What are the main types of qualitative approaches to research?
While there are many different investigations that can be done, a study with a qualitative approach generally can be described with the characteristics of one of the following three types:
Historical research describes past events, problems, issues and facts. Data are gathered from written or oral descriptions of past events, artifacts, etc. It describes “what was” in an attempt to recreate the past. It is different from a report in that it involves interpretation of events and its influence on the present. It answers the question: “What was the situation?”
Examples of Historical Research:
- A study of the factors leading to the historical development and growth of cooperative learning
- A study of the effects of the historical decisions of the United States Supreme Court on American prisons
- A study of the evolution of print journalism in the United States through a study of collections of newspapers
- A study of the historical trends in public laws by looking recorded at a local courthouse
Ethnographic research develops in-depth analytical descriptions of current systems, processes, and phenomena and/or understandings of the shared beliefs and practices of a particular group or culture. This type of design collects extensive narrative data (non-numerical data) based on many variables over an extended period of time in a natural setting within a specific context. The background, development, current conditions, and environmental interaction of one or more individuals, groups, communities, businesses or institutions is observed, recorded, and analyzed for patterns in relation to internal and external influences. It is a complete description of present phenomena.
One specific form of ethnographic research is called a case study. It is a detailed examination of a single group, individual, situation, or site.
A meta-analysis is another specific form. It is a statistical method which accumulates experimental and correlational results across independent studies. It is an analysis of analyses.
Examples of Ethnographic Research:
- A case study of parental involvement at a specific magnet school
- A multi-case study of children of drug addicts who excel despite early childhoods in poor environments
- The study of the nature of problems teachers encounter when they begin to use a constructivist approach to instruction after having taught using a very traditional approach for ten years
- A psychological case study with extensive notes based on observations of and interviews with immigrant workers
- A study of primate behavior in the wild measuring the amount of time an animal engaged in a specific behavior
Narrative research focuses on studying a single person and gathering data through the collection of stories that are used to construct a narrative about the individual’s experience and the meanings he/she attributes to them.
Examples of Narrative Research:
- A study of the experiences of an autistic student who has moved from a self-contained program to an inclusion setting
- A study of the experiences of a high school track star who has been moved on to a championship-winning university track team
PPA 696 RESEARCH METHODS
Pre-experimental DesignCross-Sectional Design
Longitudinal Designs
Time Series Design
Panel Design
Case Study Design
Control over Sources of Invalidity
How to Improve Designs for Description
PRE-EXPERIMENTAL DESIGNS
In general, a research design is like a blueprint for the research. A research design is a plan that guides the decision as to:-when and how often to collect data
-what data to gather and from whom
-how to analyze the data
More specifically, a research design refers to the type of study that will be conducted, whether it will be pre-experimental, quasi-experimental, or true experimental.
Pre-experimental designs include: -case study design -one group pre-test/post-test design -static group comparison design (cross-sectional study) Quasi-experimental designs include: -time series design (may include panel design) -equivalent time samples design -equivalent materials design -nonequivalent control group (comparison group) design -counterbalanced design -separate sample pre-test/post-test design -separate sample pre-test/post-test control group design -multiple time-series design -recurrent institutional cycle design -regression/discontinuity analysis True experimental designs include: -pre-test/post-test control group design -Solomon four-group design -post-test only control group design Research Methodology concerns how the design is implemented, how the research is carried out. The methodology employed often determines the quality of the data set produced. Methodology is concerned with: -when and how often to collect data -construction of data collection measures -identification of the sample or test population -choice of strategy for contacting subjects -selection of statistical tools -presentation of the findingsPre-Experimental Designs for Description
Descriptive research can provide data for monitoring and evaluating policies and programs. These designs are concerned with how to answer questions such as: -how many? -how much? -how efficient? -how effective? -how adequate? Cross-Sectional DesignA cross-sectional design is used for research that collects data on relevant variables one time only from a variety of people, subjects, or phenomena. The data are collected all at the same time (or within a short time frame).
A cross-sectional designs provides a snapshot of the variables included in the study, at one particular point in time. It may reveal how those variables are represented in a cross-section of a population. Cross-sectional designs generally use survey techniques to gather data, for example, the U.S. Census.
Advantages and Disadvantages of Cross-Sectional Designs
Advantages | Disadvantages |
data on many variables | increased chances of error |
data from a large number of subjects | increased cost with more subjects |
data from dispersed subjects | increased cost with each location |
data on attitudes and behaviors | cannot measure change |
answers questions on who, what, when, where | cannot establish cause and effect |
good for exploratory research | no control of independent variable |
generates hypotheses for future research | difficult to rule out rival hypotheses |
data useful to many different researchers | static, time bound |
Longitudinal Designs
A longitudinal design collects data over long periods of time. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. There are two different types of longitudinal designs: time series and panel.
A Time Series Design collects data on the same variable at regular intervals (weeks, months, years, etc.) in the form of aggregate measures of a population. For example, the Consumer Price Index (CPI), the FBI Uniform Crime Rate, unemployment rates, poverty rates, etc.
Time series designs are useful for: -establishing a baseline measure -describing changes over time -keeping track of trends -forecasting future (short term) trends Time series data are nearly always presented in the form of a chart or graph. The horizontal (or x) axis is divided into time intervals, and the vertical (y) axis shows the values of the dependent variable as they fluctuate over time.Researchers inspect a time series graph to look for four types of patterns: -long term trends (increases or decreases over the whole time span); -cyclical variations (short-term, valley-to-valley or peak-to-peak cycles); -seasonal variations (due holidays or weather); -irregular fluctuations (none of the above). Advantages and Disadvantages of Longitudinal Designs
Advantages | Disadvantages |
data easy to collect | data collection method may change over time |
easy to present in graphs | difficult to show more than one variable at a time |
easy to interpret | needs qualitative research to explain fluctuations |
can forecast short term trends | assumes present trends will continue unchanged |
Panel Designs collect repeated measurements from the same people or subjects over time. Panel studies reveal changes at the individual level, for example, when a particular person was employed or unemployed, or when they were on or off of welfare.
Panel data can show different patterns from time series data. For example, about 5% of the elderly are institutionalized at any one time, but it is not always the same people. So elderly people have a 20% chance of being institutionalized at some point.
Advantages and Disadvantages of Panel Designs
Advantages | Disadvantages |
reveals individual level changes | difficult to obtain initial sample of subjects |
establishes time order of variables | difficult to keep the same subjects over time |
can show how relationships emerge | repeated measures may influence subjects behavior |
Case Study Design
Advantages and Disadvantages of Case Study Design
Advantages | Disadvantages |
includes data from multiple perspectives | limited to contemporary phenomena |
combines data from different sources | need direct access to subjects |
need diverse sources of information | |
need skills in many techniques | |
can be an intense experience | |
difficult to replicate findings | |
insiders can be biased | |
outsiders can be naive | |
difficult to draw boundaries |
Focus Groups
Focus groups are a method of group interviewing for obtaining qualitative data. It is not so much a research design as a data collection method. More will be said about focus groups in the section on data collection.
Meta-Analysis
A meta-analysis is a quantitative analysis of a sample of existing research studies on a particular topic. It is used to draw conclusions about the topic from a range of studies, for
example, identify aspects of a program associated with program success. A meta-analysis may also generate new hypotheses for future research.
Control Over Sources of Invalidity in Designs for Description
Source | Case study | Cross-section | Panel | Time-series |
Internal Validity | ||||
History | weak | weak | weak | weak |
Maturation | weak | weak | strong | strong |
Testing | strong | strong | ||
Instrumentation | weak | ? | ? | |
Regression | weak | strong | strong | |
Selection | weak | weak | weak | strong |
Mortality | weak | weak | strong | |
Design Contamination | ? | strong | ||
External Validity | ||||
Testing | weak | weak | ||
Selection | weak | weak | weak | ? |
Experimental Arrangements | ? | ? | ||
Multiple Interactions |
How to Improve the Validity of Designs for Description
1. Case study design2. One-group Pre-Test/Post-Test Design
3. Non-randomized comparison group Pre-Test/Post-Test Design
4. One-group Time Series Design
O1 | O2 | O3 | X | O4 | O5 | O6 |
Another way to improve the validity of designs for description:
1. Case study design
2. Randomized Control Group Post-Test only design
3. Randomized Control Group Pre-Test/Post-test design
4. Control group Time Series Design
O1 | O2 | O3 | X | O4 | O5 | O6 |
O1 | O2 | O3 | O4 | O5 | O6 |