collecting high quality outcome data: part 1 collecting high quality outcome data copyright © 2012...

Collecting High Quality Outcome Data: Part 1

Collecting High Quality Outcome Data

Copyright © 2012 by JBS International, Inc.

Developed by JBS International for the Corporation for National & Community Service


Learning Objectives

By the end of this module, you will be able to:

•Recognize the benefits of collecting high-quality data

•Use theory of change to think about measurement

•Identify and evaluate merits of data sources and instruments

•Describe some uses of data collection methods, and evaluate their merits

•Describe steps to implement data collection

•Recognize data quality

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What Do We Mean By Data?

• Data: Information collected to answer a measurement question, also known as evidence

• Data collection occurs as a planned process that involves recording information in a consistent way

• Instruments aid in collecting consistent data

3


Ensuring Data Quality: Reliability, Validity, Bias

• Reliability is the ability of a method or instrument to yield consistent results under the same conditions.

• Validity is the ability of a method or instrument to measure accurately.

• Bias involves systematic distortion of results stemming from how data are collected and how instruments are designed.

4


Benefits of Collecting High-quality Data

• Sound basis for decision making

• Improve service quality and service outcomes

• Increase accountability

• Tell story of program achievements

5


Measurement Question Implied by Theory of Change

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Intended Outcome

Students improve attitudes towardsschool.

Intended Outcome

Students improve attitudes towardsschool.

Community Problem/Need

Students with poor attitudes

towards school at risk of failing academically.


Students with poor attitudes

towards school at risk of failing academically.

Specific Intervention

Individualized mentoring to

promote positive attitudes

towards school.


Individualized mentoring to

promote positive attitudes

towards school.

"Did students in the mentoring program improve their attitudes towards school?"


Identifying a Data Source

• Data source: The person, group or organization that has information to answer the measurement question

• Identify possible data sources; list pros and cons of each

• Identify a preferred data source; consider its accessibility

• Alternative data sources: consider if they can give you same or comparable data

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Data source and type of outcome

Depends partly on the type of change you want to measure - attitude, knowledge, behavior, or conditions.

•Data on changes in attitudes or knowledge usually come directly from persons experiencing these changes.

•Data on changes in behavior or conditions can come from either persons experiencing these changes or from other observers.

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“How did mentored students’ feelings towards teachers change over time?”

Pros Cons

Students• In best position to

describe how they feel about their teachers

• May not be open about their feelings towards teachers

Teachers• May know how

students feel towards them

• May not know how students feel about other teachers

• May only spend one class period with students

Mentors • May know how students feel about a wide range of issues, including teachers

• Depends on students’ willingness to share feelings with mentors

• Students and mentors may not discuss this issue much

Comparing Data Sources

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Method: Process or Steps Taken to Systematically Collect Data

Survey Written questionnaire completed by respondent

InterviewInterviewer poses questions and records responses; face-to-face or via telephone

ObservationObserver records behavior or conditions using via checklist or other form

Standardized Test

Used to assess knowledge of academic subjects (reading, math, etc.)

Next, Consider Choice of Methods

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Method: Process or Steps Taken to Systematically Collect Data

Tracking Sheet

Used to document service delivery; used primarily to track outputs

Focus GroupFacilitator leads small group through discussion in-depth discussion of topic or issue

Diaries, Journals

Respondent periodically (daily) records information about his/her activities or experiences

Secondary Data

Using data gathered by other agencies that can be used to assess program performance

Consider Choice of Methods (continued)

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Method and Outcomes Type—Attitude and Knowledge

Attitude/Belief Knowledge/Skill

Definition Thoughts, feelingsUnderstanding,

know-how

ExamplesAttachment to school

(academic engagement)

Becoming a better reader

Generally Preferred Data Source/Method

Student:Survey or interview

Learner: Standardized test*

* Use of standardized tests is mandated for certain performance measures in the Education Focus Area. Other types of knowledge (e.g., financial literacy) can be measured using other types methods.

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Method and outcome type—behavior and condition

Behavior Condition/Status

Definition Action, conduct, habitsSituation or

circumstances

ExamplesExercising more

frequentlyImproving stream

banks

Generally Preferred Data Source/Method

Beneficiary:Exercise log

Land manager: Observation checklist

or rubric

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Where to Find Instruments

• For CNCS priorities and performance measures, look for instruments by goal and focus area

• Go to http://www.nationalservice.gov/resources/npm/home

• Programs and projects can look anywhere they like to find instruments:

• Use Internet search engines

• Talk to others within you professional network to find out what they are using

• Look at evidence for intervention – how measured before?

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Evaluating Instruments

• Pre-post measurement is preferable to post-only

• Can the instrument measure the outcome?

• Appropriate for your intervention?

• Appropriate for your beneficiaries?

• How many questions measure the outcome?

• Single question low-quality data

• Series of questions: Too long or complex?

• Instrument should not exceed 2 pages

• Do questions cover all relevant aspects of your intervention? Can questions not specific to your intervention be removed?

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Define Outcome Dimensions

Outcome Dimensions: The main aspects, features, or characteristics that define an outcome and that should be taken into account for measurement to be valid

Example: Increased attachment to school:•Feelings about being in school•Feelings about doing school work•Feelings towards teachers•Feelings towards students

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Example: Dimensions of Attachment to School

a

a

b

b

c

c

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d

d

a

b

c

d


Summary: Identifying Outcome Dimensions

• National performance measures: look at performance measurement instructions

• Look at your theory of change

• Talk to stakeholders and program staff

• Build up a list of dimensions; look for repeated themes

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Evidence•Guides choice of intervention•Supports cause-effect relationship

Evidence•Guides choice of intervention•Supports cause-effect relationship





Intended OutcomeIntended Outcome


Instrument Design Issues

• Crowded layout

• Double-barreled questions

• Biased or “leading” questions

• Questions that are too abstract

• Questions that use unstructured responses inappropriately

• Response options that overlap or contain gaps

• Unbalanced scales

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Crowded Layout

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Problem: Crowded layout

Most of the time, how do you feel about doing homework?

☐ I usually hate doing homework I usually don’t like doing ☐homework I usually like doing homework I usually love doing ☐ ☐homework

Solution: Don’t use crowded layouts

Most of the time, how do you feel about doing homework?

☐ I usually hate doing homework

☐ I usually don’t like doing homework

☐ I usually like doing homework

☐ I usually love doing homework


Double-barreled Question

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They strongly like it☐

Theylike it☐

They are undecided

☐

They dislike it☐

They stronglydislike it

☐

Problem: Asking two questions in one

How do teachers and students at your school feel about the mentoring program?

Solution: Break out questions separately

How do teachers at your school feel about the mentoring program?

How do students at your school feel about the mentoring program?


Theylike it☐

They are undecided

☐

They dislike it☐


☐


Theylike it☐

They are undecided

☐

They dislike it☐


☐


Biased or “Leading” Question

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Problem: Biased or “leading” questions

Has the mentoring program improved how you feel about going to school?

☐ Yes

☐ No

☐ No opinion

Solution: Use neutral questions

How has the mentoring program affected how you feel about going to school?

☐ I feel better about going to school.

☐ I feel worse about going to school.

☐ I feel about the same about going to school.

☐ No opinion


Abstract or Broad Question

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Problem: Questions are too abstract or broad.

Did you enjoy the mentoring program?

Yes No Not Sure

Solution: Make questions more concrete and specific.

Would you recommend the mentoring program to other students?

Yes No Not Sure


Not Using Structured Responses

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Problem: Using unstructured responses when structured responses are appropriate

How much do your grades matter to you?

Solution: Provide structured responses when appropriate

How much do your grades matter to you?

☐ Not at all

☐ A little

☐ Somewhat

☐ A lot


Response Options with Overlaps or Gaps

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Problem: Response options that overlap or contain gaps

Approximately how many hours a day to you typically spend doing homework?

☐ Less than 1 hour

☐ 0 to 2 hours

☐ 4 to 5 hours

☐ More than 5 hours

Solution: Scale with no overlaps or gaps

Approximately how many hours a day to you typically spend doing homework?

☐ Less than 1 hour

☐ About 1 hour

☐ About 2 hours

☐ About 3 hours

☐ About 4 hours

☐ More than 4 hours


Unbalanced scales

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Problem: Using unbalanced scales

Solution: Use balanced scales

Poor☐

Average☐

Good☐

Very Good

☐

Excellent☐

VeryPoor☐

Poor☐

Average☐

Good☐

Very Good

☐


What else to look for in selecting an instrument

• Can the instrument work in your context?

• Does the instrument use simple and clear language?

• Is the instrument appropriate for the age, education, literacy, and language preferences of respondents?

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What else to look for in selecting an instrument, continued

• Does the instrument rely mostly on multiple choice questions?

• Is the ready for use, or does it need to be modified?

• How will you extract information from the instrument to address performance measurement targets?

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Implementing Data Collection

After identifying a data source, method and instrument:

1.Identify data collection participants

2.Set a schedule for collecting data

3.Train data collectors

4.Pilot test the data collection process

5.Make changes

6.Implement data collection

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FOR BEST RESULTS make key decisions about how to implement data collection BEFORE program startup!


Step 1: Identifying data collection participants

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• Brainstorm a list of all the relevant players in the data collection process. This includes:


Step 2: Creating A Data Collection Schedule

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• Identifies who will collect data, using which instrument, and when

• Share with team to keep everyone informed• Include stakeholders in planning• Include dates for collecting, analyzing, and reporting data• Select a format


Step 3: Training Data Collectors

• Determine best person(s) to collect data

• Provide written instructions for collecting data

• Explain importance and value of data for program

• Walk data collectors through instrument

• Practice or role play data collection

• Review data collection schedule

• Explain how to return completed instruments

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Step 4: Pilot Testing for Feasibility and Data Quality

1. Try out instruments with a small group similar to program participants

2. Discuss instrument with respondents

3. Analyze pilot test data toensure the instrument yields the right information

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Questions for Debrief

How long did it take to complete?

What did you think the questions were asking you about?

Were any questions unclear, confusing, or difficult to answer?

Were response options adequate?

Did questions allow you to say everything you wanted to say?


Steps 5 & 6: Make Changes & Implement Your Plan

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Make Changes•Based on pilot test analysis:

• Improve instrument

• Strengthen process

Implement Your Plan•Perform periodic quality control checks


Ensuring Data Quality:Key Criteria

• Criteria for collecting high-quality, useful outcome data:

• Reliability

• Validity

• Minimizing Bias

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Reliability

• Reliability: The ability of a method or instrument to yield consistent results under the same conditions.

• Requires that instruments be administer the same way every time:o Written instructions for

respondents

o Written instructions for data collectors

o Train and monitor data collectors

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Reliability

• Design instruments to improve reliability

o Use clear and unambiguous language so question meaning is clear.

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Unclear language

“How has the availability companionship services altered your capacity with respect to attending visits with medical practitioners in a timely manner?”

Clear language

“How has use of companionship services affected your ability to get to medical appointments on time?”


Reliability

• Design instruments to improve reliability

o Use attractive, uncluttered layouts that are easy to follow.

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Cluttered layout

“What grade are you in?”

☐6th grade ☐7th grade ☐8th grade

Uncluttered layout

“What grade are you in?”

☐ 6th grade

☐ 7th grade

☐ 8th grade


Validity

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Minimizing Sources of Bias

• Bias involves systematic distortion of results stemming from how data are collected and how instruments are designed.

• Who: Non-responders = hidden bias

• How: Wording that encourages or discourages particular responses

• When and Where: Timing and location can influence responses

• Bias can lead to over- or under-estimation of program results

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7 Ways of Minimizing Bias

1. Get data from as many respondents as possible

2. Follow up with non-responders

3. Take steps to reduce participant attrition

4. Work with program sites to maximize data collection

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7 Ways of Minimizing Bias(continued)

5. Pilot test instruments and data collection procedures

6. Mind your language

7. Time data collection to avoid circumstances that may distort responses

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Did students in the mentoring program increase their attachment to school?

OutputNumber of disadvantaged youth/mentor matches that were sustained by the CNCS-supported program for at least the required time period (ED4A)

OutcomeNumber of students in grades K-12 that participated in the mentoring or tutoring or other education program who demonstrated improved academic engagement (ED27)

How Measured Pre/post survey of students to gauge attachment to school

Outcome Target90 (of 100) students in grades 6-8 that participate in the after-school program for 9 months will improve academic engagement, defined as feelings of attachment to school.

Academic Engagement

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Did students in the mentoring program increase their attachment to school?

OutcomeNumber of students in grades K-12 that participated in the mentoring or tutoring or other education program who demonstrated improved academic engagement (ED27)

How Measured Pre/post survey of students to gauge attachment to school

ReliabilityDo survey responses reflect students’ stable and established beliefs about school or just fleeting and changeable feelings?

ValidityDoes the survey get at the dimensions of school attachment that are relevant to the intervention? Are students telling us how the really feel or what they think we want to hear?

BiasDoes the survey ask the questions in a neutral way? Have we timed the survey to avoid unrelated factors like “exam stress” that could contaminate our results?

Academic Engagement—Reliability, Validity, Bias

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Summary of key points

Steps to implement data collection include identifying the

players involved in data collection, creating a data collection

schedule, training data collectors, pilot testing instruments,

and revising instruments as needed.

• A data collection schedule identifies who will

collect data, using which instrument, and when.

• Training data collectors by walking them through

the instrument and role playing the process.

• Pilot testing involves having a small group of

people complete an instrument and asking them

about the experience.

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Reliability, validity, and bias are key criteria for data quality.

• Reliability is the ability of a method or instrument to

yield consistent results under the same conditions.

• Validity is the ability of a method or instrument to

measure accurately.

• Bias involves systematic distortion of results due to

over- or under-representation of particular groups,

question wording that encourages or discourages

particular responses, and by poorly timed data

collection.

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• The benefits of collecting high-quality data include

providing a sound basis for decision making, improving

service quality and outcomes, increasing accountability,

and telling your story in a more compelling way.

• Your theory of change, and the key measurement

question embedded in it, is a useful a guide to

measurement.

• The type of outcome to be measured influences

decisions about data sources, methods, and

instruments.

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Additional resources

CNCS Performance Measuremento http://nationalservice.gov/resources/npm/home

Instrument Formatting Checklisto https://www.nationalserviceresources.org/npm/practicum-

collecting-data-part-2

Practicum Materialso http://www.nationalservice.gov/resources/npm/core-

curriculum

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collecting high quality outcome data: part 1 collecting high quality outcome data copyright © 2012...

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