Categorieën: Alle - attitudes - collaboration - survey - interview

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KMF2024 Research Methodology

Survey research involves collecting data through questionnaires and interviews, focusing on quantitative observations and self-reports. Key aspects include constructing attractive, brief, and easy-to-respond-to questions, selecting participants carefully, and considering the mode of administration, such as paper-and-pencil for cost efficiency and broader reach.

KMF2024 Research Methodology

KMF2024 Research Methodology

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7_Survey Research

classifying
survey frequency

longitudinal survey (advantage - no comparability problem / disadvantage - sample tend to shrink over time, extended commitment)

study the dynamics of an issue over time

collect 2 or more times

cross-sectional survey (advantage - convenience / disadvantage - selecting comparable samples)

entire population - census survey

stand-alone study

single time period

collection of survey data

observation (quantitative)

self report

telephone

Interview

questionnaire

followup activities (initial followup strategy)

constructing the Q (attractive, brief, easy to respond to)

selecting participants

stating problem (no trivial issues)

paper-and-pencil Q (less time, less expensive, collection from much larger sample)

crtiticisms (misuse of d data)

assessing - attitudes, opinions, preferences, demographics, practices, and procedures

8_Descriptive Statistics

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major types
measures of relatioship

the degree to which two sets of scores are related

Spearmen, Rho

Pearson, r

measures of relative position

comparison

measures of variability

how spread out a group of scores are

measures of central tendency

typical or average score of a group score

Preparing data for analysis
tabulation and coding procedures

code : ID for each participant (e.g. 1 for M and 2 for F )

tabulation : organising data, 2 x 2 factorial

scoring procedures

self-developed instruments

standardised instrument (follow test manual)

9_Inferential Statistics

Test of significance
Chi Square (nominal data)
ANOVA one way (two or more means)

post hoc test (determine which means are significantly different from other means)

pretest-posttest

t-test for pretest, if the difference of significant, then ANCOVA (analysis of covariance)

t-test for pretest, if the difference is not significant, then t-test on the posttest

t Test (two means)
One-tailed test (one direction)
Two-tailed test (two direction) A=B
sampling error (a statistical error that occurs when an analyst does not select a sample that represents the entire population of data)
normally distributed

standard error of the mean (SD > bahaya , so kena cut)

mean of the means

Standard Error

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sampling error - expected variation among the means
chances of any sample being exactly indentical to its population are virtually nil.
not affect realability
inferences about about populations based on the results of samples

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10_Qualitative Research

Cyclical process
Qualitative research

Interpreting

Classifying

Describing the context and participants

Reading/memoing

Data managing

multistage process of organising, categorising, synthesising, interpreting, and writing about the data
Approaches
Historical research
Action research ( a study that can solving problem)

step 4: collect data

Triangulation (combination of qualitative, quantitative and documentation) - used for corrobrate data

Threat quality

observer effect

observer bias

Halo effect (initial impressions concerning an observe affect subsequent observations)

observation

memo writing (a form of thinking on paper)

Field notes (records of what the observer has specifucally seen or heard - emid data)

Protocol (process / checklist) - step by step

types

external or nonparticipant oberver (one who wathces but does not participate)

participant observer

interview

types

semistructured (combination)

unstructured (question being prompted by the flow of the interview)

structured (a specified set of questions)

experiences and feelings

step 3: selecting research participants

step 2: reviewing the literature

step 1 : selecting a research topic

Symbolic interaction
Phenomenology
Grounded theory
Ethnomethadology
Ethology (aims to generate a theory that explains, at a conceptual level, a process, and action, or a concept) - observation and interviews
Ethanography (seeks to describe and analyse all or part of the culture of a community by identifying and describing)
Case study
General steps

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Reporting, evaluating, and interpreting research
Analysing data
Collecting data
Selecting participants
Review of research
Indentify research topics
Nature

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understanding of a social setting or activity as viewed from the perspective of the research participants

11_Action Research

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Conducting
Taking action

leads to : new question, new forms of understanding and deeper insights in practice

help understand or try out new or needed methods

Carry out planning and share the findings (verbally or written)
Analyse and interpret the collected data
Collect data

spiraling nature (looking;observes the setting, thinking;interprets, acting;identifies a solution)

concept of triangulation (e.g. interview, observation, survey, etc)

Identify a topic or issue to study

developing research questions

conducting a literature review

Characteristics
Five C's

change

consideration

concern

collaboration

commitment

help to make informed decisions-decisions that are data driven
an approach designed to develop and improve practice

6_Correlation Research

Process
Data analysis

curvilinear relationship

linear relationship

computing a correlation coefficient

Data collection

identify variables - indentify population(select a sample) - administer instruments - collect data (short period of time)

Data analysis and Interpretation (indicates the size and direction of a relationship)

reliability

low .70s

moderate .80s

high .90s

near -1.00 (high size and -ve direction)

near 0.00 (variables not related)

near +1.00 (high size and +ve direction)

Design and Procedure
Participant and Instrument Selection (30 min participants)
Problem selection
Purpose
determine relationships between variables OR use these relationships to make predictions
Definition
degree of relationship
determine whether, and to what degree, a relationship exists between two or more quantifiable variables

5_Experimental Research

Quasi-Experimental Research (studies that aim to evaluate interventions but that do not use randomization)
Pretest-Posttest, Nonequivalent Control Group Design ( a treatment group that is given a pretest, receives a treatment, and then is given a posttest)
Posttest-Only, Nonequivalent Control Group Design (participants in one group are exposed to a treatment, a nonequivalent group is not exposed to the treatment, and then the two groups are compared)
Experimental Designs
Repeated Measures Designs (an experimental design where the same participants participate in each independent variable condition)
Factorial Designs (an experiment that has multiple factors or independent variables)
Solomon Four-Group Design
Pretest-Posttest Control Group Design (a true experimental research design that tests two groups before and after both groups receive the independent variable)
Posttest-Only Control Group Design (control for most of the same threats to internal and external validity as the classic controlled experimental design.)
Experimental Validity
Threats

Differential selection of subjects

Statistical regression

Instrumentation

Maturation

History

External validity

deals wirh the extent of generalisability of the results

Internal validity

basic minimum of control, measurement, analysis, and procedures necessary to make the results of the experiment interpretable

Criteria (Well-Designed Exp)
Parsimony

all characteristics being equal, a simpler design is preferred to a more complex one

Representativeness
No confounding of relevant variables
Uncontaminated data
Adequate information from the data
Basis for comparison
Lack of artificiality
Adequate experimental control
Experiment?
a research situation in which at least one independent variable, called the experiment variable, is deliberately manipulated or varied by the researcher.

Experiment Variables

an independent variable but not all independent variables are experimental varibales

4_Selecting a Sample

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Selecting a nonrandom sample
quota sampling

obtained from easily accessible individuals

data gatherers are given exact characteristics and quotad of persons to be interviewed

purposive sampling

units are selected because they have characteristics that you need in your sample

convenience sampling

units are selected for inclusion in the sample because they are the easiest for the researcher to access.

Determining sample size
10-20% of population (descriptive research)
Basic random sampling techniques
Systematic sampling

a probability sampling method where researchers select members of the population at a regular interval

Cluster sampling (most useful & feasibls method) (less time and expense)

a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample

Stratified sampling

researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Simple random sampling

a type of probability sampling in which the researcher randomly selects a subset of participants from a population.

Definition
POPULATION - the group of interest to the research to which the result of the study will ideally generalise (first step in sampling)

Accessible population (realistically select from)

Target population (generalise)

SAMPLING - process of selecting a number of participants for a study in such a way that they represent the larger group from which they were selected (population).

3_Selecting and Defining a Research Topic

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A good hypotheses
testable
clearly states the expected relationship between defined variables
provides a reasonable explanation for the predicted outcome
based on sound reasoning
Review of related literature (start with backgorund of studies)
Analysing, organising, and reporting the literature
Astracting

involves locating, reviewing, summarising, and classifying references

evaluating the sources

Quality (e.g. date of publication, refereed or not journals - must have peer review , evidence to support interpretations)

relevancy (keyword - at least 3)

when to stop ??? when search and benda sama je yang kua
f(x) - determine what has already been done / what needs to be done / rationale for research hypthesis / facilitates interpretation of study results.
Identify, locate and analyse documents
Stating the research topic
Qualitative (more general initially)
Quantitative (specific)
Characteristics of GOOD research topic
Ethical
Manageable
Significant (contributes to the improvement)
Researchable (can be investigated thru collection and analysis of data)
Interesting
Sources of research topics
Library search

most useful after a topic has been narrowed

Replication

not identical but altered

Personal questions

observe surrounding environments, society, news articles, and ask questions

Theories
Identify a topic or question to research
realities of research andf topic indentification

Non linear

True research

identified topic - plan to carry out the research - collect pertinent data - analyse - make research outcome available

solving problems rather than finding a problem or topic to study

2_Ethics in RESEARCH

Basic Principles of ethical research

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Protection from harm (both physically and psychologically)
Withdrawal from the investigation - participants rigth to withdraw at any time
Deception
Debriefing - provide any necessary info about the nature of the research
Confidentiality
Coercion - not be forced into participation
Informed consent

1_Introduction to RESEARCH

Limitation: Scientific and Disciplined Inquiry Approach

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the need to address participants' ethical needs and responsibilities
limitions of measuring instruments
inability to capture the full richness of the research site and participants' complexity
inability to answer 'should' questions
Fundamental differences

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Qualitative

small number of participants

interact extensively

uncontrolled context

Not to state hypotheses before data are collected

Quantitative

large number of participants

rarely interact

controlled context

state hypotheses before data are collected

Understanding things

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Deductive (general to specific) - quantitative

developing specific predictions from general principle, observtions, or experiences

Inductive (specific to general) - qualitative

developing generlisations from limited number of related observations or experiences

Purpose : primary research

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inquiry to gain understanding about some problems
Purpose : secondary research

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raising new topics/question to study
using the results in appropriate contexts
helping others understand the research results