I’ve been running daily Google Scholar alerts tied to my dissertation work, and I’ll probably keep them on for the rest of my career.
What started as research support has become something more important:
Reading research articles is a way to stay grounded in what’s actually happening as AI rapidly reshapes how people learn.
Here are five themes that stood out this week:
1. AI tutors are changing how students think
Not just improving outcomes.
Research is pointing to shifts in metacognition and self-regulation, which is far more important than surface-level performance gains.
2. Adaptive AI in autism is focused on optimization
Reinforcement learning systems are being used to adjust:
task sequencing
feedback timing
engagement
This raises a real question:
Are we building learning systems… or behavioral optimization tools?
3. “Students as prompt engineers” is gaining traction
There’s a growing push to treat prompting as a core academic skill.
I’m not convinced.
This feels less like a discipline and more like a workflow.
4. Self-regulated learning keeps showing up everywhere
Across multiple studies, one thing is consistent:
AI benefits learners who already know how to manage their own learning.
For others, it can quickly become a crutch.
🔗 https://lnkd.in/gjfuzaND
🔗 https://lnkd.in/giE7_VZS
5. Human + AI is being framed as the new model
Collaboration between learner and AI is the direction.
But most research still doesn’t define:
what structure works
what scaffolding is needed
where human judgment fits
That gap matters.
If you’re in education, EdTech, or training:
This isn’t optional anymore.
Understanding how AI is shaping learning is becoming a baseline skill.
Robert Foreman
DET Student, Central Michigan University
📧 forem1r@cmich.edu
🌐 https://nhancedata.com