Research Methods in Industrial /Organizational Psychology Flashcards
1
Q
Goals of I/O Psychology Research Methods
A
- The basic goals are: to describe, explain, and predict work behavior.
- For example, an I/O psychologist might
attempt to satisfy the first goal by describing the production levels of a company - The goal of explaining is achieved when the I/O psychologist attempts to discover why certain work behaviors occur.
- The goal of prediction aims to use psychological test scores to forecast optimal candidates for management roles.
2
Q
The Research Process
Step 1: Formulation of the Problem
A
- Research begins by identifying a specific problem or topic for investigation.
- Researchers may select topics based on personal interests or influenced by previous research.
- External factors such as client needs or organizational issues can also dictate research focus.
3
Q
The Research Process
Step 2: Generation of Hypotheses
A
- The next step in the research process involves generating hypotheses, which are statements about the relationships between variables.
- Variables are the elements that researchers intend to measure, such as job satisfaction, worker productivity, and absenteeism.
- Hypotheses are tested through the collection and analysis of systematic observations of behavior, which lead to the development of theories or models.
4
Q
The Research Process
Step 3: Selecting the Research Design
A
- After generating hypotheses, the researcher selects a research design based on factors such as the research setting and the degree of control over the setting.
- The organization’s constraints may require observational measurements or the use of existing data.
5
Q
The Research Process
Step 4: Collection of Data
A
- Testing hypotheses involves data collection, guided by the research design.
- Sampling is crucial, selecting a representative group from a larger population.
- Random sampling ensures each individual in the population has an equal chance of being selected.
- Random sampling guards against biases in participant selection.
- Stratified sampling divides the population into subgroups based on important variables.
- Both sampling techniques aim to ensure accurate representation.
6
Q
The Research Process
Step 5: Analyses of Research Data
A
- Data collected in research undergo analysis for interpretation.
- Statistical methods are commonly used for quantitative data (numerical values).
- Qualitative data analysis techniques are also utilized for non-numerical data.
- Statistical analysis involves quantifying research observations and can help identify causes of observed outcomes.
7
Q
The Research Process
Step 6: Interpretation of Research Results
A
- Interpretation of results involves drawing conclusions from research findings.
- Researchers assess the meaning of the results and their relevance to real-world work behavior.
- Possible limitations of the findings are considered, such as applicability to specific contexts.
8
Q
Dependent Variable
A
- The dependent variable is the main outcome or behavior being studied in an experiment.
- Changes in the dependent variable are attributed to the manipulation of the independent variable.
- Comparing the dependent variable in treatment and control groups helps to determine the effectiveness of the treatment.
- Measuring the dependent variable in the control group helps to account for natural fluctuations that might occur without the treatment.
9
Q
The Experimental Research Design
A
- The experimental method involves manipulating an independent variable and measuring its effect on a dependent variable.
- It allows researchers to determine cause-and-effect relationships among variables.
- In experimental designs, researchers compare treatment and control groups to assess the effectiveness of the treatment.
- Extraneous variables, which are factors other than the independent variable that can influence the dependent variable, must be controlled.
- Random assignment of participants helps to control for extraneous variables.
10
Q
The Quasi-Experimental Method
A
- Quasi-experiments mimic the experimental method but lack random assignment and manipulation of the independent variable.
- They compare groups that underwent different treatments but weren’t randomly assigned, complicating cause-and-effect determinations.
- Common in I/O psychology due to difficulties in controlling variables, they often compare groups or organizations rather than individuals.
11
Q
The Correlational Research Design
A
- The correlational method examines natural relationships between variables without manipulating them.
- Variables are measured and statistically analyzed without categorizing them as independent or dependent.
- A major drawback is the inability to determine cause-and-effect relationships.
- Caution must be exercised when interpreting results, as correlations may be influenced by third variables or reverse causality.
- For example, a correlation between workers’ attitudes and stock purchases does not necessarily imply causation, as other factors like tenure or age may influence both variables.
12
Q
Meta Analysis
A
- Meta-analysis is a methodological technique that combines and analyzes the results of multiple studies to draw a summary conclusion.
- It is typically conducted when there are 20 or more separate studies on a given hypothesis or topic.
- Meta-analysis serves several purposes, including summarizing the relationship between variables examined in each study and identifying moderating variables.
- Effect size, which estimates the magnitude of the relationship between variables or the effect of an independent variable on a dependent variable.
- Meta-analytic techniques compare and combine data from all examined studies, considering effect sizes and the number of participants in each study.
- The results of meta-analysis provide a summary statistic indicating the overall relationship between variables across studies and whether results are significantly different from each other.
13
Q
Measurement of Variables
Operationalization
A
- Operationalization is the process of defining and quantifying abstract variables so they can be measured or manipulated in research.
- It involves bringing variables down from an abstract level to a more concrete level with clear definitions.
- During operationalization, researchers typically select a technique for measuring the variable, such as observational or self-report techniques.
14
Q
Measurements of Variables
Observational Techniques
A
- Direct, systematic observation involves researchers recording specific behaviors defined as operationalized variables.
- For example, productivity can be measured by counting manufactured items, while supervisory style can be assessed by observing behaviors like giving orders or demonstrating work techniques.
- Observations can be obtrusive, where participants are aware of being observed, or unobtrusive, where they are unaware.
- Obtrusive observation may lead to altered behavior like the Hawthorne effect.
- Unobtrusive observation provides more confidence in the typicality of behavior but raises ethical concerns about privacy.
15
Q
Measurements of Variables
Self-Report Techniques
A
- Self-report techniques are commonly used to measure variables in research, particularly in I/O psychology.
- Surveys are a popular self-report method, allowing participants to provide information about various aspects of their work situation, attitudes, and perceptions.
- One challenge with surveys is the potential for response distortion or bias, especially if respondents fear retribution for their answers.
- Self-report techniques are also utilized to assess workers’ personalities, interests, management styles, and performance evaluations.
- Compared to direct observational methods, self-reports offer the advantage of collecting large amounts of data at a relatively low cost.
