Welcome! Find your “vertical team” table Be sure you know everyone at your table. We will begin at 8:30!

How do we know the district curriculum is being implemented in our classrooms?  What are our barriers to implementation?  Innovation Configurations by Level  Learning Walks at Maplewood Richmond Heights  OCG/UBD – Stage I – Observations

How do we know the district curriculum is attained? Learned and retained!

Parkway Graduate? You are a professor at a University… You are a professor at a Community College… You are a “boss”…

5 SEEHEAR The first month you are with this Parkway Graduate?

Draw a picture of the Parkway Graduate and identify the desired characteristics…

What does our data tell us about the attained curriculum?

Keeping our eye on the goal…  What does our data tell us about how well we are preparing the Parkway graduate for the 21 st century?

We will be looking at…  5 th grade district MAP data  8 th grade district MAP data  High School ACT scores

10 Looking in the mirror…  Imagine you are in a special, mirrored meeting room where you can observe your reflection.  What do you see yourself doing to help the group focus, hear one another and support the development of shared understanding about the data that we will review?  Take a minute to record the specific, observable behaviors group members see themselves doing and/or hear themselves saying?

 Data mean nothing alone – The key is in the facilitation of effective conversations around what the data tell us.

Nancy Love’s Assumptions

13 Effective data conversations takes place when…  There is mutual trust among group members  Data is not used to place blame or point fingers  Everyone needs to understand what the data being presented represents and how it was derived  Everyone must acknowledge that they play a role Adapted from “The Data Dialogue”, Laurie Olsen

14 Data Driven Dialog  Phase 1: Predictions - Surfacing of perspectives, beliefs, assumptions, predictions, possibilities, questions, and expectations.  Phase 2: Observations – Examining and analyzing the data for patterns, trends, surprises, and new questions that “jump” out.  Phase 3: Inferences – Generating hypotheses, inferring, explaining, and drawing conclusions. Defining new actions and interactions and the data that is needed to guide implementation (monitor) and build ownership for decisions. Based on the work presented by Nancy Love, author of Using Data/Getting Results, (2002).

Phase I - Predictions  Phase I Predictions dialogue takes place before you see the data. During this time, you activate prior knowledge, surface assumptions, and make predictions, thus creating readiness to examine and discuss the data. You hear and honor all assumptions and ideas as “building blocks for new learning.”

5 th & 8 th grade district MAP scores and ACT Scores

Private Think Time  Please reflect privately and record several of your preliminary thoughts about the data. One or more of the following thought-starters might be helpful. (You will share your reflections in your first session.)  I assume ……….  I predict ……  I wonder …  My questions / expectations are influenced by ………..  Some possibilities for learning that this data may present …

Move to three different groups…  Phase 2: Observations – Examining and analyzing the data for patterns, trends, surprises, and new questions that “jump” out.  Phase 3: Inferences – Generating hypotheses, inferring, explaining, and drawing conclusions. Defining new actions and interactions and the data that is needed to guide implementation (monitor) and build ownership for decisions

Schedule  9:05-9:40 Group 1  9:40-9:50 Break  9:50-10:20 Group 2  10:25-10:55 Group 3  10:55 Stay in vertical team and debrief (questions provided) Group 1: Lisa Group 2: Becky Group 3: Tim 11:15-11:45 Level Group Debrief 19

Vertical Team Debrief  After seeing three levels of data, what connections do you see to:  Classroom implementation  Current initiatives 20

Level Debrief  What questions can you pose to provide insight into our work?  Criteria:  Questions!  Questions that we can collect data on