Quantitative Studies: Descriptive/Survey, Causal-Comparative, Correlational, Experimental

Descriptive/Survey Causal-Comparative Correlational Experiment

Purpose To describe current conditions To explore relationships among

variables that cannot be actively

manipulated or controlled by the

researcher

To ascertain the extent to which two

or more variables are statistically

related

To establish cause and effect

relationships between variables

Examples What are the attitudes of parents,

students, and teachers to an extended

school year?

To what extent are elementary

teachers using math manipulatives?

What is the effect of part-time

employment on the achievement of

high school students?

What characteristics differentiate

students who dropout from those who

do not?

What are the effects of smoking on

health?

What is the relationship between ACT

scores and freshmen grades?

Do significant relationships exist

between the types of activities used in

math classrooms and student

achievement?

Examine the effect of teaching with a

1) co-operative groups strategy or 2)

traditional lecture approach on

student’s achievement

Examine the effect of teaching with

manipulatives or a traditional

algorithm approach on the test scores

of algebra students

Characteristics Use of large samples

Use of tests, questionnaires, and

surveys

Focused on information related to

preferences, attitudes, practices,

concerns, or interests

Statistical analysis of numerical data

Selection of subjects from at least two

groups in which the cause (i.e., the

independent variable) has already

occurred

Statistical comparisons of the effect

(i.e., the dependent variable) using at

least two groups

Measurement with a correlation

coefficient

One group of subjects measured on

two variables

Use of instruments to measure

variables

Focused on the direction and nature of

the relationship

Stringent procedures for selecting

subjects and assigning them to groups

Manipulation of the causal variable

Control of extraneous variables

Statistical analysis of numerical data

Potential

Problems

Instrument development

Low response rates

Honest responses from subjects

Inferring cause and effect

relationships

Instrument development

Inferring cause and effect

relationships

Inability of researcher to adequately

control extraneous variables

Use of complicated research designs

Complex statistical analyses of data

Qualitative Studies: Biography, Phenomenology, Grounded Theory, Ethnography, Case Study, (Hybrid of these)

Type of Study

(keyword)

Biography/Historical

(one person/(event)

Phenomenology

(Meaning)

Grounded Theory

(Theory/Model)

Ethnography

(Culture/Group)

Case Study

(Big Picture/System)

Purpose To explore the life of one

individual.

To gain insight into past events,

issues, of personalities to better

understand the current situation

To understand what an

experience or phenomenon or

behavior means to a sample

of people and how they

construct those meanings.

To develop a theory or

theoretical model where none

exists in the literature relative

to the sample.

To describe and interpret a

cultural or social group of

people to another culture or

group.

To develop and in-depth

analysis of a single case

(organization, family, event,

etc.) or multiple cases,

wherein all of the possible

internal and external

relationships are considered.

Examples A study of Abraham Lincoln’s

life.

Current parochial school

policies can be better

understood with knowledge of

the role these schools have

played in the education of

students in the community for

the last fifty years

A description of the “caring

interaction” between a nurse

and his or her patient (i.e.,

What is essential for the

experience to be described by

the client as being a caring

interaction?)

What theories underlie the

school change efforts of

teachers in a parochial

elementary school?

What underlying theory

explains teacher’s changing

from traditional assessment

beliefs and practices to

alternative, performance-

based assessment beliefs and

practices?

What is the nature of the

problems a teacher

encounters when he begins

using a constructivist

approach to instruction after

having taught for ten years

using a very traditional

approach?

Campus reaction to a gunman

incident in which a student

attempted to fire a gun at his

classmates.

Characteristics Focus on specific individuals,

social issues, events, or policies

Documents and artifacts are the

primary sources of data, but

interviews and observations can

also be used

Data is already available and is

complied, presented, and

interpreted

Data is examined carefully for

authenticity and truthfulness

Describes the lived

experiences for several

individuals about a concept or

phenomenon.

Search for meaning of an

experience.

Long, open-ended interviews

with up to 10 people who

shared the experience

(questionnaires are ok if you

must)

Ask three things:

1. What happened?

2. What does it mean?

3. How did you come to

that conclusion?

Respect for participant’s

beliefs and views

Qualitative data collection

using analytic strategies

In-depth, structured

(saturation) interviews are

built around categories that

define the issue and

conducted with 20-30 people

(questionnaires ok if you

must)

Inductively reasoned

synthesis of data through the

use of constant comparison

analysis

Conceptual nature of the

process

The study is conducted in the

natural setting for a lengthy

period of time

Emerging research design

Participants are observed in

naturally occurring activities

Researchers develops trust

with participants

Cyclical nature of data

collection and analysis

Observation and interviews

are the dominate data

collection strategies

Inductive nature of the data

analysis

The case is studied within its

setting and described this way

Gain confidence and trust of

participants

Data collection is extensive

and collected from multiple

sources—documents, archival

records, interviews,

observations, physical

artifacts, questionnaires

Data are themed, tell a story

Potential

Problems

Authenticity

Truthfulness

Reliance on secondary sources

Values of researcher can affect

interpretation

Participants selection—need

to have experienced the

phenomenon

May be hard to

interpret/analyze/

summarize/classify the

“essence” of the experience.

Researcher bias

Poor data collection strategies

Difficulty analyzing data

Insufficient time spent in the

field

Poor data collection efforts or

insufficient data collected

Poor data analysis

Researcher bias

Insufficient time spent in the

field

Poor data collection efforts or

insufficient data collected

Poor data analysis

Researcher bias