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Getting Started

In addition to ensuring interoperability, privacy, and security, data systems can also capture and aggregate massive amounts of student data. To begin configuring these systems such that they can also be used to measure program implementation and/or their effects on teacher practice as well as student learning, it is important to first understand key components that both influence and inform instructional decisions. Explore these key resources to learn more about what these strategies and models look like in action.

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Most Popular Resources for Data Systems Administrators

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Recovering Capacity by Using AI for Lesson Planning and Creating Instructional Materials

Streamlining Lesson Planning with Generative AI

Individual Check-ins for Student Success

Individual Check-Ins to Foster Communication and Growth in Dual Enrollment

Teacher gestures at computer screen while meeting with student
1:1 Data Conferences

Students and teachers frequently conference to ensure students understand their data and use it to improve their learning

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Creating Real-World Publications with AI

Supporting Students to Use AI in Producing Work for Real-World Audiences

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Working with Industry Partners to Design Real-World, AI-Enhanced Projects

Enhancing Work-Based Challenges With AI-Driven Research and Prototyping

Building Time Management through Calendar Look-Aheads

Developing Planning Habits for Academic Balance in Dual-Enrollment Courses

Building Connections in Virtual/Hybrid Dual Enrollment Classes

Incorporating Team-Building for Stronger Relationships and College Readiness

Self-Assessments for Student Growth

Building Reflection, Goal-Setting, and Self-Advocacy Skills in Dual Enrollment

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Extending Existing Projects with AI

Using AI to Deepen and Expand the Impact of Projects You Already Teach

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Data Dashboard for Progress Monitoring

Teacher uses data dashboard to understand where each student is in their learning pathway

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Remote Learning: Planning for Improvement

Power Moves for Remote Learning

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Data Systems Administrator Voices
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We know that the theory of personalized learning is powerful but the actual nuts and bolts of implementations is extremely difficult. A lot of the work that TLA does from the practices website to their data work make personalized learning concrete with voices from actual teachers and administrators who are practitioners.
Innovation Directors Network (IDN) Participant