This document discusses various methods and tools for data collection in research. It describes primary and secondary data sources, as well as quantitative and qualitative data. Several data collection methods are outlined, including observation, interviews, questionnaires, and library or laboratory research. The document emphasizes that there is no single best method and researchers must consider their purpose, respondents, resources, and the type of data needed. Both structured and semi-structured approaches are described. The importance of sampling techniques and using multiple data collection methods, such as triangulation, is also highlighted.

1. Introduction to Data Collection
Methods & Tools
N.G Upul Sanjeewa Wijepala

2. Define Research Problem
Review Concepts & Theories
Literature Review Review previous research finding
Formulate Hypothesis
Research Design (Including sample design)
Data Analysis
Interpret and Report
Data Collection
(Using Data collection Tools)
(Observation, Interview,
Questionnaire etc.,..)

3. Data
According to the Sources
1. Primary Sources Primary Data
2. Secondary Sources Secondary Data
According to the Nature
1. Quantitative Data
2. Qualitative Data

4. Primary Data
• Data never gathered before
• Advantage: find data you need to suit your
purpose
• Disadvantage: usually more costly and time
consuming than collecting secondary data
• Collected after secondary data is collected

6. Secondary Data
• Data gathered by another sources
• Secondary data is gathered BEFORE primary data.
WHY?
• Because you want to find out what is already known
about a subject/ Problem (L/R) before you dive into
your own investigation. WHY?
• Because some of your questions can possibly have
been already answered by other investigators or
authors. Why “reinvent the wheel”?

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Data Collection Strategies
• No one best way: decision depends on:
– What you need to know: numbers or stories
– Where the data reside: environment, files,
people
– Resources and time available
– Complexity of the data to be collected
– Frequency of data collection
– Intended forms of data analysis

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Which Data?
- do not need to quantify the results
- are not sure what you are able to measure Qualitative
- want narrative or in-depth information
- want to cover a large group
- want to be precise
- know what you want to measure
Quantitative
- want to conduct statistical analysis
Then Use:
If you:

10. Quantitative and Qualitative information
(Quantity) Kids (5)
(Quality) Happy

11. What method shall I use?
There is no simple answer
There is no ONE best method
It all depends…

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Structured Approach
• All data collected in the same way
• Especially important for multi-site and
cluster evaluations so you can compare
• Important when you need to make
comparisons with alternate interventions

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Use Structured Approach When:
• Need to address extent questions
• Have a large sample or population
• Know what needs to be measured
• Need to show results numerically
• Need to make comparisons across different
sites or interventions

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Semi-structured Approach
• Systematic and follow general procedures
but data are not collected in exactly the
same way every time
• More open and fluid
• Does not follow a rigid script
– may ask for more detail
– people can tell what they want in their own
way

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Use Semi-structured
Approach when:
• Conducting exploratory work
• Seeking understanding, themes, and/or issues
• Need narratives or stories
• Want in-depth, rich information
• Seek to understand results of data that are
unexpected

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Quantitative Approach
• Data in numerical form
• Data that can be precisely measured
– age, cost, length, height, area, volume, weight,
speed, time, and temperature
• Harder to develop
• Easier to analyze

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Qualitative Approach
• Data that deal with description
• Data that can be observed or self-reported, but not
always precisely measured
• Less structured, easier to develop
• Can provide “rich data” — detailed and widely
applicable
• Is challenging to analyze
• Is labor intensive to collect
• Usually generates longer reports

18. When choosing methods,
consider…
The purpose of your Research
Will the method allow you to gather information
that can be analyzed and presented in a way that will be
credible and useful to you and others.
The respondents
What is the most appropriate method,
considering how the respondents can best be reached,
how they might best respond, literacy, cultural
considerations, etc.?

19. Consider…
• What kind of data your stakeholders will find
most credible and useful
• Resources available.
Time, money, and staff to design,
implement, and analyze the information. What
can you afford?
• Type of information you need. Numbers,
percent's, comparisons, stories etc.

20. • Interruptions to program or participants.
Which method is likely to be least
intrusive?
• Advantages and disadvantages of each
method.
• .The importance of ensuring cultural
appropriateness.
Consider…

21. Sampling Techniques
Population - Total group of respondents that the
researcher wants to study. Populations are too costly and
time consuming to study in entirety.
Sample - selecting and surveying
respondents (research participants)
from the population.

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METHODS
The various method of data gathering involve the use of
appropriate recording forms. These are called tools or
instruments of data collection, they consists of
Library Research
1. Analysis of Historical
Records
2. Analysis of Documents
Laboratory
Research
1. Small group study of random
behavior, play and role analysis

23. METHODS
Field
Research
1. Non Participant Direct
Observation
2. Participant Observation
3. Mass Observation
4. Questionnaire
5. Personal Interview
6. Group Interview
7. Focused Interview
8. Telephone Survey
9. Case Study & Life History etc.

24. Often, it is better to use more than
one data collection method.
Triangulation

25. The use of triangulation in qualitative
research
 Triangulation refers to the use of multiple methods or data
sources in qualitative research to develop a comprehensive
understanding of phenomena (Patton, 1999).
 Triangulation also has been viewed as a qualitative research
strategy to test validity through the convergence of information
from different sources.
 Denzin (1978) and Patton (1999) identified four types of
triangulation:
 (a) method triangulation
 (b) investigator triangulation
 (c) theory triangulation, and
 (d) data source triangulation.

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