Using data process
Foundational tools at the core of the work are:
2. Data Driven Dialogue - structured approach to exploring predictions and observations of data before offering explanations (no because statements!)
Steps of Data driven dialogue include A. Predict B. Go Visual C. Observe D. Infer/Question. Process helps expunge erroneous assumptions
3. go visual with data - teams create large, visually vibrant displays of the data. Helps in identifying the student learning problem and to verify causes - teams must adopt the perspective that classroom curriculum and school policy are responsible for gaps in student learning. Also go visual with cause-effect analysis ("we didn't teach this or FA indicated students didn't master this")
What is Data-Driven Dialogue?
Phase 1: Predict—activate prior knowledge, assumptions and ideas surface
Phase 2: Go Visual—data becomes group owned, the data is displayed; simple large, colorful displays of information, charts, graphs...
Phase 3: Observe—“there is a strong tendency for participants to want to leap to explanation and interpretation before they have fully explored what can be learned from the data”. Have to be willing to hang out in uncertainty.
Must put aside assumptions, biases and what YOU think is going on. Focus only on the data, explore the data and make sense of its “story” Exploring the data can be challenging.
Phase 4: Infer/Question— results are generated for what has been observed. Use prior knowledge and assumptions to explain what they see in the data.
Ask why three times - teachers often blame students for poor scores. We need to get past this notion and instead ask:
Did we teach this? If we did teach it, how can we teach it differently?
The data divide is how we refer to the gap between data and results. Collaborative inquiry is the bridge between that gap...because we often don't ask the right questions
Core value
Process has to be collaborative and has to be about questions. It is not a quick process.
7 norms of collaboration
1.Pausing - pause b4 responding or asking a ? To allow 4 thinking
2.Paraphrasing - help understand each other
3.Probe for specificity - stems include : I'm curious about or I'd like to hear more about,
4.Putting ideas on the table and pulling them off of they block dialogue
5.Pay attention to self and others ( tone, body language, etc)
6.Presume positive intentions
7.Pursue balance between advocacy and inquiry - advocate for your position but inquire about the position of others.
4 agreements of courageous conversations:
Stay engaged! Remain morally, emotionally, intellectually and socially involved
Experience discomfort - operate in tension
speak your truth
Expect and accept non-disclosure - hang out in uncertainty
The bridge between data and results is collaborative inquiry.
1. Need leadership and capacity
Great question - if we taught this, how do we teach it differently?
2. Collaboration - needs to be "our" data to do away with concern over teachers feeling criticized.
3. Data use
4. Instructional Improvement - this takes time! Teachers want a quick fix!
The underlying factor is culture and equity - and building trust
Emphasis is on continuing improvement for students and teachers
Different types of data and how often they're analyzed
-Daily - weekly - formative assessments
-1-4 times per month - formative common assessments (benchmarks, problems of the week, etc
-quarterly or end of unit - common assessments
-2-4 times a year - data about people, practices, perceptions, demographic or enrollment, survey, interview, observation, etc.
Annually - summative and district assessments (aggregated, disaggregated, stand item, and student work)
Drilling down. - 5. Levels of analysis
1. Need to get 30,000 foot view of data (aggregated)
2. Zoom into 5,000 feet (disaggregated)
Zoom to ground level (strand, item analysis, student work)
3. 4. 5.
principles of effective data use
Go visual
Use data to build understanding and ownership of student learning problems
Hang out in uncertainty
Separate observation from inference - fully explore what there is to be learned
Pay attention to the process - follow noms of collaboration
Assure diverse voices are brought into the analysis. Need multiple perspectives
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Thanks so much for continuing the conversation!