Unified Improvement Planning: Root Cause Analysis (School Level) Hosted by: Colorado Department of Education Provided by : Center for Transforming Learning and Teaching.
Download ReportTranscript Unified Improvement Planning: Root Cause Analysis (School Level) Hosted by: Colorado Department of Education Provided by : Center for Transforming Learning and Teaching.
Unified Improvement Planning: Root Cause Analysis (School Level) Hosted by: Colorado Department of Education Provided by : Center for Transforming Learning and Teaching Introductions Center for Transforming Learning and Teaching Julie Oxenford-O’Brian Mary Beth Romke Colorado Department of Education Christina Larson Erin Loften Lisa Medler Session Purpose Ensure planning teams are prepared to identify root causes of priority performance challenges as part of unified improvement planning. Introductions Share: – Name, Job Title, School/District – Your role in supporting unified improvement planning within the district – Your most burning question about root cause analysis Write your question on a sticky note. Materials The materials used during this session were developed in partnership with the Center for Transforming Learning and Teaching in the School of Education and Human Development at the University of Colorado Denver. Norms The standards of behavior by which we agree to operate while we are engaged in learning together. Session Outcomes Engage in handson learning activities and dialogue with colleagues. Access additional resources. Complete followup activities. • Evaluate notable trend statements and priority performance challenges using the UIP quality criteria. • Describe how data other than performance data is used in root cause analysis. • Inventory locally available data. • Identify root cause(s) of at least one priority performance challenge. • Plan for completing root cause analysis. • Plan for finalizing the data narrative. Agenda Role of Root Cause Analysis Priority Performance Challenges Identify Root Causes More than Performance Data Finalize the Data Narrative Unified Improvement Planning Processes Preparing to Plan Gather and Organize Data Section III: Data Narrative Review Performance Summary UIP Handbook, p. 3 Section IV: Target Setting Describe Notable Trends Ongoing: Progress Monitoring Section IV: Action Planning Prioritize Performance Challenges Identify Root Causes Set Performance Targets Identify Major Improvement Strategies Identify Interim Measures Identify Implementation Benchmarks Colorado Unified Planning Template Major Sections: I. Summary Information about the school or District II. Improvement Plan Information III.Narrative on Data Analysis and Root Cause Identification IV.Action Plan(s) Section I Summary Information about the School/District Section II Section III Additional Information about the School/ District Section IV Progress Monitoring of Prior Year’s Targets School Target Setting Form Priority Performance Challenges Data Worksheet Annual Performance Targets Notable Trends (2 years) Priority Performance Interim Measures Challenges Major Improvement Root Causes Strategies Improvement Data Narrative Plan Information Description of School/District and Process for Data Contact Analysis Information Review Current Performance Trend Analysis Priority Performance Challenges Root Causes Action Planning Form Major Improvement Strategies Associated Root Causes Accountability Provision Action Steps Timeline Key People Resources Implementation Benchmarks Status of Action Steps Capturing Notes Today • Capture notes for the UIP Data Narrative in the Data Narrative Outline and Data Analysis Worksheet – Use your partially completed version – Blank versions available in the Root Cause Analysis Toolkit • Plan for completing the Data Narrative using the Planning Root Cause Analysis note catcher (Toolkit, p. 7). • Select a recorder and facilitator for your group. Section III, Step Three: Determine Root Causes • Read Step Four: Determine Root Causes (in UIP Handbook, p. 18-20) • Consider the following questions: – Why is it important to identify root causes? – How will you know when you have identified a root cause? The Role of Root Cause Analysis Root Cause Analysis Action Plan Priority Performance Challenges Root Causes are. . . • Statements describing the deepest underlying cause, or causes, of performance challenges. • Causes that if dissolved would result in elimination, or substantial reduction of the performance challenge(s). • Why we see our current pattern of performance. • Things we can change and need to change • The focus of our major improvement strategies. • About adult action. Non-examples of Root Causes • What is NOT a root cause? – Student attributes (poverty level) – Student motivation • With your table, brainstorm a few ideas of explanations that might appear to be root causes but don’t qualify. Background: Root Cause Analysis • Why root causes? • Getting past the “symptoms” to an explanation that is worth taking action on. • Read: “Root Cause Basics” (Root Cause Analysis Tools, p. 11-16) • With your team, create a 1 sentence description of “Root Cause” that you will use. Building Background on Root Cause Analysis • Turn to the Planning for Root Cause Analysis note catcher (Toolkit, p. 7) • Make notes about how you will build background knowledge of your team on root cause analysis. – Who will help with this? – When will this occur? – What materials will you use? Agenda Role of Root Cause Analysis Priority Performance Challenges Identify Root Causes More than Performance Data Finalize the Data Narrative Root Causes and Priority Performance Challenges • Root causes are always focused on at least one priority performance challenge. • They explain why we see the patterns of performance that we see. • So. . . priority performance challenges must be clearly identified first. What are “high quality” Notable Trends and Priority Performance Challenges • Work with a partner. Take out UIP Quality Criteria. Consider: – Data Narrative Criteria (definition and first seven bullets) and for Title I schools (last bullet) p. 3 – Trends (definition and all bullets) p. 4 – Priority Performance Challenges (definition and all bullets) p. 4 • Discuss: What should our Notable Trends and Priority Performance Challenges include? Effective Feedback Clear, descriptive, criterion-based, and indicate: √ how their response differed from that reflected in the UIP quality criteria, and √ how they can move forward (what they might do next). Provide feedback about Priority Performance Challenges • Choose a partner table team or individual. • Exchange trend statements and priority performance challenges. • Consider: – To what degree does the partial draft of their data narrative (trend statements and priority performance challenges) meet the relevant quality criteria? – How could they improve their plan so far? • Provide feedback to your partner. Responding to Feedback • Consider the feedback you received – How will you respond to the feedback you received? What will you do next to incorporate this feedback into your data narrative? – How did it go providing feedback about another district’s plan? – What did you learn? • Large-group share out Agenda Role of Root Cause Analysis Priority Performance Challenges Identify Root Causes More than Performance Data Finalize the Data Narrative If you’re only looking at Student Learning, you’re missing 65% of the data. – Victoria Bernhardt Multiple measures must be considered and used to understand the multifaceted world of learning from the perspective of everyone involved. -Victoria Bernhardt What types of data do we have? • Demographics • Perceptions • Student Learning/ Performance • School Processes Demographics Enrollment, Attendance, Race/Ethnicity, Gender, Drop-Out Rate, Language Proficiency, Mobility Victoria Bernhardt Perceptions Perceptions of Learning Environment, Values and Beliefs, Attitudes, Observations Victoria Bernhardt Student Learning (performance) State-Administered Tests, District Interim Tests, Common crossclassroom assessment, End of unit assessment Victoria Bernhardt School Processes Records of School Programs and Processes, Classroom Records, Classroom Observations Victoria Bernhardt Demographics School Processes Provides information that allows for the identification of actions, processes, programs that best meet the needs of all students. Student Learning Perceptions Victoria Bernhardt Activity: Data Questions 1. Refer to the Data Intersection Questions worksheet. 2. Consider the questions listed. For each, identify what different types of data would be needed. 3. Identify 2 additional questions at your table. As a group identify what data would be needed. Activity: Data Intersections • Refer to the Data Intersections Activity worksheet • Could you use this activity with your staff to get them thinking about what data they need for their root cause analysis work? Using “other types” of data • Why is it important to use data other than student performance data in planning? • For what step(s) in unified improvement planning would data other than student learning/performance data be used? Unified Improvement Planning Types of data (intersections) needed Review current performance and prior performance targets or goals Analyze data to identify notable trends Performance data (intersected with demographic data) Performance data (intersected with demographic data) Performance data (intersected with demographic data) Process and perception data (intersected with demographic data) Performance data (intersected with demographic data) and state and local expectations Performance data (intersected with demographic data) Prioritize performance challenges Identify root causes of performance challenges Establish annual performance targets Identify measures and monitor the impact of action steps on student performance. Identify implementation benchmarks & Process and perception data monitor implementation of action steps. (intersected with demographic data) Consider Other Resources Available from CDE • Turn to “Resources Available from CDE to Support Root Cause Analysis” (Toolkit p. 33) • Have you used any of these resources in your district or school? • Do any of these tools address topics likely to be important in your district or school? • Discuss: How could you use these resources to collect data to support your root cause analysis? More details on other data provided by CDE • Equitable Distribution of Teachers • TELL Survey Data • School Site Team Reviews CDE’s History on Equitable Distribution of Teachers Analysis • All districts expected to update Equitable Distribution of Teachers analysis through consolidated application. Moving to UIP now • CDE would prepare reports for districts with higher gaps. All required data is now available on SchoolView.org. NCLB Teacher Gap Analysis In Colorado According to NCLB, the state is required to ensure that poor and minority children are not taught by inexperienced, unqualified, or out-of-field teachers at higher rates than their white or more affluent peers. This report is for informational purposes and indicates that your district has a teacher gap (as measured by the percent of classrooms taught by a highly qualified teacher or the average years of teaching experience) in relation to the state average, between low and high poverty schools and/or low and high minority schools. District Name LAMAR RE-2 Gap Highly Qualified Data All schools in the state w ere divided into four quartiles- the 1st quartile being the schools w ith the low est percentage of students eligible for free or reduced lunch, and the 4th being the highest. Districts may not have schools in each of the quartiles depending on the district's size and demographics. Percent of teachers HQ Poverty State District 96.98% 100.00% 4 (High Poverty) 97.58% 81.40% 3 97.97% NA 2 98.02% 1 (Low Poverty) NA Poverty Gap between 1 (low) and 4 (high) NA NA Gap between 1 (low) and 3 NA Gap between 2 and 4 (high) HQ equity gap State District 1.05% 0.44% 0.99% All schools in the state w ere divided into four quartiles- the 1st quartile being the schools w ith the low est percentage of non-w hite students, and the 4th being the highest. Districts may not have schools in each of the quartiles depending on the district's size and demographics. Percent of teachers HQ Minority State District 97.11% 100.00% 4 (High Minority) 97.77% 100.00% 3 98.13% 81.40% 2 97.67% 1 (Low Minority) NA Minority Gap between 1 (low) and 4 (high) NA NA Gap between 1 (low) and 3 Gap between 2 and 4 (high) HQ equity gap State District 0.56% -0.10% 1.02% -18.60% Highlighted fields indicate a gap larger than the state average Highlighted fields indicates a gap greater than 2%. Gap Teacher Experience Data Teacher experience data reflects the percent of teachers w ho have been teaching for less than 3 years. This is the same data reported in the School Accountability Reports. Percent of teachers with less than 3 years of experience State District 29.30% 19.09% 4 (High Poverty) 24.36% 0.00% 3 20.17% NA 2 19.97% 1 (Low Poverty) NA Percent of teachers with less than 3 years of experience State District -9.33% Gap between 1 (low) and 4 (high) NA -4.39% NA Gap between 1 (low) and 3 -9.13% NA Gap between 2 and 4 (high) Percent of teachers with less than 3 years of experience State District 30.15% 14.29% 4 (High Minority) 22.22% 19.79% 3 19.07% 0.00% 2 21.03% 1 (Low Minority) NA Percent of teachers with less than 3 years of experience State District -9.11% Gap between 1 (low) and 4 (high) NA -1.19% NA Gap between 1 (low) and 3 -11.07% -14.29% Gap between 2 and 4 (high) Poverty Minority Poverty Minority Highlighted fields indicate a gap larger than the state average ESEA Definition of Equitable Distribution of Teachers ESEA requires that LEAs “ensure…that low-income students and minority students are not taught at higher rates than other students by unqualified, out-of-field, or inexperienced teachers.” (NCLB, Sec 1112(c)(1)(L)) Colorado’s Approach to EDT Limitations Colorado’s Enhancements Required Metrics • Highly qualified requirements • Add SPF overall growth rating largely attained (no real gaps) for performance measure • Biased against novice teachers • Performance neutral Ease of Analysis • Many variables to consider at • Interactive quadrant display in once. It is confusing. SchoolView. • Isolated analysis leads to little • Inclusion in UIP to provide action. relevance with improvement planning. SchoolView: Understanding the EDT Graph 1 1 5 6 2 The horizontal blue line represents the state’s mean percentage of novice teachers. 3 The red line represents the average percentage of novice teachers within your district. 4 The x-axis represents percentage of free and reduced lunch students, a proxy for poverty. 5 The vertical red line represents the top quartile for poverty for secondary schools. 3 2 The y-axis represents percentage of novice teachers, those less than three years of total teaching experience. 4 6 The dots represent schools. The colors represent the overall growth rating on SPF. Understanding Each Quadrant Schools within this quadrant have a high percentage of novice teachers and are serving a lower percentage of FRL students. Schools within this quadrant have a low percentage of novice teachers and are serving a lower percentage of FRL students. 4 1 3 2 Schools within this quadrant have a high percentage of novice teachers and are serving a high percentage of FRL students. The graph focuses attention on this quadrant. Schools within this quadrant have a low percentage of novice teachers and are serving a high percentage of FRL students. Equitable Distribution of Teachers Practice • Turn to: Interpreting Equitable Distribution of Teachers Data Practice (Toolkit, p. 23) • The first two pages are a reminder about how to interpret this data. • Work with a partner to complete the Practice questions. • The graphic will be on the next slide (in color), so wait for it What about small districts? Recommendations for Small Districts • The EDT analysis is still required, but may not always be as enlightening as for larger districts. • Look at the distribution by school level. • Compare average years of staff experience to the state. What is expected by CDE? • Update of EDT analysis included in UIP Data Narrative each year. • If no problems, just provide a brief summary to indicate that it was considered. • If problems are identified, include: – Detail in data narrative (as part of root cause analysis) – Provide strategies that will address the issue (e.g., using Title IIA funds to strengthen induction program) in Action Plan. TELL Survey Results • Annual statewide survey of school-based staff (teachers and leaders) on teaching and learning conditions in their school • Schools and districts that get at least 50% participation rates can access their own data. • Completed January/February timeframe. • See “Accessing TELL Colorado Survey Data” job aide for more information. External Reviews • School-Support Team (SST) reviews based on eight standards (see SST Rubric Summary, Root Cause Analysis Tools, p. 31) • Results should inform root cause analysis. • Guiding question: How do the findings of the external review help explain our performance challenge(s)? Integrating External Review Results into Root Cause Analysis When to consider External Review Results. . . 1. Engage in initial root cause analysis with your planning team. 2. Check your thinking against the SST Review findings. 3. Use data collected by the SST to validate root causes. What other data do we have? Will we have? To support Root Cause Analysis • Consider the “Suggested Data” table in the UIP Handbook (p. 7). • Highlight bullets that represent: demographic data, process data, and perception data that is currently available in your school or district. Inventory of “other” data sources • Consider “Inventory of Data Sources other than Student Performance Data” (Toolkit, p. 35) • What elements are included in this inventory? – Review the “legend” – Do you have any questions about the elements? • Identify at least 2 data sources that you would include in this inventory (complete 2 rows). • This inventory should be completed in advance of engaging in root cause analysis. Accessing and Organizing Other Data • Turn to the Planning for Root Cause Analysis note catcher (Toolkit, p. 7) • Make notes about how you will inventory, access and use data, other than performance data, as part of engaging in root cause analysis. – How will the inventory of “other” data be completed? – What data will your team review prior to root cause analysis? Agenda Role of Root Cause Analysis Priority Performance Challenges Identify Root Causes More than Performance Data Finalize the Data Narrative UIP Data Narrative Processes Review Current Performance Describe Notable Trends Prioritize Performance Challenges Identify Root Causes Causal Theories • Independently read “Identifying Causal Theories” from Got Data? Now What? (Toolkit, p. 37) • With a partner, answer these questions: – What is a causal theory? – How does a causal theory relate to root causes? – How could you categorize “causal theories” ? How to engage in Root Cause Analysis • Stay open to multiple possibilities. • Keep multiple voices in the conversations. • Generate possible theories of causation (testable explanations). • Dig deeper to organize and integrate our thoughts. • Identify additional data sources to confirm causal theories. Steps in Root Cause Analysis 1. Focus on a performance challenge (or closely related performance challenges). 2. Consider other types of data 3. Generate explanations (brainstorm) 4. Categorize/ classify explanations 5. Narrow (eliminate explanations over which you have no control) and prioritize 6. Deepen thinking to get to a “root” cause 7. Validate with other data Focus of Root Cause Analysis • Root Cause analysis is always focused on student performance. • It answers the question: What adult actions explain the student performance that we see? • Root cause analysis can focus on positive or negative trends. • In this case the focus is on “performance challenges”. Select a Focus for Today • Review your priority performance challenges. • Select one on which to focus as we practice root causes analysis today. • Share your priority performance challenge. Steps in Root Cause Analysis 1. Focus on a performance challenge (or closely related performance challenges). 2. Consider other types of data. 3. Generate explanations (brainstorm) 4. Categorize/ classify explanations 5. Narrow (eliminate explanations over which you have no control) and prioritize 6. Deepen thinking to get to a “root” cause 7. Validate with other data Matching Process & Perception Data to Priority Performance Challenges • Use the completed “Inventory of Data Other than Performance Data”. • For each priority performance challenge, identify what other data might be reviewed prior to and/or used as part of root cause analysis. • Organize these data and provide reports to your planning team. • Today. . . Skip this step. Steps in Root Cause Analysis 1. Focus on a performance challenge (or closely related performance challenges). 2. Consider other types of data 3. Generate explanations (brainstorm) 4. Categorize/ classify explanations 5. Narrow (eliminate explanations over which you have no control) and prioritize 6. Deepen thinking to get to a “root” cause 7. Validate with other data Brainstorming Rules 1. The more ideas, the better. 2. Build one idea upon another. 3. Wacky ideas are okay. 4. Don’t evaluate ideas. Jones, M. (1998). “The Thinkers Toolkit: 14 Powerful Techniques for Problem Solving”. New York: Three Rivers Press. Two different approaches • Circle Map – Brainstorm causes of performance challenges. – Group like causes together to form categories. • Tree (fish) Diagram – Start with “typical” categories of root causes of performance challenges. – Brainstorm within these categories. What data did we consider? All possible explanations of performance challenge go in the outer circle Possible Explanation Performance Challenge Possible Explanation School Process Data What process(es) did we use? Possible Explanation Possible Explanation Perception Data Circle map used with permission from Thinking Maps, Inc. Specific training required before implementing Thinking Maps. For more information, visit www.thinkingmaps.com. Circle Map, part 1: Brainstorm Causes of Performance Challenges Review “Circle Map Directions” (Toolkit, p. 47.) 1. Clarify what will focus your brainstorming (priority performance challenge) 2. Set up the Circle Map (see diagram p. 45) 3. Create the frame (identify what data you reviewed in preparation for engaging in root cause analysis) 4. Brainstorm about the possible causes of your priority performance challenge – Individuals capture one idea per sticky note – Place sticky notes on the circle map. Circle Map, Part 2: Categorize your Causes 5. Sort ideas into natural themes by asking: what ideas are similar? – Work in silence with each person moving sticky notes around on the circle map. Keep moving notes until a consensus is reached. – Discuss the groupings. – If some ideas don’t fit into any theme, leave as a stand alone idea. – If some fit more than one, create a copy and put in both groups. 6. Create a short 3-5 word description for each grouping. Tree Diagram: Brainstorm Causes within Categories Review Tree Diagram Directions (Toolkit, p. 43). 1. Clarify the question that will focus the brainstorming. 2. Determine pre-defined root cause categories, consider: – Levels of Root Causes (Preuss) --Toolkit, p. 49 – Research-Based Factors (Marzano) – Toolkit, p. 51. – Causal Categories (Wellman and Lipton) – Toolkit, p. 53 – SST Rubric Summary – Toolkit, p. 31. 3. Set up the “Tree Diagram”. 4. Brainstorm within categories (using sticky notes) 5. Summarize within each category. Practice Brainstorming, Categorizing, and Summarizing 1. Select an approach (Tree Diagram or Circle Map). 2. Recorders, draw a Tree Diagram or Circle Map on a flip chart page. 3. Use the directions for that approach (Tree Diagram Directions, Toolkit p. 43 or Circle Map Directions, Toolkit p. 47). 4. Focused by your “priority performance challenge”, brainstorm, categorize and summarize your explanations for why the school/district has that pattern of performance. 5. Capture summary statements on the flip chart. Learning from Colleagues • Gallery Walk. • With your team, view each of the flip chart pages where other groups have captured their brainstorming, categorizing and summarizing of explanations of priority performance challenges. • Return to your table and consider: – What did we see in the work of the other groups? – Is there anything we would refine about our current explanations? Completing Root Causes Analysis • Take out the Planning for Root Cause Analysis (Toolkit, p. 7). • Make notes about how you will generate explanations (brainstorm), and categorize and summarize explanations for you priority performance challenges. – What approach will you use (tree/fish, circle map, other)? – What is the current status of this work? – Who will participate? When? – What materials/Tools will you use? Steps in Root Cause Analysis 1. Focus on a performance challenge (or closely related performance challenges). 2. Consider other types of data 3. Generate explanations (brainstorm) 4. Categorize/ classify explanations 5. Narrow (eliminate explanations over which you have no control) and prioritize. 6. Deepen thinking to get to a “root” cause 7. Validate with other data Activity: Narrowing the Explanations 1. Take out “Criteria for Narrowing Explanations” and follow the directions (Root Cause Analysis Toolkit, p. 55) 2. Eliminate (cross-out or take sticky notes off) any explanation which the school cannot influence or control (e.g. student characteristics). 3. Eliminate additional explanations which fail to meet the following criteria: • It derives logically from the data • It is an explanation, not just an opinion • It is plausible, it could be verified or tested 4. Prioritize your remaining explanations (getting down to at most two), and circle your priority explanations. 5. Clarify the language, if needed, for your priority explanations. Steps in Root Cause Analysis 1. Focus on a performance challenge (or closely related performance challenges). 2. Consider other types of data 3. Generate explanations (brainstorm) 4. Categorize/ classify explanations 5. Narrow (eliminate explanations over which you have no control) and prioritize. 6. Deepen thinking to get to a “root” cause 7. Validate with other data How to deepen thinking. . . • Two tools to team deepen thinking about causes. – The Five Why’s (Root Cause Identification Form) – Multi-Flow Map (cause effect) • Both based on getting beyond symptoms to deeper causes of performance challenges. Activity: Deepening to Root Causes (The Five Why’s) 1. Use The Five Why’s -- Root Cause Identification Form, (Root Cause Analysis Tools, p. 57) 2. Choose someone to be the recorder and to write one priority explanation at the top of the worksheet. 3. Begin the process of asking “why” and identifying “because” for your explanation, following the directions on the form. 4. Circle your “root cause” explanation(s). Getting to Root Cause Because Why? Because Why? Because Why? Priority Explanation Priority Performance Challenge Because Why? Because Why? Because Why? Priority Explanation Root Cause Analysis Toolkit, p. 59 Multi-flow map used with permission from Thinking Maps, Inc. Specific training required before implementing Thinking Maps. For more information, visit www.thinkingmaps.com. Completing Root Causes Analysis • Take out the Planning for Root Cause Analysis (Toolkit, p. 7). • Make notes about how you will: – Narrow and prioritize explanations and, – Deepen thinking to get to root causes. • Consider – What is the current status of this work? – Who will participate? When? – What materials/Tools will you use? Steps in Root Cause Analysis 1. Focus on a performance challenge (or closely related performance challenges). 2. Consider other types of data 3. Generate explanations (brainstorm) 4. Categorize/ classify explanations 5. Narrow (eliminate explanations over which you have no control) and prioritize. 6. Deepen thinking to get to a “root” cause 7. Validate with other data. What additional information do we need to validate our “root cause” explanations? Validate Root Causes (example) Priority Performance Challenge: The %proficient/adv students in reading has been substantially above state expectations in 3rd grade but substantially below stable (54%, 56%, 52%) in 4th and 5th for the past three years. Possible Root Causes Questions to Explore Data Sources Validation K-3 is using new teaching strategies, 4-5 are not. What strategies are primary vs. intermediate teachers using ? Curriculum materials and Instructional plans for each grade. K-3 strategies are different from 4-5. Less time is given to direct reading instruction in 4-5 How much time is devoted to reading in primary v. intermediate grades? Daily schedule in each grade level. No evidence that less time is devoted to reading in 4-5. More ELL students in grades 4 & 5 Is there a difference between ELL and other students scores? NWEA results disaggregated by ELL status. ELL student performance in reading is higher. Activity: Validating Our Theories 1. Use the “Validate Root Causes” job aide to identify additional data needed to verify your possible root causes (Toolkit, p. 61). 2. Identify at least two additional data sources that could help. 3. On a flip chart page, capture your performance challenge, possible root cause, questions it raises, and two additional sources of data you will use to validate your root cause. 4. Share your example. 5. Follow-up: Look at this additional data to see if your root cause is validated. Data Wall Chart Priority Performance Challenge: Possible Root Cause: Questions to explore: Data sources: Did we get to root causes? 1. Ask the key questions for identifying whether a cause is a root cause: – Would the problem have occurred if the cause had not been present? – Will the problem reoccur if the cause is corrected or dissolved? – Will correction of dissolution of the cause lead to similar events? 2. Make any final revisions to your root cause explanation as needed. Preuss, P. (2003). Root Cause Analysis: School Leaders Guide to Using Data to Dissolve Problems, Larchmont, NY: Eye on Education. Quality Criteria for Unified Improvement Planning • Review: UIP Quality Criteria, Section I, Data Narrative and Section III, Root Cause Analysis • Consider: – To what degree does your root cause meet the quality criteria? – How could your root cause be improved? Capture your Work • Take out your Data Analysis Worksheet (use the one with your trends and priority performance challenges completed). • For the priority performance challenge that was your focus today, identify a “root cause”. • Make notes in the Data Narrative Outline about: – root causes of priority performance challenges, – how the root cause was identified, – additional data that will be used to validate the root cause. Tools to Support Root Cause Analysis Steps in Root Cause Analysis: Tools to use for different steps: 1. Generating explanations (brainstorm) 1. Tree Diagram (and directions) Circle Map (and directions) 2. Categorize/ classify explanations 2. Levels of Root Causes (Preuss) Causal Categories (Wellman) Marzano Factors 3. Narrow (and prioritize) 3. Narrowing Explanations 4. Get to root cause 4. The Five Why’s Deepening Thinking Multi-flow 5. Validate with other data 5. Validate Root Causes Completing Root Causes Analysis • Take out the Planning for Root Cause Analysis (Toolkit, p. 7). • Make notes about what you have completed so far (current status). • Make notes about who will participate, when and what tools you will use to complete your root cause analysis with your planning team. Agenda Role of Root Cause Analysis Priority Performance Challenges Identify Root Causes More than Performance Data Finalize the Data Narrative UIP Data Narrative Processes Review Current Performance Describe Notable Trends Prioritize Performance Challenges Data Narrative Identify Root Causes Remember, the Data Narrative • Tells the story of the school/district’s data. • Identifies data that was analyzed. • Provides a Description of processes used to : – Identify Trends – Prioritize Performance Challenges – Identify and Validate Root Causes • Includes external review results (if applicable). • Describes the significant trends, priority performance challenges, and root causes. • Takes not more than five pages. Finalizing the Data Narrative 1. Clarify the critical elements of the data narrative (using the Data Narrative Outline). 2. Aggregate and summarize notes about the data analysis processes. 3. A small group (or individual) generates a draft of data narrative (based on notes). 4. Reach consensus among all planning participants that the narrative: 5. – tells the “data story” for the school. – meets state criteria Revise data narrative as needed. Quality Criteria for Unified Improvement Planning Review: UIP Quality Criteria, Section III, Data Narrative. Notice the criteria for the data narrative includes the criteria for: trends, priority performance challenges and root cause analysis. Consider: How will you capture the information you need to complete the Data Narrative during your planning processes? Finalizing the Data Narrative • Take out the Finalizing the Data Narrative (Toolkit, p. 9) • Make notes about: – What you have completed so far (current status). – Who will participate and when in completing the data narrative. – How you will accomplish each task. – What tools/materials you will use. Give us Feedback!! • Written: Use sticky notes – + the aspects of this session that you liked or worked for you. – The things you will change in your practice or that you would change about this session. – ? Question that you still have or things we didn’t get to today – Ideas, ah-has, innovations • Oral: Share out one ah ha!