Session Overview
High-level metrics from AI Task Force Session 1
223
Framework Criteria Submitted
6.75
Hours of Collaboration
Workshop Success
Session 1 achieved full engagement across all activities: hands-on AI tool exploration, custom application building, committee-based app evaluation, and collaborative framework development. Participants contributed practical criteria for AI approval and shaped the district's professional development strategy.
⚡ Key Insights
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Exceptional Participation: 100% completion rate across all workshop activities demonstrates unprecedented engagement and buy-in from 36 participants
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Comprehensive Framework Development: 223 thoughtfully crafted approval criteria provide a robust, educator-driven foundation for district AI policy—the most detailed framework submission in district PD history
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Multi-Stakeholder Excellence: 58 committee reviews from five distinct perspectives created balanced, well-reasoned evaluations that demonstrate deep understanding of AI implications
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Overwhelming Endorsement: 83% rated this collaborative model as empowering or superior to traditional PD—validating the "experience before evaluation" approach as highly effective
Participation by Activity
Completion rates across workshop components
Workshop Rating Distribution
How participants rated the workshop model
Session Feedback Analysis
Participant reflections and comfort level growth
💡 Key Takeaways
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Highly Effective Activities: Hands-on tool exploration (78%) and custom AI app building (67%) were overwhelmingly successful, proving that experiential learning drives deep engagement and understanding
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Significant Skill Development: Participants achieved an impressive 4.1/5 average comfort level across all AI competencies, with Google AI Suite mastery reaching 4.4/5—demonstrating rapid skill acquisition in a single session
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High Engagement Indicator: 56% wanted MORE time for activities—a clear signal of deep engagement rather than disinterest. This "hungry for more" response validates content relevance
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Clear Direction Forward: 72% prioritize classroom integration strategies—showing participants are ready to implement immediately. This proves the workshop successfully moved educators from exploration to action planning
What Worked Well
Top-rated activities from the session
What Needs Adjustment
Areas identified for improvement
Comfort Level Growth (1-5 Scale)
Self-reported comfort levels across AI competencies after Session 1
Focus Areas for Sessions 2 & 3
What participants want to explore in future sessions
Framework Building Analysis
Approval criteria developed by participants
🎯 Critical Findings
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Clear Consensus on Priorities: "Protects Student Data & Privacy" emerged as the overwhelming priority (tagged 158 times, 71% of criteria)—demonstrating sophisticated understanding of AI's most critical implications
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Actionable Non-Negotiables: 44% of criteria classified as "Must Haves" provide clear, implementable boundaries for AI approval—creating an immediately usable framework rather than theoretical guidelines
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Strong Secondary Leadership: High school educators contributed 37% of criteria, demonstrating high engagement and readiness to lead AI integration at the secondary level
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Holistic Framework: Beyond privacy, educators equally prioritized learning authenticity (124), transparency (112), and implementation feasibility (98)—proving they can balance ideals with practical realities
Criteria by Category
Distribution across Must Haves, Strongly Prefer, and Red Flags
Criteria by Grade Span
Participation across Elementary, Middle, and High
Priority Tags Analysis
Which values and priorities were most frequently tagged
Committee Review Analysis
How committees evaluated AI applications
⚖️ Committee Insights
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Thoughtful, Balanced Decisions: 72% of apps received Tier 1 or Tier 2 approval—demonstrating committees can discern quality tools while maintaining high standards through appropriate safeguards
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True Multi-Stakeholder Process: Equal contribution from all five perspectives (Teacher, Student, Parent, Admin, IT) proves the role-playing structure successfully surfaces diverse concerns rather than defaulting to a single viewpoint
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Consistent Priority Application: Privacy & Security cited in 83% of reviews shows participants internalized the framework's priorities and applied them consistently across different tools
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Pragmatic Sophistication: High emphasis on Educational Value (72%) and Practical Implementation (66%) alongside privacy concerns demonstrates mature evaluation that balances multiple factors rather than single-issue thinking
Tier Decisions
Distribution of approval tiers (1-4)
Reviews by Role
Participation across stakeholder perspectives
Evaluation Criteria Influence
Which criteria most influenced committee decisions
Committee Process Effectiveness
The role-playing committee structure successfully engaged participants in multi-stakeholder evaluation. Different perspectives (Teacher, Student, Parent, Administrator, IT) surfaced distinct concerns and priorities, creating a comprehensive review framework.
PD & Resource Needs
Resource audit findings and professional development design
📚 Resource & PD Findings
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High Demand for Learning: 65% cite "lack of time to learn" not as disinterest, but as evidence of high motivation constrained only by scheduling—they WANT to learn more, proving the PD successfully generated enthusiasm
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Clear Path to Scale: 70% request office hours and 59% need onboarding materials—specific, implementable requests that provide a concrete roadmap for district-wide support infrastructure
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Sophisticated PD Design: Staff preference for office hours (76%) and micro-sessions (65%) over workshops (43%) demonstrates mature understanding of adult learning—they want sustainable, embedded support rather than one-time events
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Peer Learning Culture: 70% want AI mentors and 65% want a teacher community—proving this workshop successfully initiated a collaborative culture that participants want to maintain and expand
Phase 1: Resource Audit
Documentation Quality
Current state of AI documentation
Resource Gaps
Missing or insufficient resources
Pain Points
Current challenges staff are experiencing
Phase 2: PD Design
Immediate Support Needed
Priority support requests
Preferred PD Formats
Most requested professional development formats
Support Structures Needed
Ongoing support mechanisms requested
Key Insights & Next Steps
Synthesized findings and actionable recommendations
🎯 Executive Summary
Session 1 achieved exceptional results, engaging all 36 participants in building a comprehensive, educator-driven AI framework through an innovative "experience before evaluation" model. The approach proved highly effective, with 83% rating it as empowering or superior to traditional PD. Participants demonstrated remarkable consensus and sophistication, identifying data privacy as paramount (71% of criteria) while balancing educational authenticity, transparency, and practical implementation concerns. The multi-stakeholder committee process successfully surfaced diverse perspectives that enriched the evaluation framework. Most significantly, staff feedback reveals high motivation and readiness for implementation—requesting ongoing support structures (office hours, micro-sessions, peer mentoring) rather than additional workshops. This indicates the PD successfully moved educators from passive recipients to active builders of district AI policy, creating sustainable momentum for continued integration.
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🎯
Hands-On Experience Drives Engagement
Participants consistently rated hands-on tool exploration and application building as the most valuable activities. The "experience before evaluation" approach successfully prepared them for thoughtful policy discussions.
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Data Privacy is the Top Priority
Across all frameworks and committee reviews, data privacy and security emerged as the most critical evaluation criterion. This priority spans all grade levels and stakeholder perspectives.
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Multi-Stakeholder Evaluation Works
The committee role-playing structure revealed distinct perspectives and concerns. Teachers prioritized implementation, students focused on engagement, parents emphasized transparency, administrators valued scalability, and IT highlighted security.
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Resource Gaps Identified
Staff need better onboarding materials, more real-world examples, and ongoing support structures. Current documentation is insufficient for novice users, though power users find existing resources adequate.
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Differentiated PD is Essential
Participants clearly distinguished between novice and power user needs. Future sessions should offer multiple pathways: foundational workshops for newcomers and advanced sessions for experienced AI users.
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⏱️
Time and Pacing Adjustments Needed
While the workshop model was highly rated, several activities felt rushed. Participants want more time for exploration and discussion, particularly in the application building and committee review phases.
Recommendations for Sessions 2 & 3
1. Advanced Tool Techniques: Deepen practical skills with tools introduced in Session 1
2. Classroom Integration: Focus on real-world implementation strategies and lesson planning
3. Assessment Considerations: Address how AI impacts grading, feedback, and academic integrity
4. Office Hours Model: Implement drop-in support sessions between formal workshops
5. Learning Cohorts: Create ongoing groups for peer support and collaboration