Thank goodness it’s Saturday and what a week it’s been here on the 24DaysOfAI Appvent calendar!
On Monday, we introduced the calendar with Consensus. Then on Tuesday we had Intelligent Evidence. Wednesday saw Emma Darcy introduce Gemini from Google with me taking over Thursday’s mantle with Seesaw. Yesterday’s brilliant AI tool was the highly popular Goblin Tools shared by Bukky Yusuf and today we explore a tool suggested and shared by Matthew Wemyss, and before we dive in, can I also make a recommendation that you connect with Matthew and subscribe to his useful and handy newsletter while you’re at it! Now, over to Matthew.
Let’s be honest, there’s been no shortage of student-facing AI tools popping up lately. But here’s what usually nags at me. Who’s actually in control of the conversation? If a student is chatting with an AI and there’s no accountability, no logs, no safety checks, that’s a problem.
That’s why I wanted to put Mindjoy in the spotlight today.
I’ve been using it mainly in computer science lessons, and we’re starting to explore it across other subjects too. It’s not trying to be everything. But what it does well is give you peace of mind. Students can engage with AI in a way that’s safe, structured, and fully visible to you.
Here’s what it is, how it works, and why it’s one of the few AI tools I’ve felt confident using with a full class.
What it is
Mindjoy is a student-facing AI platform, but not the kind that drops a random bot into a browser and leaves you guessing. Students have to log in. They go through a few steps before they reach the AI. And they know they’re interacting with a system that’s been built for learning, not just conversation.
The standout feature, the thing that drew me to it in the first place, is the oversight. You get full access to conversation histories. And here’s the part that matters most to me. Those safeguarding filters aren’t just sitting there quietly in the background. If a student types something inappropriate, you don’t get a passive alert buried in a dashboard somewhere. You get an email. Within 30 seconds. I can act on that immediately. It’s fast, it’s direct, and honestly, it’s the kind of peace of mind I didn’t realise I needed until I had it.
You can also write your own prompts, build and deploy your own bots, and shape how they interact. This isn’t AI taking over. It’s AI working inside a structure you’ve designed.
Features that make a difference
There are a lot of smart tools baked in, but here’s what I’ve actually used and found useful.
- AI tutors that students access on their own when they hit a learning bottleneck. They’re available 24/7. It’s not a shortcut. It’s an extra layer of support.
- Prompt control, which lets me shape how the AI sounds, how it guides, and how it responds. I can give it some of my tone and teaching approach. That matters.
- Multimodal bots, which we’ve used for projects in Canva, robotics, 3D design, and Micro:bit. If I can describe the task in a prompt, the bot can support it.
- Learning pathways, which let you build multi-page learning journeys with a mix of quizzes, content, and moments for students to interact with AI where it helps.
- Assessment tools, including long-answer marking, where you define the criteria and the system shows you how each response matches up. The dashboard layout is simple and saves time without taking away teacher judgment.
- Insights and analytics, so you can see who’s using what and how. It’s not just student-facing, it’s teacher-informed.
What it looks like in practice
We’ve already run some solid use cases in school.
Students working on robotics and Micro:bit projects used bots to help debug, plan, and reflect. In a Canva-based design project, we added a feedback bot so students could get personalised advice as they iterated. Our subject-specific bots support students in computer science with problem-solving and planning.
We’ve also built learning pathways where students get help early on, then move into self-guided tasks later, with no bots on certain pages to encourage independent thinking.
And we’re planning to roll it out to other subjects in term two, starting with humanities and science.
Things to consider
Mindjoy offers a free trial for 14 days, so you can explore how it fits with your teaching before committing. It is a paid platform, but what you’re paying for is the peace of mind that comes with oversight and a tool that has been shaped specifically for education.
The features that matter most, including learning pathways, assessments, and detailed analytics, are part of the paid plan. For schools that want to use AI with structure and intention, it can be a worthwhile investment.
Setup takes some thought. Writing prompts, building pathways, and deciding when and how to bring bots into learning all require you to think like a teacher. But you don’t need to be a coder. You just need to know your students and how they learn best.
Why I’d recommend it
If you’re looking for a student-facing AI tool that keeps you fully in the loop, Mindjoy is worth your attention.
It gives students structured, scaffolded access to support. It gives you the tools to guide that interaction. And it gives everyone the clarity to know what’s happening and why.
For me, it’s been one of the first platforms I’ve come across that gets the safeguarding piece right from the ground up. That matters. And knowing I can respond to anything within 30 seconds if I need to? That’s not a small thing. It’s what makes the difference between trying something out and actually rolling it out with confidence.
🔗 Explore Mindjoy’s AI platform here
My massive thanks to Matthew for sharing this tool, it’s one which has made it on to the Appvent calendar in recent years and one of the things that draws me to it the most, the founders come from education, which is so clearly evident when you use the tool. Have a look, I agree with Matthew, it’s well worth a look.
