Descriptive research survey design is an approach within descriptive research that strategically combines quantitative and qualitative data collection methods to gain relevant and accurate information about a specific population, situation, or phenomenon. It primarily aims to describe "what is" rather than determining cause-and-effect relationships.
Key Characteristics of Descriptive Survey Design:
- Descriptive Focus: The core objective is to accurately portray the characteristics of a group or situation. This involves describing the who, what, when, where, and how of a topic.
- Data Integration: It integrates both quantitative data (numerical data, often collected through structured questionnaires and scales) and qualitative data (descriptive data, often gathered through open-ended questions, interviews, or focus groups). This blended approach provides a more comprehensive understanding.
- Survey as the Primary Tool: Surveys, including questionnaires, are the primary means of data collection. These surveys are carefully designed to gather specific information from a representative sample of the population.
- Real-World Context: Descriptive surveys are typically conducted in real-world settings, allowing researchers to observe and understand phenomena as they naturally occur.
- Non-Experimental: Descriptive survey research is non-experimental, meaning researchers do not manipulate variables or attempt to establish causal relationships. It's about observation and reporting.
Components of Descriptive Survey Design:
- Research Question Formulation: Start with clear and specific research questions that guide the survey design and data collection process. For example: "What are the attitudes of college students towards online learning?"
- Population and Sampling: Define the target population and select a representative sample. Proper sampling techniques ensure that the findings can be generalized to the larger population.
- Survey Instrument Design: Develop a well-structured survey instrument (questionnaire) that includes both closed-ended questions (e.g., multiple-choice, rating scales) for quantitative data and open-ended questions for qualitative insights. Pilot testing the survey is crucial to ensure clarity and validity.
- Data Collection: Administer the survey to the selected sample, ensuring confidentiality and ethical considerations are addressed. Data can be collected through various methods like online surveys, mail surveys, telephone surveys, or in-person interviews.
- Data Analysis: Analyze the collected data using appropriate statistical techniques for quantitative data (e.g., descriptive statistics, correlations) and qualitative analysis methods (e.g., thematic analysis, content analysis) for qualitative data.
- Interpretation and Reporting: Interpret the findings and present them in a clear and concise manner, often using tables, graphs, and narratives. Integrate the quantitative and qualitative findings to provide a holistic understanding of the topic.
Example of Descriptive Survey Research:
A researcher wants to understand the job satisfaction levels of nurses in a particular hospital. They could use a descriptive survey design:
- Quantitative Data: A standardized job satisfaction questionnaire is distributed to a sample of nurses, collecting numerical data on different aspects of job satisfaction (e.g., workload, management support, work-life balance).
- Qualitative Data: Follow-up interviews are conducted with a subset of the nurses to gather more in-depth information about their experiences, challenges, and suggestions for improvement.
By analyzing both the quantitative and qualitative data, the researcher can provide a comprehensive description of the job satisfaction levels of nurses in the hospital, identifying specific areas of concern and potential solutions.
Descriptive research survey design provides a valuable framework for exploring and understanding complex phenomena in a systematic and rigorous manner, ultimately informing decision-making and improving practices.
