Using Data 4-Part Series
Using Data's Instructional Leadership Four-Part Series
TERC's Using Data offers a four-session professional development program for data leaders, data coaches, and data teams. This series of workshops will enable you to maximize use of data to create a high-performing school for the educators, students, and parents in your local educational community.
Through this series, you'll learn how to:- Launch a high-performing data team;
- Apply a four-step collaborative process for data inquiry;
- Drill down into state and local data, including student work;
- Identify student learning problems and goals;
- Address the underlying causes of student learning problems in order to plan effective intervention strategies.
- How can we organize ourselves for collaboratve inquiry?
- What are our core commitments to improvements at all levels of achievement? Learning Goals:
- Understand Using Data Process;
- Understand roles and responsibilities of data coach and data team members;
- Understand data inquiry process and its implementation requirements, including the shifts in culture, data use, collaboration, and instructional improvement that result from effective collaborative inquiry;
- Understand Data-Driven Dialogue and how it differs from other discussion or conversation;
- Use data and planning tools to assess current uses of data.
- How can we use the data we have to formulate a Student Learning Problem/Goal?
- What is the benefit of data triangulation?
- What are the issues and potential hazards surrounding analyzing data with data teams? Learning Goals:
- Understand the use of aggregate, disaggregate, strand, and item level data;
- Understand triangulation of multiple data sources and develop plans for analyzing multiple measures of student learning;
- Understand how to use disaggregated data to pinpoint achievement gaps for individual students and student groups;
- Understand how to facilitate drill down: aggregate, disaggregate, and strand item.
- What is our Student Learning Problem/Goal?
- How do different types of data support each other? Learning Goals:
- Understand how to analyze student work;
- Understand how to analyze common assessments and other local student learning data sources;
- Accurately identify a weakness in student understanding through analysis of item level data, student work, and triangulation of multiple data sources.
- How can we be sure that the causes of our Student Learning Problem are grounded in research and our own local data, and do not blame students' failure on causes that are out of our control?
- How do we engage our team in conducting and compiling relevant research?
- How do we verify the causes of our Student Learning Problem?
- How will this process help us generate solutions for Student Learning Problems? Learning Goals:
- Understand how to conduct cause-and-effect analysis;
- Learn how to formulate research questions;
- Understand why and how to conduct equity checks;
- Develop local data research questions to verify the "extent" of research supported conditions;
- Identify sources of local data; create additional sources needed to verify causes.
Session 1: Launch a High-Performing Data Team
Essential Questions:Session 2: Data Analysis Part I: Build Data Literacy and Drill Down
Essential Questions:Session 3: Data Analysis Part II*
Essential Questions:(Please note: Session 2 is a prerequisite for Session 3.)
Session 4: Verify Causes of Learning Gaps
Essential Questions:Contact us for more information about registering for a workshop or scheduling a professional development program at your school! Call 617.873.9793 for details.
