Preparation, belonging, jobs, and the hidden work of student success
AI’s student benefits, retention’s growing importance, and what the numbers leave out
Predictions, metrics and models are only the beginning
Affordability, definitions, suspicious exams, and other reasons to read the fine print
When our assumptions about students, employers, and AI stop matching reality
The trouble with translation
Why student success increasingly depends on interpretation, navigation, and relational guidance
A miscellany of charts, questions, and mild skepticism
Pulling students out of the river isn’t a strategy
The recurring blind spot in EdTech’s promises of frictionless scale
The short-term success trap
Looking beneath the surface
