DATA COACHING WORKSHOP DAY 1 PRESENTED BY SARITA SIQUEIROS THORNBURG, JILL PATNODE & KRISSY SOLTMAN

Transcription

1 DATA COACHING WORKSHOP DAY 1 PRESENTED BY SARITA SIQUEIROS THORNBURG, JILL PATNODE & KRISSY SOLTMAN January 28, 2014

2 Success for Each Child and Eliminate the Opportunity Gap Welcome and Introductions

3 Overview of the Workshop Series Workshop 1 Workshop 2 The big picture Getting Ready and Issues Diagnosing Causes Digging Deeper Plan and Evaluate Application to your context

4 Today s Agenda Welcome and Introduction Exploring vision, purpose and challenges What questions and what data? Understanding Issues

5 Today s Objectives 1. Understand the importance of integrating a racial equity lens into the data inquiry cycle. 2. Learn concepts related to: a. Team readiness for use of data b. Creating focusing questions c. Gathering, displaying and analyzing data d. Understanding underlying causes 3. Apply these concepts and related tools to real-life data and begin construction of data action plan.

6 To download materials:

7 The Four Agreements Stay Engaged Don t Let your heart and mind check out! Experience Discomfort Agree to experience discomfort so that we can deal with issues of race in an honest way. Speak your truth Be honest about your thoughts, feelings and opinions. Say them in a way that is true for you. Expect and accept non-closure Accept that you will not reach closure in your understandings about race and race relations. There is no such thing as a quick fix.

8 What is your level of experience with Racial Equity work? Expert I understand and could teach it to someone else Practitioner I can mostly do it by myself, but I sometimes get stuck. Apprentice I m starting to get it, but still need someone to coach me through it. Novice I m just starting to learn, and I don t really understand it yet.

9 Race Matters Final Word Protocol 1. Read through article highlighting 2-3 key ideas 10 min. 2. Presenter chooses 1 quote from article to read to group, shares why they chose it, and implications 2 min. 3. Group members respond - 1 min. each (3 min. total) 4. Presenter responds to group - 1 min. 5. Repeat process with new presenter

10 Equality vs. Equity

11 Why have a racial equity perspective? Advocates need to make a strong data-based case about racial disparities. Otherwise, discussions about race easily fall off the table, get diverted into side arguments, or default into ideological camps. Sometimes race matters in situations that aren t even presented in racial terms. We need to know when that s the case so that our work can be effective. Most of the time the story behind the initial data is far more complicated than those data reveal. We need to know that story fully so our work can be effective. Sometimes race isn t a major factor, even when a situation is presented as such. Because race so often is a major factor, we need to protect the space for that claim to be made.

12 Success for Each Child and Eliminate the Opportunity Gap 1.0 Getting Ready

13 Does working with data ever feel like this?

14 Don t Be Puzzled!

15 Getting Ready Evaluate Results Identify Issues The Cycle of Inquiry and Action Plan and Take Action Understand the Issue Diagnose Causes

16 1.0 Getting Ready: Overview Vision for data use Evaluate Results Getting Ready Identify the Issue Vision for Data Use The Cycle of Inquiry and Action Plan and Take Action Understand the Issue Getting Ready Diagnose Causes

17 1.2B Data Vision Future Focus Protocol What is your current reality? Where do you hope to be?

18 1.0 Getting Ready: Overview Team self-assessment of capacity Getting Ready Evaluate Results Identify the Issue Vision for Data Use Data Capacity The Cycle of Inquiry and Action Plan and Take Action Diagnose Causes Understand the Issue Getting Ready

19 1.7 Self-Assessment: Data Use Capacity Poll Everywhere -1.4 Poll Everywhere - 1.6

20 Debrief with Team/Journal: Getting Ready 1.0 & Questions

21 Let s Take a Break

22 Success for Each Child and Eliminate the Opportunity Gap 2.0 Identify Issues

23 2.0 Identify Issues: Overview Formulate Initial Questions Vision for Data Use Getting Ready Data Capacity Formulate Initial Questions Evaluate Results Identify Issues Plan and Take Action The Cycle of Inquiry and Action Understand the Issue Identify Issues Diagnose Causes

24 Identify Issues: Attributes of Good Issues 1. The issue is under your direct control. 2. The issue will make a significant difference in terms of helping children or students.

25 2.0 Identify Issues: Scenario Hidden Valley H.S.

26 2.0 Identify Issues: Questions The Hidden Valley High School leadership team identified high school completion of African American students as a priority issue in the school. To what extent do current African American students have safe, healthy, supportive, challenged, and engaging experiences at Hidden Valley High School? African American students (grades 9 12) in Hidden Valley HS

27 2.0 Identify Issues: Questions As a group: Review document Examples of Issues Commonly Investigated Use document 2.1 Identifying and Prioritizing Significant Issues to select an issue appropriate to your organization Use document 2.2 Developing Focusing Questions to Initiate Inquiry to formulate your own focusing question. Complete the top three sections of the Identify and Understand Issues and Diagnose Causes Template

28 Problem Statement Worksheet: Questions

29 2.0 Identify Issues: Overview Identify Useful Data Vision for Data Use Getting Ready Data Capacity Formulate Initial Questions Evaluate Results Plan and Take Action The Cycle of Inquiry and Action Identify Issues Understand the Issue Identify Issues Identify Useful Data Diagnose Causes

30 Identifying Issues: Data By Victoria L. Bernhardt 5. How have families and students of color been involved to share perceptions of the Learning Environment? 6. How have community conditions, including racial inequities, been documented?

31 2.3 Sources of Data To provide the team with a protocol to follow when attempting to find data to answer a focusing question. 10 minutes

32 Debrief with Team/Journal: Identify Issues & Questions

33 Finish Process Summary, Stages 1 & 2

34 Lunchtime!

35 Success for Each Child and Eliminate the Opportunity Gap 3.0 Understand Issues

36 3.0 Understand Issues: Overview Display data for understanding Vision for Data Use Data Capacity Getting Ready Formulate Initial Questions Evaluate Results Identify Issues Identify Useful Data Display Data Plan and Take Action The Cycle of Inquiry and Action Understand the Issue Understand the Issue Diagnose Causes

37 Types of Data Displays

38 Data Display Checklist As a team use the Data Display Checklist and Sample Data Display to evaluate the quality of the data display in document 10 Minutes

39 Race Matters Advancing Better Outcomes for All Children - A-B Each Teach Protocol Read Selection (15 min.) Both partners read intro Partner A reads bottom of page 1- page 4 Partner B reads page 5- end Summarize and Teach (5 min each) Partner A summarizes and teaches key points to Partner B Partner B summarizes and teaches key points to Partner A

40 3.1 NCES Which Graph to use? nces.ed.gov/nceskids

41 3.1 Data Displays Time to create a data display: What is your question? What are the data elements you ve identified? What would NCES recommend for the chart format (i.e., Pie, Bar, etc.)? If you have your own program data, use it if not, use data from document Hidden Valley Sample Data, or, just make it up! Have fun with it! Reflect on the quality data display check-list.

42 3.0 Understand Issues: Overview Analyze the data Vision for Data Use Data Capacity Formulate Initial Questions Evaluate Results Getting Ready Identify Issues Identify Useful Data Display Data Plan and Take Action The Cycle of Inquiry and Action Diagnose Causes Understand the Issue Understand the Issue Analyze Data

43 Analyze Data: Data Carousel What is a Data Carousel?

44 Learning to See, Unlearning to Judge Factual Observations are a statement about what the data say without any interpretation. are the first step in the data analysis process and they provide the basis for making sound inferences. Not all observations are factual Observations can be colored by biases, assumptions, prejudice

45 Observation vs. Inferences The majority of students in the Hidden Valley School District are from middle economic class families. More minority students are enrolled in the FRPL program than white students in Hidden Valley. About one quarter of the students in the Hidden Valley School District were enrolled in the FRPL program in

46 Percent of Washington state 8th graders who met standard on the math MSP by Race and Ethnicity ( ) Source: OSPI Report Card American Indian Asian Black/African-American Hispanic Pacific Islander White Strengths: Concerns: Clarifying Questions:

47 3.5B Analyze Data: Data Carousel Now, you get to experience a minicarousel. Review each of the data display mock-ups, and record your objective statements in these categories: Objective Observations (Noticings) Strengths and Concerns Clarifying Questions (Wonderings)

48 3.5 Analyze Data: Other Protocols

49 Debrief with Team/Journal: Understand Issues

50 Let s Take a Break

51 Let s Recap- Example Focusing Question: To what extent do current African American students have safe, healthy, supportive, challenged, and engaging experiences at Hidden Valley High School?

52 Hidden Valley Data Domain Averages by Gender and Race/Ethnicity: Diversity Policies and Practices Domain Average SD N 90 % Conf. Int. Gender Males Females Race/Ethnicity American Indian or Alaskan Native Asian American or Pacific Islander Black or African American Two or more races White Latino Note. SD = sample standard deviation. N = number of respondents. Averages for all domains are based on a scale of 1 to 4, with 1 being the undesirable end and 4 being the desirable end. High scores reflect more positive school climate. Dashes are printed where results are not reported for groups with fewer than ten respondents.

53 Example Data: Observations Hidden Valley scores Low, Very Low, or Moderately Low on eight of ten domains on the School Diversity Inventory Faculty/Staff Survey On all domains of the School Diversity Inventory Student Survey, Hidden Valley scores below 3.0 African American students have the lowest average rating for five of ten domains on the survey 56.7% of Black/African American students are above the cutoff point for having opportunities for prosocial involvement The majority of class of 2011 African American students who dropped out left in their fourth year 75% of African American families agree the school encourages them to be involved compared to 78% of all parents 51% of African American families believe teachers are able to connect with kids like mine

54 Summarize and Prioritize Concerns Comments Group concerns by similar observations/comments Use sticky dots to allow each team member to rank the groups Draft problem statement based on highest concern

55 Problem Statement Worksheet: Data Observations & Draft Problem Statement What do the data say about the focusing question? Hidden Valley scores Low, Very Low, or Moderately Low on eight of ten domains on the School Diversity Inventory Faculty/Staff Survey On all domains of the School Diversity Inventory Student Survey, Hidden Valley scores below 3.0 African American students have the lowest average rating for five of ten domains on the survey 56.7% of Black/African American students are above the cutoff point for having opportunities for prosocial involvement The majority of class of 2011 African American students who dropped out left in their fourth year 75% of African American families agree the school encourages them to be involved compared to 78% of all parents 51% of African American families believe teachers are able to connect with kids like mine Draft Problem Statement Using multiple measures, African American students and their families at Hidden Valley High School have a less positive experience than other students and families.

56 Problem Statement Worksheet: Data Observations & Draft Problem Statement What do the data say about the focusing question? Draft Problem Statement

57 Success for Each Child and Eliminate the Opportunity Gap 4.0 Diagnose Cause(s)

58 4.0 Diagnose Causes 4.1 Identify and articulate the major problem behind an issue. Evaluate Results Plan and Take Action Vision for Data Use Vision for Data Use Getting Ready The Cycle of Inquiry and Action Diagnose Causes Data Capacity Formulate Initial Questions Identify Issues Understand the Issue Identify Useful Data Display Data Analyze Data Diagnose Causes Diagnose Root Cause

59 Root Cause: That ONE Thing

60 4.2 Diagnose Cause: Protocols 1. As a team, review the 3 Root Cause Protocols: 4.2A Why? Why? Why? Protocol 4.2B 20 Reasons Protocol 4.2C Fishbone Analysis Protocol 2. Select 1 of the 3 protocols and apply it to your selected issue/concern.

61 Debrief with Team/Journal: Process Summary for Section 3

62 5.0 Plan & Take Action 6.0 Evaluate Results Vision for Vision Data for Use Data Use Getting Ready Data Capacity Formulate Initial Questions ID Data Elements to Collect Short-Term, & Long-Term Goals Evaluate Results Evaluate Results Identify Issues Identify Useful Data Plan and Take Action The Cycle of Inquiry and Action Diagnose Causes Understand the Issue Display Data Analyze Data Select Strategies & Write the Plan Describe Preferred End State Plan and Take Action

63 Questions

64 End of day and debrief