Overview
We are seeking volunteers (teams of classroom teachers and building leaders) to participate in an action research project to investigate the effect of AI-Powered Inquiry Sequences (AIS) on student learning and achievement. Using a quasi-experimental design, the study will determine how AI can best scaffold implementing the Marzano Inquiry Sequences Framework to foster deeper learning and improve academic achievement.
Powered by Marzano's (2014) structured questioning framework, students will progress through four phases of inquiry: 1) Detail Questions, 2) Category Questions, 3) Elaboration Questions, and 4) Evidence Questions. Effect size calculations will quantify the impact of AIS on student achievement.
Participant Expectations
• Participate in 3 90-minute online workshops with Drs. Marzano & Magana at no cost.
• Anonymously share Effect Size data with the researchers. Required Text: Questioning Sequences in the Classroom (Marzano & Simms, 2014)
Workshop Sessions
Session 1—Wed. October 1, 2025, 4:00-5:30 PM Pacific Time. Focus: Understanding Inquiry Sequences for deeper learning; generating sequences with the Marzano Custom AI Protocol.
Session 2—Wed. October 8, 2025, 4:00-5:30 PM Focus: Sharing Impact Stories to identify and highlight best practices from classroom implementation.
Session 3—Wed. October 15, 2025, 4:00-5:30 PM Focus: Generating Classroom Effect Sizes using the REL Central Excel Analysis Tool to measure impact on learning and achievement.
About the Facilitators
Dr. Robert J. Marzano is a leading authority in educational research and practice. His decades of work have bridged research and classroom application, creating frameworks that significantly improve student outcomes.
Dr. Anthony J. Magana is a pioneer in the use of EdTech to enhance teaching and learning. The creator of the acclaimed T3 Framework for Innovation, he empowers educators to leverage EdTech to reliably improve learning outcomes