Here are the key points about observations as a method of collecting qualitative data: - Observations involve gathering first-hand information by watching people and places at the research site. - There are different observational roles: 1) Participant observer - the researcher takes part in the activities being observed. 2) Non-participant observer - the researcher does not participate, only observes. - The observational role can change - a researcher may start as a participant observer and then shift to non-participant. - As an observer, the researcher takes detailed field notes on the behaviors, activities, events, and other features observed at the research site. - Field notes include descriptions, direct quotations, and observer

1. Data Collection
Population
Sampling

2. More reminders ..
 Get your variables sorted by now
 Chapters 1, 2, 3,4 are not yours
 Strong remark
 Use of phrases from another article
 Citing secondary sources
 Block quotation and Page reference
 In text citation
 Colloquial – “In my honest opinion….”
 Connecting ideas – on the other hand,
moreover, in support of, This is supported
by.., in contrast to, in addition,
nonetheless….

3. Instructor assigned task
(25%)
 TASK : Design a research
 Survey
 Correlational
 Experimental
 Causal Comparative
 Case study – Mixed
method
 Ethnography
 TOPIC : 21st century
learners
 Group work
 Group of 3 (max)
 Study task description on
i-Learn
 Assignment/Projects
 Instructor Assigned Task
 Use Blendspace
 Due 30th May 2015
 Marks given for product
and
comments/discussions

4. Where we are now…
Observation
Background
survey
Broad area
of research
Literature
review
Problem
definition
Problem
statement
Research
questions
Theoretical
framework
Variables
clearly
identified
Hypothesis
generation
Research
design
Methods
Data
collection
Analysis
Interpretation
Deduction
Hypothesis
substantiated?
RQ answered?

5. Lesson Objectives
 Describe procedures
 Obtaining permissions for data collection
 Selecting participants for data collection
 Identifying data options
 Recording and administering data collection

6. Let’s move on to data
collection
What is data?
Collection of facts from which conclusions
may be drawn

7. Key ideas
 Who will you study (unit, sampling, sample
size)?
 What permissions will you need?
(levels,MOE)
 What information will you collect? (types
of data, links to questions/variables)
 What instrument(s) will you use? (selecting
an instrument, scales of measurement,
validity, reliability)
 How will you administer the data
collection? (standardization, ethical issues)

8. Who will you study?
 Unit of analysis is the level (e.g. individual, family,
school, school district) the data will be gathered.
 There may be different units of analysis
one for the dependent
variable
one for the independent
variable

9. Procedures for Collecting
Quantitative Data
(1) Obtain permissions
secure permissions
obtain informed consent
from participants

10. Obtaining Permissions
 Institutional or organizational (e.g. school district)
 Site-specific (e.g. secondary school)
 Individual participants or parents
 Campus approval (e.g. university or college)

11. Obtaining Informed Consent
from EPRD,MOE
 Obtain Approval via State Education Department
 Have participants sign an informed consent form

12. Procedures for Collecting
Quantitative Data
(2) Select participants
specify a population and
sample
use probability and non-
probability sampling
choose a sample size

13. Procedures for Collecting
Quantitative Data
(3) Identify data options
specify variables
operationalize variables
select scales of
measurement
choose types of data
measures

14. Procedures for Collecting
Quantitative Data
(4) Record and administer data collection
locate or develop an
instrument
obtain reliable and valid data
develop administrative
procedures for data collection

15. Population and
Sampling

16. POPULATION and SAMPLING
 A population is a group of individuals that comprise
the same characteristics
 A sample is a sub-group of the target population that
the researcher plans to study

17. Select Participants: Specify
a Population and Sample
 Samples
 for the purpose about making generalizations about the
target population (quantitative research).
samples are only estimates
the difference between the
sample estimate and the true
population is the “sampling
error.”

18. Manageable research
population
Populations and Samples
Sample
Target
Population
Population
• All science teachers in
secondary schools in
Kuantan
• College students in all
community colleges
• Adult educators in all
faculties of education
Better?
All sec. school biology
teachers in Kuantan
Students in one
community college
Adult educators in
faculties of education in
the East Malaysia

19. Probability and Non-Probability
Sampling
 Probability sampling is the selection of individuals from
the population so that they are representative of the
population
 Non-probability sampling is the selection of
participants because they are available, convenient,
or represent some characteristic the investigator wants
to study.

20. Types of Sampling
Sampling Strategies
Probability/Random
Sampling
Non-Probability/Purposeful
Sampling
Simple Stratified Cluster
Random Sampling Sampling
Sampling
Convenience Snowball
Sampling Sampling

21. Differences Between Random
and Purposeful Sampling
Random “Quantitative” Sampling
Select Representative individuals
To generalize from sample to population
To make claims about the population
To build/test “theories” that explain the population
Purposeful “Qualitative” Sampling
Select people/sites who can best help us understand our
phenomenon
To develop detailed understanding
That might be “useful: information
That might help people “learn” about the phenomenon
That might give voice to “silenced” people

22. Types of Probability
Sampling
 Simple Random: selecting a sample from the
population so all in the population have an equal
chance of being selected
 Systematic: choosing every “nth” individual or site in
the population until the desired sample size is
achieved

23. Types of Probability Sampling
Stratified sampling: stratifying the
population on a characteristic (e.g.
gender), then sampling from each
stratum.
Boys
N=6000
Girls
N=3000
Population
(N=9000)
.66 of pop. 200
.33 of pop 100
Sample = 300

24. Types of Probability
Sampling
 Cluster Sampling:
 Selects groups, not individuals
 All members in the groups have similar characteristics
 Useful when the population is large or spread over a wide
geographical area

25. Example: Cluster Sampling
 Population : All primary school teachers in
Klang valley (5000)
 The desired sample : 400
 Cluster: School
 No. of primary schools in Klang valley: 150
 Average number of teachers per school : 40
 Number of cluster : 400/ 40
 10 out of 150 schools are randomly selected
 All teachers in the selected schools make up
the sample

26. Try one
 You want to study the resilience of UiTM students.
 Population?
 Sampling?

27. Select Participants: Choose
a Sample Size
 Select a sample size as large as possible from the
individuals available
 Select a sufficient number of participants for the
statistical tests you will use
 Calculate the sample size using a sample size formula

28. Select Participants: Choose
a Sample Size
 A rough estimate:
 15 participants in each grp in an expt
 30 participants for a correlational study
 350 individuals for a survey study but depend of
several factors

29. Calculating sample size
 Krejcie and Morgan (1970)

30. EXAMPLE
 Gender difference in vocational
interest of post matriculation at UiTM
 Independent variable:
 Dependent variable:
 Research Design:
 Population:
 Sample size:
 Instrument:

31. EXAMPLE
Gender difference in vocational
interest of post matriculation at UiTM
Independent variable: Gender
Dependent variable: Vocational
interest
Research Design: Survey
Population: Post matriculation
students
Sample size: 350
Instrument: Self developed

32. Calculating sample size
 Use web calculator
 http://www.raosoft.com/samplesize.html
 http://survey.pearsonncs.com/sample-calc.htm

34. Non Probability
Sampling

35. Types of Purposeful Sampling
When Does Sampling Occur?
After Data Collection
has startedWhat is the intent?
To develop
many
perspectives
Extreme
Case
Sampling
To describe
particularly
troublesome
or enlightening
cases
Typical
Sampling
To describe what
is “typical” to
those unfamiliar
with the case
What is the intent?
To take advantage
of whatever case
unfolds
Opportunistic
Sampling
To locate
people or
sites to study
Snowball
Sampling
To explore
confirming or
disconfirming
cases
Confirming/
Disconfirming
Sampling
Maximal
Variation
Sampling
To generate a
theory or
concept
Theory or Concept
Sampling
To describe some
sub-group in depth
Homogenous
Sampling
Before Data Collection

36. One may sample..
 Maximal variation
 Most hardworking/ Highest achiever
 Lowest achiever
 Extreme case
 ??

37. Examples of Non-Probability
Samples
 Convenience Sampling: participants are selected
because they are willing and available to be studied
 Snowball Sampling: the researcher asks participants
to identify other participants to become members of
the sample.

38. Non Probability sampling example
 Study delinquent behaviour during recess.
 I selected 1 school out of 4 - Interviewed all 4 principals
and toured all 4 schools. I chose school to which I was
given most access with fewest restrictions. Also school
that reported the widest variations in delinquent
behaviour during recess (very high to virtually no
display).
 Then sampled different locations with camera to find
most varied activity and least self-conscious/guarded
behavior. Where?
 Turned out to be behind the surau.
 Later used snowball approach in choosing children to
interview.

39. Your sample?

40. Proceed to collecting
quantitative data

41. Collecting
quantitative data

42. Flow of Activities in
Collecting Data
1.Identify the variable
2.Operationally define the
variable
3.Locate data (measures,
observations, documents with
questions and scales)
4.Collect data on instruments
yielding numeric scores

43. Identify Data Options:
Specify Variables
 Independent Variables
 Dependent Variables
 Intervening
 Moderating

44. Identify Data Options:
Operationalize Variables
 Operational Definition: The specification of how the
variable will be defined and measured
typically based on the
literature
often found in reports under
“definition of terms”
 Sometimes the researcher must construct it

45. Flow of Activities in
Collecting Data
Identify the variable
Operationally define the
variable
Locate data (measures,
observations, documents
with questions and scales)
Collect data on
instruments yielding
numeric scores
Self-efficacy for learning from
others
Level of confidence that an
individual can learn something
by being taught by others
13 items on a self-efficacy
attitudinal scale from Bergin
(1989)
Scores of each item ranged from
0-10 with 10 being “completely
confident.”
Flow of Activities Example

46. Flow of Activities in
Collecting Data
Identify the variable
Operationally define the
variable
Locate data (measures,
observations, documents
with questions and scales)
Collect data on
instruments yielding
numeric scores
Learning motivation of adult
learners
Interest and level of
engagement of an individual
----- items on a questionnaire
developed
Scores of each item ranged from
1-5 with 5 being “most
interested”
Flow of Activities Example

47. Scales of
measurement

48. Identify Data Options: Select
Scales of Measurement
 Nominal (Categorical): categories that describe traits
or characteristics
 participants can check 
  Female  Male
 Ordinal: participants rank the order of a characteristic,
trait or attribute

49. Identify Data Options: Select
Scales of Measurement
 Interval: provides “continuous” response possibilities to
questions with assumed equal distance ; scale with no
true zero
 Discrete (SD ---------------------SA)
 Metric (oC)
 Ratio: a scale with a true zero and equal distances
among units

50. Practice
Identify the level of measurement

51. Measurement level?
 Age
 Religion
 Gender
 Income bracket
 Test scores
 CGPA
 Frequency of asking questions
 Time spent on task
 Level of acceptance
 (0 – never, 5 – all the time)
 Activity
 ( 0 –not active, 5 – very
active)
Ratio ?
Nominal?
Ordinal?
Interval?

52. Measurement level?
 Age
 Religion
 Gender
 Income bracket
 Test scores
 CGPA
 Frequency of asking questions
 Time spent on task
 Level of acceptance
 (0 – never, 5 – all the time)
 Activity
 ( 0 –not active, 5 – very
active)
 Ratio
 Nominal
 Nominal
 Ordinal
 Ratio
 Ordinal
 Ratio
 Ratio
 Interval/ Ordinal
 Interval/Ordinal

53. Identify Data Options: Choose
Types of Data Measures
 An instrument is a tool for measuring,
observing, or documenting quantitative
data
 Types of Instruments
 Performance Measures (e.g. test
performance)
 Attitudinal Measures (measures feelings
toward educational topics)
 Behavioral Measures (observations of
behavior)
 Factual Measures (documents, records)

54. Record and Administer Data Collection:
Locate or Develop an Instrument
 Develop your own instrument
 Locate an existing instrument
 Modify an existing instrument

55. Record and Administer Data Collection:
Locate or Develop an Instrument
 Strategies to use
Look in published journal articles
Run an ERIC search and use the
term “instruments” and the topic
of the study
Go to ERIC web site for Evaluation
and Assessment
Examine guides to commercially
available tests

56. Developing a
questionnaire

57. Obtain Reliable and Valid Data
Reliability: individual scores from an
instrument should be nearly the
same or stable on repeated
administrations of the instrument
Bathroom scale

58. Reliability
 Types of reliability
 Test-retest (scores are stable over time)
 Internal consistency (consistent scores across the
instrument)
 Cronbach coefficient alpha if items are scored as continuous
variables (SA—SD)
 Inter-rater reliability (similarity in observation of a behavior
by two or more individuals)

59. Validity
Validity: the ability to draw
meaningful and justifiable
inferences from the scores about a
sample or a population

60. Types of validity
Content (representative of all
possible questions that could be
asked)
Criterion-referenced (scores are a
predictor of an outcome or criterion
they are expected to predict
Construct (determination of the
significance, meaning, purpose and
use of the scores)

61. Let’ s look at a Rosenberg
Self Esteem Scale

62. Collecting Qualitative
Data

63. Key Ideas
 Gaining site permission
 Purposive sampling
 Types of qualitative data
 Protocols and Issues regarding administering and
recording qualitative

64. Gaining Permission
 Gain permission from Institutional Review Board
 Gain permission from “gatekeepers” at the research
site
 Gatekeepers: individuals at the site who provide site
access, helps researcher locate people and identifies
places to study
 The gatekeeper may require written permission about the
project

65. Information for the gatekeeper
Why their site was chosen
What time and resources are required
What will be accomplished at the site
What potential there is for your
presence to be disruptive
What individuals at the site will gain from
the study
How will you use and report the results

66. Types of data to Collect
 Observations
 Interviews
 Documents
 Audio-Visual Materials

67. Sources of Qualitative Data
 From People:
 Interviews
 Surveys
 Focus Groups
 Participant Observation
(field notes)
 From Things:
 Agency case records
 Miscellaneous
documents
 Historical Artifacts
 Media
 Published materials

68. Observation
Interviews
Documents
Audio Visuals

69. Types of Data to Collect:
Observations
 An observation is the process if gathering first-hand
information by observing people and places at a
research site.
 Observational roles
 Participant observer
 Non-Participant observer
 Observational roles can be changed

70. Types of Data to Collect:
Observations
 Conduct multiple observations
 Record both descriptive and reflective
field notes during the observation
Descriptive field notes describe the
events, activities and people
Reflective field notes record personal
reflections that relate to their insights,
hunches or broad themes that
emerge

71. Administering and Recording
Data: Observational Protocols
 The header: essential information about the
observation
 Left column to record descriptive notes
 Right column to record reflective notes
 A picture of the site may be sketched

72. Types of Data to Collect:
Interviews
 Types of Interviews
 Individual
 Focus group
 Telephone
 e-mail

73. Structured, Unstructured, and
Semi-Structured Interviews
Approach to
Data
Collection
Type of
Response
Options to
Questions
Types of
Interviews
Leading
to
Data
Quantitative Close-
Ended
Structured/
semi-structured
Interviews
Scores to
answers
Qualitative Open-
Ended
Unstructured
Interviews
Transcription
of words

74. Types of Data to Collect:
Interviews
 General open-ended questions are asked
 allows the participant to create options for responding
 participants can voice their experiences and
perspectives
 Information is recorded then transcribed for analysis

75. Administering and Recording
Data: Interview Protocols
 The header: essential information about the interview
 Open-ended questions include
 “ice-breaker”
 ones that address major research questions
 probes that clarify and elaborate
 Closing comments thanking the participant

76. EXAMPLE:
Semi structured Interview protocols
Name:
Date:
Time:
Venue:
Experience – please describe
Questions
1. Is the method a valid approach to
addressing the learning needs of adult
learners? Please describe your thoughts of
the method
2. What do you think are the barriers to the
utilization of the method in UiTM?
3. How would you rate the quality of learning
using the method?
4. What overall suggestions do you have for
improving the method?

77. Types of Data to Collect:
Documents
 Public and private records
 Good source for text data
 You must obtain permission before using
documents
 Scan documents when possible

78. Types of Data to Collect: Audio-
Visual Materials
Determine the material that can
provide evidence to address your
research questions
Determine if the material is available
and obtain permission to use it
Check the accuracy and
authenticity of the material if you do
not record it yourself
Collect the data and organize it

79. Administering and
Recording Data: Field Issues
 Time needed for data collection
Limit initial collection or one or two
observations or interviews
Time is needed to establish a substantial
data base

80. Administering and
Recording Data: Field Issues
 Obtaining permission to use materials
 Ethical issues
Anonymity of participants
Convey true purpose of study without
deception

81. Let’s gather data
 Fill in the Qnaire
 Tabulate results
 Answer research Qs
 Qualitative data
??

82. NEXT
Quantitative Data Analysis