In our third live session on 1 March 2025, the AI-in-Mentoring Special Interest Group (SIG) within MenTRnet took another step in investigating AI’s potential—this time, exploring how it can help teacher-researchers plan and engage in data collection. From AI-generated data collection tools to ethical dilemmas, we had a lively discussion about how AI fits (or doesn’t!) into the EAR (Exploratory Action Research) process. Here’s what we uncovered.
AI’s Role in Planning Data Collection
Have you ever faced blank page syndrome? You sit down, ready to plan your research, and… nothing. That’s where AI can step in – it can generate ideas, suggest data collection methods, and even structure a data collection plan. Many participants agreed that AI can certainly get the ball rolling, but it doesn’t know the real contexts of our classrooms. This is where human insight comes in. AI may suggest a plan, but it takes a mentor’s experience and a teacher-researcher’s contextual knowledge to evaluate it and make it useful. It should act as a brainstorming partner, providing ideas that mentors and teacher-researchers can refine together.
Balancing AI and Human Judgment
One of the key takeaways from our reflection notes and discussion was, again, the need for careful prompting when using AI. The quality of AI-generated responses depends on the clarity and specificity of prompts (‘Garbage In, Garbage Out’ (GIGO), as the saying goes). This highlights the importance of developing AI literacy with teacher-researchers so they can effectively guide AI tools to produce useful outputs. At the same time, AI should not dictate research decisions. AI-generated plans may be structured and detailed, but they still require human validation. If we rely on AI too much, we risk losing the critical, reflective nature of research. That’s why mentors play a key role in ensuring AI’s suggestions are reviewed, adapted, and contextualised—rather than just accepted at face value.
Using AI as a Research Mentor
Could AI act as a research mentor? Participants noted that customised AI tools, such as fine-tuned GPT models, can offer relatively relevant and reliable outputs. When used correctly, AI can facilitate a dialogic research process, where teacher-researchers engage in critical reflection rather than passively accepting AI-generated suggestions.
To support this process, we discussed the idea of creating a structured and staged AI prompt handout for teacher-researchers. This handout would provide guidance on effective prompting, helping researchers to maximize AI’s potential while ensuring critical engagement with its outputs. By providing clear, structured prompts, we can help researchers guide AI in a way that enhances, rather than dominates, their thinking process. This would also help improve their AI literacy skills
Looking Ahead
As we continue this AI journey, we left our session with some key questions:
- Can inexperienced teacher-researchers critically evaluate AI-generated data collection tools? How can they be equipped to assess their relevance?
- How can AI help make research more accessible for teachers with diverse needs and experiences?
- What prompts should go into an AI prompt handout to ensure researchers get high-quality, relevant AI outputs?
- What ethical considerations do we need to keep in mind, particularly when it comes to data privacy and the role of human mentors?
Next Steps
Our next live session will focus on AI’s role in data analysis and how teacher-researchers can critically engage with AI-generated insights. We will explore strategies for using AI tools to draw conclusions, reflect on findings, and determine appropriate follow-up actions based on research data.
Stay tuned for our next discussion, and feel free to share your thoughts on using AI in data collection planning and implementation!
Şirin Soyöz Yılmaz
This blog post summarises key insights from our AI-in-Mentoring SIG meeting and reflections shared by participants. AI tools, including ChatGPT and DeepSeek, were used to synthesise and organise key themes from reflective written material and discussions, ensuring a comprehensive overview of our findings.
Photo by Markus Winkler on Unsplash
Excellent summary, thank you for this informative and carefully considered blog post.
Thanks, Eli for your feedback 🙂
AI tools can be used very carefully for Mentoring. It clarifies detail process which is excessive. At this time human mentor provides good direction. Both mentor and mentee should be specific , clear and focused on main objectives then AI tools can help us organising and well structured plan.
Thank you for sharing, Manjusha. Yes, I see what you mean, AI can sometimes over-explain things.
This blog post offers a well-balanced perspective on AI in data collection, highlighting both its transformative potential and the ethical considerations that come with it. The discussion on bias, privacy, and human oversight is especially important in today’s data-driven world. It’s refreshing to see a nuanced take that neither blindly celebrates AI nor dismisses its value. A great read for anyone interested in the evolving role of AI in research and decision-making!