Metode Penelitian Kombinasi | Prof. Dr. Sugiyono, M.Pd #8

Summary

This video script explains the concept of mixed-methods research, combining qualitative and quantitative approaches. It discusses various research designs, such as sequential explanatory and exploratory designs, as well as concurrent and embedded designs. The script also emphasizes how these methods can be applied in real-world research, with examples like employee performance and faculty assessments. By integrating both numerical and descriptive data, mixed-methods research allows for a more comprehensive understanding of complex subjects, providing deeper insights and enhancing the validity of findings.

Takeaways

• 😀 Mixed-methods research combines both qualitative and quantitative approaches for a more comprehensive understanding.
• 😀 Understanding both qualitative and quantitative methods is crucial for successfully implementing a mixed-methods approach.
• 😀 Sequential designs involve conducting the two methods one after the other: explanatory (quantitative first) or exploratory (qualitative first).
• 😀 Concurrent designs use both methods simultaneously, allowing for a holistic analysis of the research topic.
• 😀 The combination of methods can be either balanced (e.g., 50% qualitative, 50% quantitative) or skewed (one method dominating).
• 😀 In mixed-methods research, symbols like ‘+’ indicate simultaneous use of methods, while arrows (→) show a sequential order of methods.
• 😀 There are 9 types of mixed-methods designs, reflecting different combinations of methods, either sequential or concurrent, with varying levels of dominance.
• 😀 Examples of mixed methods in research include combining descriptive and comparative data or univariate and multivariate data analysis.
• 😀 Mixed-methods research is used to study phenomena in both quantitative terms (e.g., numerical performance data) and qualitative terms (e.g., behavior, observations).
• 😀 Discrepancies can occur when quantitative and qualitative data do not align, such as high performance ratings supported by negative qualitative observations, which requires careful interpretation.
• 😀 Researchers must select the appropriate mixed-methods design based on their research question and the type of data they seek to analyze.

Q & A

What is the primary focus of the script?

The primary focus of the script is on research methods, specifically the combination of qualitative and quantitative methods in research design, and how to apply these methods in a mixed-methods approach.

What does 'mixed methods' research involve?

Mixed methods research involves combining both qualitative and quantitative research methods. The approach can be sequential, where one method follows the other, or concurrent, where both methods are used simultaneously.

What is the difference between 'sequential explanatory' and 'sequential exploratory' designs?

In a sequential explanatory design, the quantitative method is used first, followed by the qualitative method. In a sequential exploratory design, the qualitative method is used first, followed by the quantitative method.

How are the two methods represented in a mixed-methods approach?

The two methods in a mixed-methods approach are represented with a plus symbol (+) when combined, indicating the use of both methods together, or with an arrow (→) when the methods are used sequentially, one after the other.

What are the four main design types in mixed-methods research as mentioned in the script?

The four main design types are: (1) Sequential explanatory (quantitative dominant), (2) Sequential exploratory (qualitative dominant), (3) Concurrent design with equal combination of methods, and (4) Concurrent design with unequal combination of methods.

Can you explain the concept of a 'dominant' method in mixed-methods research?

A dominant method in mixed-methods research refers to the method that plays a more central role in the design. For example, in a sequential explanatory design, the quantitative method is dominant, while in a sequential exploratory design, the qualitative method is dominant.

What is the significance of combining descriptive and comparative data in research?

Combining descriptive and comparative data allows researchers to provide a comprehensive analysis, offering both numerical insights and contextual understanding. Descriptive data gives an overview of the situation, while comparative data highlights differences or relationships.

How can quantitative data be supported by qualitative data?

Quantitative data can be supported by qualitative data by providing context and deeper understanding. For example, while quantitative data might show high employee performance (numerically), qualitative data can explain the reasons behind this performance, such as strong work habits or positive work environment.

What are some challenges when combining qualitative and quantitative methods?

Challenges in combining qualitative and quantitative methods include differences in data collection and analysis techniques, balancing the two methods effectively, and ensuring that the findings from both methods are integrated meaningfully in the final research results.

Why is it important to choose the right mixed-methods design?

Choosing the right mixed-methods design is important because it determines how the research will be conducted and how data will be interpreted. The design must align with the research goals, whether it's to explore new concepts, validate findings, or provide a deeper understanding of a phenomenon.