Analytics / Behavior Analytics
🤝 Behavior Analytics

Behavior Analytics

Behavior incidents, positive behavior, restorative practices, interventions and outcomes, trends, classroom referrals, student reflections, and well-being indicators — with AI-generated behavior insights. All figures are fictional sample data created for demonstration.

A supportive lens. Behavior data here is used to understand needs and offer support, not to punish or label. This dashboard follows a PBIS and restorative-practices framework — emphasizing teaching expectations, repairing harm, and connecting students to the right supports.
Office Referrals
0
▼ 19% vs. last term
Suspensions
0
▼ 33% vs. last term
Positive Recognitions
0
▲ 22% this term
Restorative Resolutions
0
▲ 9% resolved

Behavior Incidents ▼ Trending down

Incidents declining as positive supports scale up.

Positive Behavior

0%Met expectations

91% of students met PBIS expectations this week.

Restorative Practices

Restorative chat
84%
Peer mediation
79%
Circle process
72%
Re-entry plan
68%

% of cases resolved without recurrence (fictional sample).

Classroom Referrals — Type × Month

Darker = more referrals (an area to support, not to penalize). Fictional sample data (band 0–4).

Referral type
Sep
Oct
Nov
Dec
Jan
Feb
Disruption
14
11
9
7
6
4
Off-task
10
9
7
6
4
3
Conflict
6
5
5
3
3
2
Tardy/transition
9
7
6
5
4
3
Fewer Mid More

🛠️ Behavior Intervention Outcomes — click to expand

▸Check-in / Check-out (CICO) — 24 students81% improving

Daily point card with a named mentor and family communication. 81% of students reduced referrals within 6 weeks; 3 students transitioned back to Tier 1. Continue and fade support gradually.

▸Social-emotional skills group — 16 students74% improving

Small-group lessons on self-regulation and conflict resolution. 74% showed fewer classroom incidents; reflection quality improved. Pair with classroom reinforcement.

▸Restorative re-entry plans — 9 students68% resolved

Structured re-entry after time away, repairing relationships and clarifying expectations. 68% had no recurrence; remaining students moved to a coordinated Tier 3 support plan with the team.

Behavior Trends

Fictional sample behavior trends by grade band.
Grade bandReferrals (term)Positive : referralTrend
K–5938 : 1 Improving
6–82114 : 1 Watch
9–121222 : 1 Improving

Positive-to-referral ratio is a healthier signal than raw counts.

Student Reflections

  • This week
    32 restorative reflections completed; common theme: needing a calm space to reset.
  • In progress
    Goal-setting check-ins with CICO students.
  • Planned
    Student-voice survey on classroom climate.

Reflections are growth tools, kept private and used supportively.

Well-Being Indicators

82%
Sense of belonging
88%
Has a trusted adult
3.9/5
Self-reported well-being
▲ 6%
Connectedness trend

Behavior and well-being are connected. For the full picture, visit the Well-Being Dashboard →

✨ AI Behavior Insights Simulated

In this fictional sample, behavior incidents are down 19% and suspensions down 33% as positive recognitions (▲22%) and restorative practices scale. The strongest remaining signal is Grade 6–8 classroom disruption, concentrated early in the day and during transitions — and most disruption-flagged students also appear on the attendance watchlist, suggesting a shared root cause. Recommended priorities: continue CICO (81% improving), strengthen morning and transition routines in middle grades, and coordinate behavior plans with attendance and well-being supports.

👤 Educator decides AI analysis on fictional sample data — transparent, strengths-based decision-support reviewed by educators. Behavior data is handled supportively (PBIS/restorative), never to punish or label. Open the AI Risk Engine →

✨ AI Risk Engine 🛠️ Plan a Behavior Support 💛 Well-Being Dashboard

All data shown is realistic fictional sample data created for demonstration. Behavior data is presented supportively within a PBIS / restorative-practices framework.