hypotheses to explore together. Each group will examine:
1.What signals and evidence already exist to support or challenge the hypothesis.
2.What local factors might influence how it plays out in their context.
3.What simple, practical ways they could test or generate new evidence around this idea in their own day-to-day work.

The workshop will close by bringing participants back into a plenary discussion. Together, we will reflect on how these hypotheses connect to one another, what gaps remain, and how this framework and approach can inform their navigation of AI in education from here on. Importantly, the session will also capture new hypotheses and insights that emerge from participants, ensuring the collective wisdom of the group feeds into EdTech Hub’s broader work.

By the end of the session, participants will:
-Understand the EdTech Hub’s theoretical framework for navigating education in the age of AI.
-Learn how a hypothesis-based approach can be applied to emerging AI opportunities and risks.
-Identify hypotheses that are directly relevant to their work and explore them collaboratively.
-Gain practical strategies for testing hypotheses in agile, context-sensitive ways.
-Contribute new insights to EdTech Hub’s global knowledge base on AI in education.

Sub Unit

• Book Launches and Workshops / Workshop

Chair

• Verna Lynn Lalbeharie, EdTech Hub

Workshop Organizer

• Daniel Plaut, EdTech Hub

Presenter

• Lea Simpson, Brink