Collecting and Analyzing Data to Inform ActionCollecting and Analyzing Data to Inform Action

Stage 2: A theory of action for your project

Stage 2: A theory of action for your project

Exploring research and best practices to provide a strong rationale for the design of your projectWhat 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?

Exploring research and best practices to provide a strong rationale for the design of your projectWhat 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?

Creating a roadmapCreating 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?

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?

Stage 3: Implementing the action & collecting data

Stage 3: Implementing the action & collecting data

Simultaneously implementing your improvement strategy/strategies and collecting data to examine the effect the action is havingWhat is happening?Why is it happening?What impact is it having?

Simultaneously implementing your improvement strategy/strategies and collecting data to examine the effect the action is havingWhat is happening?Why is it happening?What impact is it having?

Types of dataTypes 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

Quantitative data – numeric, results, “what”

Tests Checklists Surveys Forced-choice

Qualitative data – narrative, descriptive, “why” or “how”

Interviews Observations Document analysis Open-ended

Categories of dataCategories of data

Informal or formalDemographic data – looking at

subgroups of studentsGenderEthnicitySocioeconomic statusParent employmentAttendance rates

Informal or formalDemographic data – looking at

subgroups of studentsGenderEthnicitySocioeconomic statusParent employmentAttendance rates

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)

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)

Perceptual data/qualitative data – attitudes, beliefsSurveysInterviewsObservationsAnecdotal records

Perceptual data/qualitative data – attitudes, beliefsSurveysInterviewsObservationsAnecdotal records

Selecting data sourcesSelecting 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

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

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 sourcesMultiple perspectives on the research

teamMultiple data collection points

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 sourcesMultiple perspectives on the research

teamMultiple data collection points

Tips from “What is Data Anyway?”

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

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

Stage 4: Reflecting on data and planning informed actionStage 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?

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?

Processes of data analysisProcesses of data analysis

Pattern analysisTriangulationDisaggregationDiscussion

Pattern analysisTriangulationDisaggregationDiscussion

Sagor’s generic analysis questions

Sagor’s generic analysis questions

ACR Question 1: What did we do?Time allocatedLook for patternsCreate a timeline

ACR Question 1: What did we do?Time allocatedLook for patternsCreate a timeline

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 contextDisaggregation

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 contextDisaggregation

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)

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)

Planning for informed action

Planning for informed action

Data-based decisionmakingLevels 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

Data-based decisionmakingLevels 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

Telling the story of your Action Research journeyTelling the story of your Action Research journey

Action Research Project Summary Form – complete by April 15 Effective Schools Research Network

summariesExamples on the WVCPD website

PLA Session III, April 24 & 25, Morgantown

Action Research Project Summary Form – complete by April 15 Effective Schools Research Network

summariesExamples on the WVCPD website

PLA Session III, April 24 & 25, Morgantown