Dean of Students
Manage student conduct referrals and disciplinary processes
What You Do Today
Review behavior referrals from teachers, investigate incidents, determine appropriate consequences or interventions, and communicate with families. Balance accountability with maintaining student engagement.
AI That Applies
AI analyzes referral patterns to identify trends—time of day, location, referring teacher, student demographics—and flags disproportionality. Automated systems track consequence consistency across similar incidents.
Technologies
How It Works
The system ingests referral patterns to identify trends—time of day as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Pattern recognition in discipline data improves dramatically, helping deans address systemic issues rather than just individual incidents.
What Stays
Every discipline situation involves a unique student with a unique story. Determining fair and developmentally appropriate responses requires empathy, cultural awareness, and relationship context that AI cannot replicate.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for manage student conduct referrals and disciplinary processes, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long manage student conduct referrals and disciplinary processes takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your department chair or principal
“Which steps in this process are fully rule-based with no judgment required?”
They influence which ed-tech tools get approved and funded
your instructional technologist
“What's the error rate on the manual version, and what would "good enough" look like from an automated version?”
They support the tech stack and can show you capabilities you don't know exist
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.