SEEDS Hub: A Comprehensive GenAI Toolkit for Teachers for Inquiry-Based Learning

Over the past few years, the explosion in generative AI tools, spearheaded by the rapid development of Large Language Models (LLMs) and the emergence of prompt engineering as a concept, has had an undeniable impact on the way we educators do our jobs. If I were to ask you right now how you use AI in your work as a teacher, I would expect one of two replies:

• “I use ChatGPT for everything.”
• “I use specialized AI educator tools like Brisk or MagicSchool.”

Both are viable, powerful approaches and preference depends on who you are as a person (and subsequently, as a teacher). Some of us prefer the convenience of brain-dumping to ChatGPT and allowing it to organize for us rather than look up the best tool for a specific application (more on that later) and keep up with a handful of accounts and subscriptions, while others prefer the reassurance of dedicated tools that are vetted and recommended for the quality of their output. On this distinction, Moundridou et al. (2024) iterate how GenAI tools that are more structured than the flat chatbot interface of ChatGPT and other LLMs “partially predefined prompts, guide users, facilitate the prompt engineering process, and lead to outputs that more closely align with their anticipated needs and expectations.” While some teachers view this structure as a convenience, others, understandably, will consider it cumbersome and limiting.

Now let’s talk more about the actual applications of LLM-powered AI tools for educators. Moundrido et al. (2024) suggest a nifty classification into the four following groups:

• Planning, with subgroups for course design and lesson and activity planners.
• Content Creation, with subgroups textual information objects, image/video/presentation tools, concept and mind maps, code generation tools, and other forms of objects such as interactive or three-dimensional models.
• Evaluation, with subgroups assessment tools, plagiarism detection, and feedback and grading.
• Teaching Assistants, with subgroups for coming up with ideas, extracting and organizing knowledge, supporting students’ diverse needs, communication and community building, and personal/custom chatbots.

The authors go on to build a bridge between AI tools in each of these subgroups (with real examples) and Inquiry-Based Learning (IBL) principles, drawing on Pedaste et al. five-phase IBL framework: Orientation, Conceptualization, Investigation, Conclusion, and Discussion. They then match up each subgroup of AI tool to one or more of these phases while also detailing the objective of that each subgroup fulfills in those identified phases.

Moundrido et al.’s (2024) work is an excellent resource for teachers with any level of expertise in using GenAI for education (the tables presented in the table are particularly handy). The goal of this blog, though, is not to simply summarize this resource, but to actually share with you a single AI for educators powerhouse that ticks all the boxes of both the five-phase IBL framework and the authors’ classification of tools in their light. This powerhouse is Zaka’s very own SEEDS Hub

SEEDS itself is a multifaceted initiative for K-12 education that Zaka launched officially on August 18, 2025, encompassing a comprehensive and self-contained digital AI curriculum for grades  to 12, an AI for educators training program, and SEEDS Hub, which is the focus of this blog. SEEDS Hub consists of a host of (yes, free) AI tools for educators. These tools are designed to support teachers in implementing Inquiry-Based Learning, in line with Peaste et al’s (2015) five-phase framework. In the table below, we show you how the educator toolkit available on SEEDS Hub aligns with Moundrido et al.’s (2024) taxonomy of AI tools.

And, if you happen to be the type that likes to occasionally scrawl their ideas down into a chatbot, you’ll be happy to hear that you can access Zack, SEEDS’ education-focused AI chatbot, from any place on the SEEDS Hub website.