Jenis Sampel/Informan dalam Penelitian Kualitatif #Kualitatif #InformanPenelitian #NonProbability

Summary

In this video, the presenter discusses key aspects of sampling in qualitative research, focusing on the differences between samples and informants. They explain that qualitative research prioritizes informants over samples because the goal is to gather in-depth, detailed information rather than representative data. The video also explores the two main types of non-probability sampling techniques in qualitative research: purposive and snowball sampling. The presenter emphasizes that the selection of informants is based on their ability to provide rich, relevant information, rather than the need for statistical representativeness. Throughout the discussion, practical examples are used to clarify these concepts for students and beginner researchers.

Takeaways

• 😀 In qualitative research, the term 'informant' is used instead of 'sample', as it emphasizes gathering information rather than selecting a representative sample.
• 😀 The main goal in qualitative research is to gather rich, detailed information from a small number of informants rather than focusing on statistical representation of the population.
• 😀 Probability sampling, which is common in quantitative research, is not suitable for qualitative research, as it does not ensure a depth of information that qualitative studies require.
• 😀 Non-probability sampling, especially techniques like purposive sampling and snowball sampling, is the preferred approach in qualitative research.
• 😀 Purposive sampling involves selecting informants who are particularly knowledgeable or have experience related to the research topic, ensuring relevant and accurate data.
• 😀 In snowball sampling, an initial informant helps the researcher identify additional informants, leading to a growing pool of data as the research progresses.
• 😀 The selection of informants in qualitative research is subjective and based on their ability to provide valuable insights related to the research question.
• 😀 In qualitative studies, the researcher must carefully consider the competence and expertise of informants to ensure they can provide useful information.
• 😀 Qualitative research often involves the development and refinement of research questions as new information emerges during the data collection process.
• 😀 The key challenge in qualitative research is ensuring the depth of information rather than the breadth or representation of the sample, which is why probability sampling is avoided.

Q & A

What is the main difference between sampling in quantitative and qualitative research?

In quantitative research, sampling aims for representation of the population through techniques like probability sampling. In qualitative research, however, the focus is on obtaining rich, detailed information from specific informants, and sampling is typically done through non-probability methods like purposive or snowball sampling.

Why is it not correct to use the term 'sample' in qualitative research?

Qualitative research does not focus on representing a population; instead, it seeks in-depth insights from informants who can provide relevant, detailed information on the research topic. Thus, 'informant' is a more accurate term than 'sample.'

What is the purpose of non-probability sampling in qualitative research?

Non-probability sampling in qualitative research is used because it doesn't aim for representativeness but rather focuses on gathering detailed, relevant information from specific informants who are knowledgeable about the topic being studied.

Can you explain what purposive sampling is in qualitative research?

Purposive sampling is a technique where the researcher selects informants based on specific criteria, ensuring that the informants are knowledgeable and can provide relevant insights for the research topic. It's a goal-oriented selection of participants based on their expertise or experience.

How does snowball sampling work in qualitative research?

Snowball sampling begins with an initial informant who provides recommendations or referrals to other informants. This process continues, with new informants referring others, expanding the sample progressively, much like a snowball rolling and growing larger.

Why might qualitative research evolve during the study process?

Qualitative research often evolves as new information is uncovered. As researchers collect data and interact with informants, the research questions or focus areas may shift, requiring further exploration and the involvement of additional informants.

What are the three key considerations for using non-probability sampling in qualitative research?

The three key considerations for using non-probability sampling are: 1) the informant's ability to provide relevant information, 2) the appropriateness of the informant in relation to the research topic (not about representativeness), and 3) the need for information to evolve during the study, requiring flexibility in informant selection.

What is the primary criterion for selecting an informant in purposive sampling?

The primary criterion for selecting an informant in purposive sampling is their expertise or knowledge about the research topic. Researchers select informants who can provide valuable and detailed insights, ensuring that the sample fits the research objectives.

What does 'probability sampling' refer to in the context of quantitative research?

Probability sampling in quantitative research refers to the technique of selecting samples in such a way that every member of the population has a known and often equal chance of being included. This approach aims for a representative sample that reflects the broader population.

How does qualitative research differ from quantitative research in terms of data collection and analysis?

Qualitative research focuses on understanding human experiences and perceptions through in-depth data like interviews and observations. It prioritizes context, complexity, and meanings, whereas quantitative research emphasizes numerical data, generalization, and statistical analysis for identifying patterns across populations.