Diving into Exploratory Sequential Research Design
Instructions for Combining Quantitative and Qualitative Research Strategies
In this section of the Mixed Methods Research Guide, we'll delve into the characteristics, purpose, and advantages of the exploratory sequential research design. We'll also look at some studies that used this method and its variations.
What's It All About?
Exploratory sequential design is a two-phase research approach that starts with qualitative research followed by quantitative instrument development and testing. Researchers employ this design when they're interested in creating an instrument from qualitative data, which is then validated using the quantitative phase. Confused about what this thingamajig is called? It's also known as the "instrument development design" or the "quantitative follow-up design".
Creswell and Plano Clark (2017) explain that this design aims to generalize qualitative findings to larger, quantitative sampling methods. It's designed to tackle research problems where the measures or instruments haven't been established, the variables are unknown, and a theoretical framework hasn't been set yet. Essentially, this design seeks to explore unknowns with a qualitative foundation and then quantify them.
The Philosophical Side
Exploratory sequential mixed methods research integrates qualitative and quantitative approaches, shedding light on complex research problems. It all starts with qualitative research, which takes precedence when the research question requires a deep understanding of experiences, contexts, and perspectives. The initial phase operates under constructivist principles, focusing on exploring subjective meanings and social contexts.
Designing an Exploratory Sequential Study
Creswell and Plano Clark (2017) suggest the following step-by-step approach for conducting an exploratory sequential mixed methods research design:
Qualitative Strand
- Clearly define the qualitative research question(s) and select an appropriate qualitative approach.
- Obtain necessary permissions.
- Identify and recruit participants for the qualitative sample.
- Collect open-ended data using established protocols.
- Analyze qualitative data using theme development techniques or methods specific to the chosen qualitative approach.
Quantitative Strand
- Design and pilot test a quantitative data collection tool.
- Refine quantitative research questions or hypotheses based on the qualitative phase insights.
- Determine criteria for selecting participants for the quantitative sample.
- Collect closed-ended data using the newly designed tool.
- Analyze quantitative data with descriptive statistics, inferential statistics, and effect size calculations.
Interpreting Connected Results
- Summarize and interpret both the qualitative and quantitative results.
- Discuss how quantitative results support, generalize, or test qualitative findings.
Now, Here's the Juicy Part: Advantages and Challenges
Advantages
- Phase Separation: The separation of phases simplifies the process of explaining, conducting, and presenting the research.
- Adds a Quantitative Phase: A quantitative phase can make research findings more appealing to audiences that favor quantitative approaches.
- Informative Insights: If insights from the initial qualitative phase reveal the need for a quantitative phase, it can be very helpful.
- New Instruments: This design allows researchers to create a new instrument as part of the study process.
Challenges
- Time-Intensive: The two-phase structure can be time-consuming, especially if developing a new instrument is part of the study.
- IRB Application Complexities: Specifying the procedures for the quantitative phase during the initial Institutional Review Board (IRB) application can be difficult, as these details often depend on findings from the qualitative phase.
- Sampling Considerations: Careful attention must be paid to the selection of participants for each strand. The qualitative phase should involve a small, purposeful sample, while the quantitative phase should include a larger, more diverse group for enhanced generalizability and reduced potential bias.
- Instrument Development Challenges: When developing an instrument between phases, researchers must determine which qualitative data to prioritize and effectively translate those insights into quantitative measures.
- Ensuring Validity and Reliability: Establishing the validity and reliability of scores generated from the new instrument requires rigorous procedures.
Design Variants and Example Studies
Unlike explanatory sequential designs, an exploratory design consists of three distinct phases: a qualitative phase, a quantitative development phase, and a final quantitative testing phase. The key difference among the variants lies in what is developed during the middle phase of the design.
New Variable Development Variant
In this variant, researchers identify new variables or create a conceptual or theoretical framework during the qualitative phase. These variables are then analyzed in the quantitative phase to determine their prevalence or to test the emerging theory with a larger sample.
Survey Development Variant
The qualitative phase helps define the content and structure of survey instruments in this variant. Researchers gather qualitative data to identify key themes, which guide the development of survey questions. After finalizing the instrument, they administer it to a representative sample for quantitative analysis.
Intervention Development Variant
Researchers use qualitative data to design interventions or experiments that are meaningful and relevant to participants. The qualitative phase focuses on identifying activities and measures that can influence outcomes.
Digital Tool Development Variant
In this variant, qualitative data is used to guide the design and testing of digital tools. Researchers gather qualitative data to understand the questions and measures needed for the tool, shape the development process, and assess the tool in practical settings.
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[1] Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.[2] Kron, F.W., Gjerde, C.L., Sen, A. et al. Medical student attitudes toward video games and related new media technologies in medical education. BMC Med Educ 10, 50 (2010).[3] Clark, C. J., Shahrouri, M., Halasa, L., Khalaf, I., Spencer, R., & Everson-Rose, S. (2012). A Mixed Methods Study of Participant Reaction to Domestic Violence Research in Jordan. Journal of Interpersonal Violence, 27(9), 1655-1676.[4] Betancourt, T. S., McBain, R., Newnham, E. A., & Brennan, R. T. (2014). A behavioral intervention for war-affected youth in Sierra Leone: A randomized controlled trial. Journal of the American Academy of Child & Adolescent Psychiatry, 53(12), 1288-1297.[5] Goldenberg, C., Gallimore, R., & Reese, L. (2005). Using mixed methods to explore Latino children's literacy development. In T. S. Weisner (Ed.), Discovering successful pathways in children's development: Mixed methods in the study of childhood and family life (pp. 21-46). The University of Chicago Press.[6] Mak, L., & Marshall, S. K. (2004). Perceived Mattering in Young Adults' Romantic Relationships. Journal of Social and Personal Relationships, 21(4), 469-486.
- The exploratory sequential research design, commonly known as instrument development design or quantitative follow-up design, is a two-phase approach that supports the creation of new learning instruments through a sequence of qualitative and quantitative methods.
- Online education platforms can benefit from mixed methods research, particularly the exploratory sequential design, as this approach allows for the development of relevant and meaningful digital tools for enhancing education-and-self-development, with findings appealing to both qualitative and quantitative-favoring audiences.
- Case studies utilizing the exploratory sequential design can provide valuable learning opportunities, as they shed light on complex education-and-self-development issues with a qualitative foundation, while also offering a quantitative understanding for more informed decision-making and generalization of findings.
