Explanatory sequential design

Definition

Explanatory sequential design is a mixed methods research approach where qualitative data is collected and analyzed after the initial quantitative data has been gathered. This method helps researchers better understand quantitative results by using qualitative insights to explain or expand on the numerical findings. The combination of both data types allows for a more comprehensive understanding of research questions, enhancing the depth and context of the findings.

5 Must Know Facts For Your Next Test

1. Explanatory sequential design typically starts with a quantitative phase, where researchers gather numerical data through surveys or experiments.
2. After analyzing the quantitative results, researchers conduct a qualitative phase to gather in-depth insights through interviews or focus groups.
3. This design is particularly useful when initial quantitative results are unexpected or when researchers need to explore underlying reasons behind those results.
4. The integration of qualitative findings can lead to richer interpretations and more actionable recommendations based on the quantitative data.
5. Researchers using this approach must carefully plan the timing and methods for both the quantitative and qualitative phases to ensure coherence and relevance.

Review Questions

• How does explanatory sequential design enhance the understanding of research findings?
  • Explanatory sequential design enhances understanding by combining quantitative and qualitative methods. After collecting and analyzing quantitative data, researchers gather qualitative insights to explain or add depth to their numerical findings. This two-phase approach allows researchers to clarify unexpected results or explore the reasons behind certain trends, resulting in a more comprehensive understanding of the research question.
• What are some challenges researchers might face when implementing explanatory sequential design in their studies?
  • Researchers may face challenges such as ensuring effective integration of quantitative and qualitative data, maintaining participant engagement during both phases, and addressing potential biases that can arise from different data collection methods. Additionally, careful planning is required to align research questions and ensure that both phases contribute meaningfully to the overall analysis. Managing time effectively between phases can also be a challenge, as it may require adjustments based on initial findings.
• Evaluate the impact of explanatory sequential design on developing theories in social science research.
  • Explanatory sequential design can significantly impact theory development in social science by providing nuanced insights that pure quantitative or qualitative approaches might miss. By integrating both types of data, researchers can identify patterns and causal relationships while simultaneously exploring participants' perspectives. This comprehensive view not only enriches existing theories but can also lead to the emergence of new theoretical frameworks that better explain complex social phenomena.

Related terms

Mixed Methods: A research approach that combines both quantitative and qualitative data collection and analysis to provide a more complete picture of a research question.

Qualitative Research:

Research that focuses on understanding human behavior, thoughts, and experiences through non-numerical data like interviews, observations, and open-ended surveys.

Quantitative Research: Research that involves the collection and analysis of numerical data, often using statistical techniques to identify patterns, relationships, or trends.