0–10 min
Introduction & Framing – Why Data Drives Transformation
• Overview of challenges with traditional data use and “data dumps.”
• Connect to closing gaps, personalization, and systemic change.
• Poll: “What’s your biggest data challenge?”
• Pair-share: Discuss one success and one frustration with current data systems.
10–30 min
Collecting Meaningful Data
• Identify essential assessment points and observation metrics.
• Demonstrate templates for efficient data collection. • Hands-on: Participants select relevant data sources from sample school datasets.
• Table activity: Organize data to reveal patterns.
30–55 min
Analyzing & Translating Data Into Action
• Teach methods to convert raw data into visual dashboards and actionable insights.
• Focus on closing achievement gaps and informing personalized instruction.
• Guided work: Participants create a one-page visual summary and draft a 90-second narrative for a classroom or school team.
• Peer feedback: Triads review and refine clarity and actionability.
55–75 min
Using Data to Personalize Learning & Build Sustainability
• Discuss practical ways to adjust instruction, groupings, and supports.
• Introduce a cycle for reviewing and iterating weekly. • Hands-on: Teams design a “data-to-action” weekly rhythm, including review meetings, check-ins, and follow-ups.
• Gallery walk: Share plans with peers for feedback.
75–90 min
Commitments & Next Steps
• Reflect on immediate changes participants can implement in classrooms or PLCs.
• Connect sustainable data practices to long-term transformation. • Individual reflection: Write first 10-day actions.
• Exit poll: “Which step will you implement first?”
Learning Outcomes
By the end of this session, participants will be able to:
1. Identify key metrics and assessment data that reveal achievement gaps and instructional opportunities.
2. Analyze and visualize data in ways that inform differentiated, personalized learning strategies.
3 .Design a sustainable data-use cycle that supports long-term instructional improvement and whole-school transformation.
David, J. O. (2025). Redefining assessment for sustainability: A reflective examination of adaptive and student-centered learning strategies. Frontiers in Education, 10, Article 1553999. https://doi.org/10.3389/feduc.2025.1553999
Du Plooy, E. (2024). Personalized adaptive learning in higher education. Frontiers in Psychology, 15, Article 11544060. https://doi.org/10.3389/fpsyg.2024.11544060
Kochmar, E., Do Vu, D., Belfer, R., Gupta, V., Serban, I. V., & Pineau, J. (2020). Automated personalized feedback improves learning gains in an intelligent tutoring system. Proceedings of the 13th International Conference on Educational Data Mining, 2020, 1–10. https://arxiv.org/abs/2005.02431
Pearson Education. (2024). The key to personalized learning? Personalized assessment. https://www.pearsonassessments.com/large-scale-assessments/blog-webinars/blog/2024/05/the-key-to-personalized-learning-personalized-assessment.html
Shemshack, A. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7(1), Article 9. https://doi.org/10.1186/s40561-020-00140-9
Back
Trips and Tours
