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Collecting and Analyzing Data to Inform Action

Collecting and Analyzing Data to Inform Action. Stage 2: A theory of action for your project. Exploring research and best practices to provide a strong rationale for the design of your project What is known about the context where your team will implement improvement strategies?

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Collecting and Analyzing Data to Inform Action

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  1. Collecting and Analyzing Data to Inform Action

  2. Stage 2: A theory of action for your project • Exploring research and best practices to provide a strong rationale for the design of your project • What is known about the context where your team will implement improvement strategies? • What is present in the professional knowledge base? • What do we know from our own experiences, our practical knowledge base?

  3. Creating a roadmap • Start with your achievement targets – what are the actions your team will need to take to achieve improvement? • What specific actions need to be taken related to each target? • Who is involved with each action? • When should actions occur? • Will multiple actions need to be taken simultaneously? • Is there a sequence of events that should be followed? • If problems are encountered, what types of remedial steps should be taken?

  4. Stage 3: Implementing the action & collecting data • Simultaneously implementing your improvement strategy/strategies and collecting data to examine the effect the action is having • What is happening? • Why is it happening? • What impact is it having?

  5. Types of data • Quantitative data – numeric, results, “what” • Tests • Checklists • Surveys • Forced-choice • Qualitative data – narrative, descriptive, “why” or “how” • Interviews • Observations • Document analysis • Open-ended

  6. Categories of data • Informal or formal • Demographic data – looking at subgroups of students • Gender • Ethnicity • Socioeconomic status • Parent employment • Attendance rates

  7. Achievement or outcome data • Teacher tests • Text tests • State tests • Standardized tests (ACT, SAT) • Program or process data – what does your school do and how does it do it? • Programs (Reading First) • Services and interventions (ESL, Counseling, AP) • Philosophical approaches (teaming, cooperative learning)

  8. Perceptual data/qualitative data – attitudes, beliefs • Surveys • Interviews • Observations • Anecdotal records

  9. Selecting data sources • Rely heavily on existing or readily available data • Include data that can be collected while teachers are facilitating learning • Maximize the value for students of monitoring their own progress

  10. Validity – does the data measure or describe what you are trying to achieve? • Reliability – is the data accurate? • Triangulation – a process of corroboration (Sagor, page 93) • Multiple data sources • Multiple perspectives on the research team • Multiple data collection points

  11. Tips from “What is Data Anyway?” • Do no harm • Collect feasible data • Don’t collect data if you’re not going to use it • Data is everybody’s business • Collect data frequently • Analyze data as you collect it • Keep asking questions • Don’t jump to conclusions; don’t jump to solutions

  12. Stage 4: Reflecting on data and planning informed action • Have your team look at data and ask: • What does this data see to tell us? • What does it not tell us? • What else do we need to know? • What action might we need to take? • What can we celebrate?

  13. Processes of data analysis • Pattern analysis • Triangulation • Disaggregation • Discussion

  14. Sagor’s generic analysis questions • ACR Question 1: What did we do? • Time allocated • Look for patterns • Create a timeline

  15. ACR Question 2: What changes occurred regarding the achievement targets? • Look at trends (may use basic descriptive statistics: mean, median, mode, standard deviation for numeric data; coding by categories and looking at frequencies for qualitative data) • Consider the context • Disaggregation

  16. ARC Question 3: What was the relationship between actions taken and any changes in performance on the targets? • Assertions based on empirical data (your findings) and intuition (practitioner knowledge)

  17. Planning for informed action • Data-based decisionmaking • Levels of decisions • What to do tomorrow? • What changes to make in instruction? • What changes to make in the program? • What resources should be allocated to support the work? • Iterative process

  18. Telling the story of your Action Research journey • Action Research Project Summary Form – complete by April 15 • Effective Schools Research Network summaries • Examples on the WVCPD website • PLA Session III, April 24 & 25, Morgantown

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