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QUANTITATIVE & QUALITATIVE EDU702

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INTRODUCTION • • • •

Two types research in education Differ in the nature data is collected Quantitative and Qualitative Also known as Positivist & Postpositivist respectively • Qualitative is sometimes called case study

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Quantitative & Qualitative

Quantitative

• Knowledge is developed by collecting numerical data on observable behaviors • The data is subjected to numerical analysis

Qualitative

• Knowledge is developed by primarily verbal data through intensive study of cases • The data is subjected to analytical analysis

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Quantitative & Qualitative • Quantitative focuses on populations samples • Qualitative focuses on the study of cases

and

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Quantitative vs Qualitative • Is one approach better than the other? • Do they complement each other in some way? • Do they produce conflicting findings? Answers: • Qualitative – best to discover themes and relationship at case level (discovery) • Quantitative – bet used to validate those themes and relationships in samples and population (confirmatory)

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Learning Styles Qualitative

Interview

•Visual •Auditory •Reading / Writing preference •Kinesthetic

Quantitative

Create & Distribute Survey

•Visual •Auditory •Reading / Writing preference •Kinesthetic

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DIFFERENCES Quantitative

Qualitative

Assume an objective social role

Social reality is constructed by the participants in it

Social reality is relatively constant over time

Social reality is continuously constructed in local situations

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DIFFERENCES Quantitative

Qualitative

View causal relationship among social phenomena from a mechanistic perspective

Causal relationship is human intention

Detached, objective from participants & setting

Personally involved

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DIFFERENCES Quantitative

Qualitative

Study populations & samples

Study cases

Study behavior & observable phenomenon

Study meanings created and internal phenomenon

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DIFFERENCES Quantitative

Qualitative

Analyze social realities into variables

Make holistic observations

Use preconceived concepts & theories to determine data to collect

Discover concepts & theories after data collected

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DIFFERENCES Quantitative

Qualitative

Generate numerical data

Generate verbal & pictorial data

Use statistical method to analyze data

Use analytic induction to analyze data

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DIFFERENCES Quantitative

Qualitative

Use statistical inference procedure to generalize findings

Generalize case findings by searching for other similar cases

Prepare impersonal, objective report of research findings

Prepare intepretive report that reflect researchers’construction of the data & awareness that readears will form

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QUANTITATIVE RESEARCH METHODOLOGIES Methodologies • Experimental • Single subject • Correlational • Causal comparative • Survey

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Experimental Research • Attempts to influence/manipulate a variable • Best for testing hypotheses of cause-and-effect relationship • In education – use to test effects of various practices e.g.: ▫ ▫ ▫ ▫

Teaching techniques Organization of curriculum Content Instructional programs etc

• On outcomes e.g.: ▫ Academic achievement ▫ School climate etc.

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EXPERIMENTAL RESEARCH • Looking at the effect(s) of independent variable(s) on 1 or more dependent variables • Independent variable aka: ▫ Experimental, treatment, intervention

• Dependent variable aka: ▫ Criterion, posttest

• Involves: ▫ One group receiving the experimental treatmentexperimental group ▫ One comparison group not receiving the treatment – control group

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EXPERIMENTAL RESEARCH Experimental

A new reading program

Pre-test test

Post-Test Post

Control

Regular reading program

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EXPERIMENTAL RESEARCH • Randomization a key element ▫ Random assignment of students to experimental and control group ▫ To make the groups equivalent – differ only by chance

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VALIDITY PROBLEMS • Problem in establishing suitable controls – that the posttest result is only influence by the treatment • Control against or elimination of extraneous variables ▫ Affect the internal validity of the experiment

• Extraneous varibale ▫ Any variable other than the treatment variable that, if not controlled, can affect the experimental outcome

• Internal validity ▫ The extent to which extraneous variables have been controlled by the researcher so that any observed effect can be attributed solely to the treatment variable

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EXTRANEOUS VARIABLES History

• Influence of other events

Maturation

• Physical & psychological changes

Testing Instrumentation

• Test – wise • Tend to be biased in marking the posttest

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EXTRANEOUS VARIABLES Statistical Regression

• When using the same pre and post test

Differential Selection

• No random selection

Experimental Mortality

• Drop out, missed test, absent

Selection Maturation • Difference in age Interaction

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EXTRANEOUS VARIABLES Experimental Treatment Diffusion

• Control group seek access to treatment

Compensatory Rivalry by Control Group

• Control group work to perfom better – John Henry Effect

Compensatory Equalization of Treatments

• CG given something equal

Resentful Demoralizartion of CG

• CG become discouraged, affect post test

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TYPES OF EXPERIMENTAL DESIGN Single Group

• One shot case study • One group pre-post test • Time-series

True Experimental

• Randomized pre-post test control group design • Randomized posttest only control group

QuasiExperimental

• Static-group • Nonequivalent control-group

Factorial

• Two factor • Three factor

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CORRELATIONAL RESEARCH • Purpose – to discover relationships between variables through correlational statistic

Explanatory

• Relationship between anxiety & self-esteem • Between intelligence & academic achievement

Prediction

• SPM results and college CGPA • Level of education and potential income

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CORRELATIONAL RESEARCH • Relationship can be postive or negative • Relationship is presented in a scattergram (scatter plot)

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CORRELATIONAL RESEARCH Positive Correlation

Negative Correlation

Absence of Correlation

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CORRELATIONAL RESEARCH • The more education people have, the greater the income ▫ Positive or negative relationship?

• As people get older, they often lose their memory ▫ Positive or negative relationship?

• Can we say: ▫ Education causes higher income? ▫ Aging causes memory loss?

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CORRELATIONAL RESEARCH

•NO • Correlation is not equal to causation • All we can say is that there’s is a relationship between these two variables • Although we think the relationship is causal, we cannot assume without conducting experiment

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CAUSAL COMPARATIVE • The study of cause-and-effect relationship • To explain educational phenomenons • Attempts to determine the cause, or reason, for pre-existing differences in groups of individuals • Also called ‘ex post facto’ (Latin – after the fact) • Both the effect and the alleged cause have already occurred and must be studied in retrospect • The basic causal-comparative approach involves starting with an effect and seeking possible causes • Another approach starts with cause and investigates its effects on some variable

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CAUSAL COMPARATIVE • The presumed cause – independent variables • The presumed effect – dependent variables • Example: ▫ Introduction of KPI on teachers’ morale ▫ Introduction of KPI– independent variables ▫ Teachers’ morale – dependent variables

• Or ▫ Teachers’ morale – independent variable ▫ Absenteeism – dependent variable

• Different from experimental, causal comparative does not manipulate variables (sex, ethnicity etc)

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CAUSAL COMPARATIVE • IV: presumed cause ▫ Groups formed on the basis of how much TV they watch, and compared on academic achievement (GPA).

• DV: presumed effect ▫ Groups formed on the basis of gender, and compared on strength of career aspirations.

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CAUSAL COMPARATIVE • IV: presumed effect ▫ Groups formed on the basis of whether they dropped out of high school, and compared on lack of mentoring relationship.

• DV: presumed cause ▫ Groups formed on the basis of difficulty in learning to read, and compared on time parent spent reading to child.

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CAUSAL COMPARATIVE When to use: 1. When it is unethical to manipulate an independent variable (e.g. diet) 2. When the independent variable CANNOT be manipulated (e.g. sex, ethnicity, etc.) 3. When the independent variable not been changed due to ignorance or negligence (e.g. teaching methods)

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CAUSAL COMPARATIVE • Examples: ▫ A researcher measured the mathematical reasoning ability of young children who had enrolled in Montessori schools and compared the scores with a group of similar children who had not been to Montessori schools. ▫ A researcher measured the frequency of students’ misbehavior at schools which use corporal punishment and compared that to schools which did not use corporal punishment.

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CAUSAL COMPARATIVE • How do you analyze: ▫ t tests, ANOVA, ANCOVA when two or more groups are being compared. ▫ Regression analysis when there are multiple independent variables. ▫ MANOVA, and multivariate regression, when there are multiple dependent variables. ▫ Path analysis and structural equation modeling when the theoretical causal paths are being investigated.

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CAUSAL COMPARATIVE • Which of the following questions would lend themselves well to causal-comparative research? 1. How many students were enrolled in PSYC101 this semester? 2. Which subject do high school students like least? 3. How do elementary school teachers teach phonics? 4. Are two-year-old girls more aggressive than twoyear-old boys? 5. How might Jimmy Thomas be helped to read? 6. Is teacher enthusiasm related to student success in academic classes? 7. What is the best way to teach arithmetic? 8. Do female students perform better in literature classes than male students? 9. Does sleep (amount of time) affect academic performance of students at college

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CAUSAL COMPARATIVE • Example ( Green & Jaquess) ▫ The effect of part-time employment on high school students’ academic achievement ▫ Sample – 44 high school juniors, employed and not employed (have already occurred, you do not make them work – unethical)

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SURVEY RESEARCH • Also known as Descriptive Research • Purpose – to describe the natural or man-made phenomena ▫ The form, actions, changes similarities with other phenomena

over

time,

• In education – it involves making careful description of educational phenomena • Concerned primarily with determining “what is”

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SURVEY RESEARCH • Examples: ▫ How many teachers in the state of Selangor hold favourable attitudes toward ETeMS? ▫ How do adolescent spend their time? ▫ What have been the reactions of school administrators to innovations in teaching physical science?

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SURVEY RESEARCH Types of survey: • Cross-sectional • Longitudinal

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SURVEY RESEARCH • Cross - sectional ▫ Data are obtained at one point in time but groups of different ages, or different stages of development

• Example: ▫ How students’ attitude towards art change from Year 5 to Form 3? ▫ Samples are selected from each grade ▫ Administer a questionnaire to all of them on the same date or within narrow range of dates

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SURVEY RESEARCH • Longitudinal ▫ Collecting data from a sample at different points in time in order to study changes and continuity in the sample’s characteristics

• Example: ▫ The development of art appreciation among primary school children

• Types: ▫ ▫ ▫ ▫

Trend Cohort Panel Cross sectional

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SURVEY RESEARCH

Trend Cohort Studies

• Describe change by selecting a different sample at each data collection point of same population which may change • Attitudes of principal towards cluster schools in Malaysia • 2010 – one sample, 2011- another sample

• Describe change by selecting a different sample at each data collection from population which remains the same

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SURVEY RESEARCH

Panel

• Using the same sample at different point of data collection • Follow individuals over time to note changes • Teaching effectives of ED725 graduate of 2012 • Data collected on same group in 2013, 2015

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SURVEY RESEARCH • Measurement types ▫ ▫ ▫ ▫ ▫

Questionnaire Classroom observation checklist Standardized achievement tests Attitudes scales Interviews

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SURVEY RESEARCH • Statistics in survey research ▫ Measures of central tendency
Mean
Median
Mode

▫ Measures of variability
Standard deviation
Variance
Range

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QUALITATIVE RESEARCH • General Features (may not be in all types) ▫ The natural setting is the direct source of data and the researcher is the key instrument ▫ Qualitative data are collected in the form of words or pictures rather than numbers ▫ Qualitative researchers are concerned with process as well as product ▫ Qualitative researchers tend to analyze their data inductively ▫ How people make sense of their lives is a major concern to qualitative research

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QUALITATIVE – MAJOR CHARACTERISTICS Natural inquiry

Inductive analysis

Holistic perspective

Qualitative data

Personal contact and insight

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QUALITATIVE – MAJOR CHARACTERISTICS Dynamic

Unique case orientation

Context sensivity

Emphatic neutrality

Design flexibility

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QUALITATIVE – STEPS 1. 2. 3. 4. 5. 6.

Identification of the phenomenon Identification of the participants Generation of hypotheses Data collection Data analysis Interpretations and conclusions

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QUALITATIVE – APPROACHES

NARRATIVE RESEARCH

PHENOMENOLOGY

GROUNDED THEORY

CASE STUDIES

ETHNOGRAPHIC

HISTORICAL

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NARRATIVE •Study life experiences of people •As told to the researcher •The participant recalls one or more special events (epiphany)

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PHENOMENOLOGY • Reactions to or perceptions of a particular phenomenon • e.g. what is like to teach science in rural school • Data – through in-depth interview • Seek to identify, understand & describe commonalities of perceptions & interpretations • Malay students in Chinese schools • Data collected are clustered into themes

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GROUNDED THEORY • Intention is to generate theory in data from participants who have experienced the process • Generalizations are developed from the data • Use of constant comparative method • Data collected through one-on-one interview, focus group, observations

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PROCESS OF GROUNDED THEORY Data collected & analyzed

Theory suggested

More data collected

Theory further developed, clarified

More data collected

Theory revised

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CASE STUDIES • Objects of research are called cases • A case – a particular instance of a phenomenon • Phenomenon: • Programs • Curricula • Roles • Events

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CASE STUDIES •Widespread in education •Purpose: •To produced detailed description of a phenomenon •To develop explanation of it •To evaluate it

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CASE STUDIES •Example •Dona Kagan examined the effects of a staff development program on the professional lives of 4 elementary school teachers •Audio-taped 90 minute interview

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ETHNOGRAPHY • First hand, intensive study of the features of a given culture and the patterns in those features • If reader can understand the culture by reading an ethnographic research, then it is a good research • Originally developed by anthropologist • Data collected through, observation, interview and documents • Participant observation – be part of the culture and make observation

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ETHNOGRAPHY • Examples: • The Orang Asli school • Racial interactions in urban school • Bullying in secondary school • Power in the dorm • Teachers teaching style • Practicum trainees

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HISTORICAL RESEARCH •Systematic process of data collection to answer questions about a phenomenon for the purpose of gaining a better understanding of present institutions, practices, trends, and issues in education

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HISTORICAL RESEARCH •Examples: •The changes in the status of teachers in the public eyes from 1900 – 2000 •Pondok schools •Art curriculum over the years

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HISTORICAL RESEARCH • Purpose: • To make aware of past failures & success • To learn from the past to improve the present / future • To assist making prediction • To test hypotheses concerning relationships or trends • To understand present educational policies and practices more fully

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HISTORICAL RESEARCH •Sources •Documents •Numerical records •Oral statements •Relics

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