Scan the cohort roster for at-risk and disengaged learners
Decides which actions to take, in what order, toward a goal.
You might say…
“Someone dropped off three weeks ago and I only noticed when they didn't submit. I need the system to tell me before it's too late.”
What it does
Autonomously monitors engagement and progress signals across the full cohort roster and surfaces a ranked list of learners who warrant a personal nudge.
Trigger: Use on a scheduled cadence across the cohort — weekly or at key milestones — to surface at-risk learners before disengagement becomes dropout.
I/O: Cohort engagement and progress data (logins, submissions, completions) → ranked at-risk list with risk signals per learner
Autonomy: Acts autonomously — runs end-to-end without a human in each loop.
Recognise the problem?
The primitives are the commodity part. The fastest next step is a conversation about composing them into something that works for you.
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