Tracking AI in Education (TRAINE)
Project Details
Led by McKenzie Fellow, Dr Samantha-Kaye Johnston, the TRAINE Study (Tracking AI in Education) is being implemented as an annual research initiative designed to investigate how generative artificial intelligence (Gen-AI) is influencing teaching, learning, and assessment practices in Australian secondary school classrooms. TRAINE aims to document how Australian educators are responding to the growing presence of tools like ChatGPT, Gemini and Co-pilot in their everyday practice.

The TRAINE study focuses specifically on secondary years education, a critical stage when students are building deeper reasoning skills, developing ethical awareness, and becoming increasingly active users of digital and AI technologies.
This foundational phase uses a national teacher survey to examine:
- Patterns of Gen-AI use and non-use in teaching and assessment, including the assessment of critical thinking
- Ethical decision-making around use of AI
- Educator confidence, concerns, and support needs
The goal of TRAINE is to generate high-quality evidence that informs teacher education, policy development, and future-ready curriculum reform. Findings will help ensure that AI integration in schools is not only technically innovative, but also pedagogically meaningful, ethically sound, and grounded in the realities of the classroom.

TRAINE also contributes to the broader international conversation about what it means to teach and assess in the age of AI, offering practical insights and a longitudinal evidence base to support system-wide improvement.
The study forms part of Dr Johnston's broader McKenzie Fellowship, which explores how personalised learning in AI-enabled environments can be optimally designed in autonomy-enhancing ways to foster students' critical thinking.
Researchers
Dr Samantha-Kaye Johnston (Principal Investigator)
Collaborators
Dr Mireia Vendrell-Morancho (Artificial Intelligence Research Institute (IIIA) of the Spanish National Research Council)
Louise Hartley (Educator, Department of Education Victoria)
Xuanhua Wu (Postgraduate student, University of Melbourne)
Luting Zhang (Postgraduate student, University of Melbourne)
Research Outcomes
TRAINE 2025: Early Insights from Australian Teachers
Generative artificial intelligence (GenAI) is now firmly part of the educational landscape. Yet much of the public conversation continues to focus on predictions, risks, and speculation rather than the realities of classroom practice. The Tracking AI in Education (TRAINE) study seeks to better understand how Australian secondary school teachers are navigating GenAI and how it is shaping teaching, assessment (including critical thinking assessment), and ethical decision-making in schools.
The 2025 TRAINE dataset comprised 665 responses from Australian secondary school teachers across Years 7 to 12, representing a diverse range of subject areas, career stages, and levels of experience with GenAI. While ChatGPT was the most commonly reported tool, many teachers described using multiple platforms, including Copilot, Gemini, Claude, Canva, Diffit, Brisk, NotebookLM, Magic School AI, and department-supported tools such as EduChat, reflecting an emerging ecosystem approach in which different AI tools are used for different professional purposes.
While detailed analysis is ongoing, several clear patterns are emerging from the data. Rather than simply adopting or rejecting AI, teachers are actively experimenting with how these tools can support learning while preserving the central role of teacher expertise and student thinking.
Explore the findings:
- Download the TRAINE 2025 infographic – a visual summary of the six key findings.
- Read the full blog – explore each finding in more detail, with downloadable classroom resources generously shared by participating teachers.
Published Research
TRAINE 2025 Teacher Resources
- Resource 1: Dialogic engagement
- Resource 2: Schema check
- Resource 3: AI-traffic light disclosure form
TRAINE 2025 Research Summary
If you have any questions about participating or would like additional information about the project, please email the lead researcher, Dr Samantha-Kaye Johnston at: samanthakaye.johnston@unimelb.edu.au