AI-powered MTSS intervention plan generator producing SMART goals and suggested interventions that educators can review and edit¶

Element · All elements
Evidence · 2 claims (2 for) · 3 studies (2 design, 1 qualitative), q2 · 0 of 3 report an effect size · 1 claim rests on one study

Description¶

The AI-powered MTSS plan generator is a co-designed tool that "produces SMART goals and suggested interventions to dramatically reduce planning time." It is customizable to local context, allowing schools to adapt intervention menus and templates and vary the tool by role. Recommendations are "reviewable/editable by educators and not fully automated, to preserve trust and teacher judgment," reflecting educators' desire for controlled use of AI rather than full automation.

Design Implications¶

Context¶

Requirements¶

• Requires local customization of intervention menus and templates and role-based configuration (e.g., teachers, interventionists, attendance teams).

Constraints¶

• The report notes adoption funnel data showed teachers used the AI primarily for consumption (reading profiles) rather than creation (logging plans), prompting further investigation.

Target Learners¶

• Ninth-grade high school students supported by student support teams

Target Learning Goals¶

• Faster, consistent intervention planning that maintains educator professional judgment

Claims¶

• Fragmented data systems made intervention planning slow and burdensome, with educators spending 2-3 hours building a single student intervention plan [+W]
• Pilot engagement was strong with month-over-month user retention, and teachers used the AI primarily for consumption rather than creation [+W]

Related Elements¶

• AI-enabled SST/MTSS meeting agenda tool built on Solara's custom configuration
• Freshman On-Track dashboard aggregating attendance, grades, discipline, and momentum scores into a single student view

Examples¶

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Key Sources¶

• Cocuzza, B., Noakes, S., Aso, C., Vollavanh, A., Goldschmidt, L., and Bennett, K. (2026, August). From Data Silos to Student Success: The CICS and Innovare Co-Design Approach to AI-Driven Intervention. Digital Promise. https://doi.org/10.51388/20.500.12265/304