Data Collection
Population
Sampling
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….
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
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?
Lesson Objectives
 Describe procedures
 Obtaining permissions for data collection
 Selecting participants for data collection
 Identifying data options
 Recording and administering data collection
Let’s move on to data
collection
What is data?
Collection of facts from which conclusions
may be drawn
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)
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
Procedures for Collecting
Quantitative Data
(1) Obtain permissions
secure permissions
obtain informed consent
from participants
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)
Obtaining Informed Consent
from EPRD,MOE
 Obtain Approval via State Education Department
 Have participants sign an informed consent form
Procedures for Collecting
Quantitative Data
(2) Select participants
specify a population and
sample
use probability and non-
probability sampling
choose a sample size
Procedures for Collecting
Quantitative Data
(3) Identify data options
specify variables
operationalize variables
select scales of
measurement
choose types of data
measures
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
Population and
Sampling
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
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.”
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
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.
Types of Sampling
Sampling Strategies
Probability/Random
Sampling
Non-Probability/Purposeful
Sampling
Simple Stratified Cluster
Random Sampling Sampling
Sampling
Convenience Snowball
Sampling Sampling
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
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
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
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
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
Try one
 You want to study the resilience of UiTM students.
 Population?
 Sampling?
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
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
Calculating sample size
 Krejcie and Morgan (1970)
EXAMPLE
 Gender difference in vocational
interest of post matriculation at UiTM
 Independent variable:
 Dependent variable:
 Research Design:
 Population:
 Sample size:
 Instrument:
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
Calculating sample size
 Use web calculator
 http://www.raosoft.com/samplesize.html
 http://survey.pearsonncs.com/sample-calc.htm
Week 8 sampling and measurements 2015
Non Probability
Sampling
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
One may sample..
 Maximal variation
 Most hardworking/ Highest achiever
 Lowest achiever
 Extreme case
 ??
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.
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.
Your sample?
Proceed to collecting
quantitative data
Collecting
quantitative data
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
Identify Data Options:
Specify Variables
 Independent Variables
 Dependent Variables
 Intervening
 Moderating
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
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
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
Scales of
measurement
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
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
Practice
Identify the level of measurement
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?
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
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)
Record and Administer Data Collection:
Locate or Develop an Instrument
 Develop your own instrument
 Locate an existing instrument
 Modify an existing instrument
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
Developing a
questionnaire
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
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)
Validity
Validity: the ability to draw
meaningful and justifiable
inferences from the scores about a
sample or a population
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)
Let’ s look at a Rosenberg
Self Esteem Scale
Collecting Qualitative
Data
Key Ideas
 Gaining site permission
 Purposive sampling
 Types of qualitative data
 Protocols and Issues regarding administering and
recording qualitative
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
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
Types of data to Collect
 Observations
 Interviews
 Documents
 Audio-Visual Materials
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
Observation
Interviews
Documents
Audio Visuals
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
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
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
Types of Data to Collect:
Interviews
 Types of Interviews
 Individual
 Focus group
 Telephone
 e-mail
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
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
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
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?
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
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
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
Administering and
Recording Data: Field Issues
 Obtaining permission to use materials
 Ethical issues
Anonymity of participants
Convey true purpose of study without
deception
Let’s gather data
 Fill in the Qnaire
 Tabulate results
 Answer research Qs
 Qualitative data
??
NEXT
Quantitative Data Analysis

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Week 8 sampling and measurements 2015

  • 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
  • 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
  • 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.
  • 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
  • 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
  • 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
  • 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
  • 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 ??