The AI Teacher Lounge

Hey friends, Scott here.

I am excited to share a quick update from The AI Teacher Lounge.

We are only two episodes into the podcast, and it has already grown beyond YouTube.

You can now find The AI Teacher Lounge on SoundCloud, Spotify, Amazon Music, and iHeartRadio. That is a pretty fun milestone for something that started as an idea to help educators make sense of AI without drowning in hype, panic, or tool-of-the-day nonsense.

You can find everything here: https://theaiteacherlounge.com/

Our next episode is also one I think every educator needs: Ep 03: Watch What You Put Into AI | AI Privacy and Safety for Educators

Or, as I have been thinking about it, the “please don’t paste student info into the magic robot box” episode. It is practical, important, and a good bridge before we start getting into more hands-on workflow demos.

Now, let’s jump into this week’s brief.

Source: Microsoft Education Blog

Link: https://techcommunity.microsoft.com/t5/education-blog/assignments-in-microsoft-teams-grading-feedback-and-ai-built/ba-p/4528387

What happened: Microsoft is adding more AI support directly into the Assignments workflow in Microsoft Teams and through LMS connections like Canvas and Schoology. The idea is that teachers can get help while creating assignment instructions, building rubrics, giving feedback, and managing grading tasks.

Why educators should care: This is the kind of AI update I pay attention to because it does not require teachers to jump into a brand-new tool, learn a separate dashboard, or build a 12-step workflow that only looks good in a conference demo. If your school already uses Teams or Microsoft 365, this may eventually become part of the normal assignment process.

That does not mean you should let it drive the bus. It means it may become a useful assistant in the passenger seat.

What to watch: If your school uses Microsoft Teams, pay attention to how your district rolls this out. The key question is not “Can AI help make a rubric?” The better question is “Does this rubric match my standards, my students, and the way I actually teach?”

AI suggestions are starting points. Teacher judgment is still the adult in the room.

Source: Shake Up Learning

Link: https://shakeuplearning.com/blog/reducing-teacher-burnout-learner-agency/

What happened: Shake Up Learning shared Jake Miller’s “Salad Night Strategy,” a practical way to think about learner agency. Instead of teachers trying to personalize everything for every student, the idea is to create clear goals while giving students more meaningful choices in how they get there.

Why educators should care: Teacher burnout is real, and one reason it happens is that teachers often end up doing all the thinking, all the planning, all the adjusting, and all the rescuing.

The “short-order cook” version of teaching sounds caring, but it can wear you down fast. Learner agency shifts some of that responsibility back to students in a healthy way. Not “good luck, figure it out,” but “here is the goal, here are your options, now make a smart choice and own part of the process.”

That is good for students, and frankly, it is good for teachers who would like to finish a week with a few brain cells still waving from the back row.

What to watch: Do not turn this into a giant redesign project. Start small. Give students one meaningful choice inside an assignment you already planned. Choice is not chaos when the goal is clear.

Source: eSchool News
Link: https://www.eschoolnews.com/it-leadership/2026/06/24/for-schools-cyber-resilience-starts-at-the-data-layer/

What happened: The article focuses on cyber resilience, which is the ability to keep going or recover quickly when something goes wrong with technology. The big point is that schools need to protect the data layer: the systems that store, back up, and recover important information like student records, learning platforms, staff data, and operational systems.

Why educators should care: Most teachers are not managing backup systems or writing cybersecurity recovery plans. That is not the job.

But teachers are absolutely affected when those systems fail.

If the LMS goes down, grades disappear, files are locked, or student data is exposed, the classroom

impact is immediate. Lessons get disrupted. Communication gets messy. Trust takes a hit. And now that AI tools are spreading into more school workflows, the amount of data moving around is only getting bigger.

What to watch: This is a good time to ask a simple question: “What is our plan if the system we depend on goes down?”

You do not need to become the cybersecurity person. But it helps to know who to contact, what data is backed up, what tools have approved use, and what your classroom backup plan looks like if the fancy digital thing takes a nap at the worst possible time.

This week’s tool worth watching is not really a separate tool. That is why it is interesting.

Microsoft is building AI support into Assignments inside Teams and connected learning management systems. In plain English, that means AI help may show up right where teachers are already creating assignments, writing directions, building rubrics, giving feedback, and tracking student work.

That matters because teachers do not need another tool to babysit.

The possible win here is workflow. If AI can help draft clearer directions, suggest rubric language, or help speed up feedback without pulling teachers out of the system they already use, that is worth watching.

The caution is obvious: built-in does not automatically mean better. AI-generated instructions can be vague. Rubrics can sound polished but miss the actual standard. Feedback can be technically correct and still not sound like something you would say to a student.

My take: If your school already uses Microsoft Teams, this is worth exploring carefully. Try it on low-stakes assignments first. Keep what helps. Delete what does not. And please do not let the AI write feedback that sounds like it came from a robot wearing a cardigan.

This week, I want to recommend Data Science by John D. Kelleher and Brendan Tierney from The MIT Press Essential Knowledge series. I picked this one up while preparing for a client training, and it is a great, short introduction if you want to better understand data science without signing up for a graduate program by accident.

Data science, in plain English, is about using data to find patterns, make better decisions, and understand what is happening. That connects directly to AI because AI tools are only as useful, safe, and accurate as the data behind them. Even with my background teaching databases and technology, I still got a lot out of it.

For educators, this is a good way to get up to speed on the data side of AI, especially as schools keep talking about student data, privacy, dashboards, and AI decision-making. I also bought the audiobook version, but fair warning: this is not my “listen while driving” recommendation. Great content, but it needs coffee, a notebook, and preferably not Houston traffic.

Give Students One Small Choice

Try adding one simple choice to an assignment you already plan to use.

Nothing huge. Nothing that requires a new platform, a parent permission slip, and a committee meeting.

For example, instead of requiring every student to respond in the exact same format, give them two or three ways to show understanding:

• Students can write a short paragraph.
• Students can create a quick slide or infographic.
• Students can record a short explanation.
• Students can build a simple example or demonstration.

The key is to keep the learning target the same. The choice is in how students show what they know, not whether they have to learn the thing.

You can also keep your grading simple by using the same success criteria for every option. For example:

• Did the student explain the concept accurately?
• Did the student include evidence or examples?
• Did the student communicate clearly?
• Did the student meet the required parts of the assignment?

This is learner agency without making your grading life weird.

And yes, some students will pick the easiest-looking option. That is fine. Adults do that too. The trick is making sure every option still points back to the learning goal.

I like AI best when it fits into work teachers are already doing.

That is why the Microsoft Assignments update caught my attention. I am not saying every teacher should run out and use it tomorrow. I am saying this is the direction that probably matters more than another shiny AI tool with a name that sounds like a rejected Marvel sidekick.

Teachers do not need more tabs. They need less friction.

If AI can help a teacher write clearer assignment directions, tighten up a rubric, or draft feedback faster inside a workflow they already use, that is a practical win. Not a revolution. Not a miracle. A win.

But here is the part we cannot skip: AI help still needs teacher review.

A rubric that looks clean may not match your actual standard. Feedback that sounds nice may not fit the student. Assignment directions that seem clear to an AI may still confuse a ninth grader who is reading them during third period while also thinking about lunch.

That is why I keep coming back to the same idea: AI is the assistant, not the authority.

The learner agency piece connects to this too. Teachers are tired partly because we keep building systems where the teacher carries all the cognitive weight. We plan it, explain it, adjust it, rescue it, remind everyone about it, and then grade it.

At some point, students need to carry more of the work of learning. Not because teachers care less, but because learning requires ownership.

So maybe the real theme this week is not “use more AI.” Maybe it is “stop doing every part of the work yourself.”

Let AI help where it fits. Let students make meaningful choices where they can. Keep your judgment in the center.

That feels less like hype and more like survival with a lesson plan.

This week in StackFord, I have been thinking a lot about teacher workload and how much the design of a course matters.

When I build curriculum, labs, simulations, or teacher support materials, I am not just thinking, “Does this cover the standard?” That matters, of course. But I am also thinking, “Can a real teacher actually use this on a normal school day?”

That is the part people sometimes miss.

A resource can be technically aligned, beautifully formatted, and still be a pain to teach. If it requires the teacher to constantly translate, troubleshoot, rebuild, or explain around the gaps, it is not really saving time.

The bigger takeaway is this: good instructional design should reduce friction. That can come from AI support, better directions, student choice, cleaner rubrics, smarter labs, or just not making teachers click through 19 things to get one job done.

Fancy is fine. Useful is better.

Ask one simple question this week: “What is one thing I am doing for students that they could start doing for themselves?”

That question might save you time, build student ownership, and make next week feel a little less like educational whack-a-mole.

That is all from the lounge this week.

Catch you next time.