Sampling Techniques in Education

If you're researching human subjects, You're familiar with the sampling dilemma. Your sampling technique changes the future direction of your work. It enhances your methodology and improves your chances of acceptance. There are 5 main types of sampling techniques you can choose from ⤵ →  𝘗𝘳𝘰𝘣𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘚𝘢𝘮𝘱𝘭𝘪𝘯𝘨 Every member of the population has a known, non-zero chance of being selected. This method ensures that the sample is representative of the population, reducing the risk of bias. →  𝘙𝘢𝘯𝘥𝘰𝘮 𝘚𝘢𝘮𝘱𝘭𝘪𝘯𝘨 Random sampling is a type of probability sampling in which each member of the population has an equal chance of being selected. This method is the gold standard for ensuring a representative sample and minimizing sampling bias. →  𝘚𝘵𝘳𝘢𝘵𝘪𝘧𝘪𝘦𝘥 𝘚𝘢𝘮𝘱𝘭𝘪𝘯𝘨 This technique involves dividing the population into distinct subgroups or strata based on specific characteristics, such as age, gender, or income level. A sample is then drawn from each stratum to make sure that the sample reflects the diversity of the population. →  𝘚𝘺𝘴𝘵𝘦𝘮𝘢𝘵𝘪𝘤 𝘚𝘢𝘮𝘱𝘭𝘪𝘯𝘨 Researchers select every 𝘯th member of the population after a random starting point. This method is straightforward and easy to implement, which makes it a popular choice in large-scale surveys. But it assumes that the population is ordered in a way that does not introduce bias. →  𝘕𝘰𝘯-𝘱𝘳𝘰𝘣𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘚𝘢𝘮𝘱𝘭𝘪𝘯𝘨 Unlike probability sampling, not every member of the population has a known chance of being selected. This method incorporates techniques like convenience sampling, where participants are selected based on availability, and purposive sampling, where participants are chosen based on specific criteria. While quicker and easier to implement, non-probability sampling can introduce bias and limit generalizability. P.S. Have you ever received a journal rejection because of your sampling technique? ________________ 🔔 This is Dr. Samira Hosseini. Scholars who took my training published +2,000 articles in top-tier journals. Join my inner circle not to miss even one single bit of learning: https://lnkd.in/eVNSihCM

📌Step-by-step guide on how to choose participants in quantitative research: 1. Identify the Target Population 📌This refers to the entire group of individuals or elements you want to study. 📌Define characteristics: Age, gender, education, profession, location. 2. Choose a Sampling Method 📌Quantitative research often uses probability sampling to ensure results can be generalized to the whole population. A. Probability Sampling Methods (Preferred for Quantitative Research): 📌Sampling Method Description and When to Use 📍Simple Random Sampling - Every individual has an equal chance of being selected. Used when you have a complete list of population. 📍Systematic Sampling -Select every nth individual from a list. It is used when population is ordered or listed. 📍Stratified Sampling-Divide the population into subgroups (strata) and randomly sample from each. It is used when population has key subgroups (e.g., by age, gender, income). 📍Cluster Sampling-Randomly select whole groups or clusters, then survey all within them or sample within clusters. Used when population is spread out geographically. B. Non-Probability Sampling Methods (Less Ideal for Quantitative Research but Sometimes Used): 📍Sampling Method Description When to Use 📌Convenience Sampling Select whoever is easiest to reach. When time/resources are limited. 📌Quota Sampling Ensure specific numbers of participants from key groups. When you need proportions of subgroups, but can’t randomly sample. 📌Purposive Sampling Select participants based on specific purpose/criteria. Used rarely in quantitative studies, more common in qualitative research. 3. Determine the Sample Size 📍A larger sample size increases accuracy but also requires more time/resources. 📍Use a sample size calculator (online tools available). 📌Consider: 📍Population size 📍Margin of error (usually 5%) 📍Confidence level (usually 95%) 📍Expected response rate 📌Example: 📍Population: 1,000 students 📍Confidence level: 95% 📍Margin of error: 5% 📌→ Required sample: ~278 participants. 4. Set Inclusion and Exclusion Criteria 📍These criteria specify who can or cannot participate. 📌Inclusion Criteria: Characteristics that participants must have (e.g., enrolled college students, aged 18-25). 📌Exclusion Criteria: Characteristics that disqualify participants (e.g., students on leave, under 18). 5. Recruit Participants 📌Methods: 📍Email invitations 📍Posters 📍Social media 📍School bulletins 📍Research panels 6. Obtain Informed Consent 📍Before collecting data, explain: 📍Purpose of the study 📍Voluntary participation 📍Confidentiality 📍Right to withdraw anytime

Sampling in Qualitative Inquiry OnlineClassHelp.Net Sampling in qualitative inquiry differs significantly from quantitative research, where sample sizes must be statistically representative. In qualitative studies, the goal is not generalizability but in-depth exploration of participants' experiences, perspectives, and meanings. This makes purposive sampling the most commonly used strategy. Key Features of Sampling in Qualitative Research ✔ Purposeful Selection – Researchers select information-rich cases relevant to their research questions. ✔ Flexibility – Sampling evolves throughout the research process as new insights emerge. ✔ Saturation-Driven – Data collection continues until no new themes emerge, rather than based on a predetermined number. 📌 Example: A study on workplace stress may involve HR managers, employees, and mental health professionals to capture multiple perspectives rather than using random sampling. Types of Qualitative Sampling Strategies 1️⃣ Purposive Sampling – Selecting participants based on expertise or relevance to the study. 2️⃣ Snowball Sampling – Relying on referrals from participants to find additional subjects. 3️⃣ Convenience Sampling – Using easily accessible participants (less rigorous). 4️⃣ Theoretical Sampling – Common in Grounded Theory, where sampling evolves based on emerging data. 5️⃣ Maximum Variation Sampling – Capturing diverse perspectives for richer insights. 📌 Example: In an ethnographic study of hospital culture, researchers might purposively sample doctors, nurses, and patients to obtain varied viewpoints. Determining Sample Size in Qualitative Research Unlike quantitative studies, there is no fixed rule for qualitative sample sizes. However, some guidelines exist: ✔ Phenomenology: 6–25 participants. ✔ Grounded Theory: 30–50 participants. ✔ Ethnography: 30–50 participants. ✔ Case Study: 1–10 participants. ✔ Narrative Research: 1–2 participants. 📌 Data saturation determines when no new insights emerge, signaling the sample is sufficient. Challenges in Qualitative Sampling ❌ Over-reliance on Small Samples – Risk of insufficient depth if too few participants are included. ❌ Bias in Selection – Subjectivity in choosing participants may influence findings. ❌ Ethical Concerns – Maintaining participant confidentiality is crucial. Conclusion 🎯 Sampling in qualitative research prioritizes depth over breadth, ensuring rich, meaningful data rather than statistical generalization. Qualitative researchers can ensure trustworthy and credible findings by using strategic sampling methods and continuing data collection until saturation is reached. #QualitativeResearch #SamplingStrategy #DataSaturation #PurposiveSampling #GroundedTheory #Ethnography #CaseStudy #NarrativeResearch #SocialSciences #ResearchMethods #Interviews #DataCollection #AcademicWriting #ResearchEthics #ThematicAnalysis 🚀

𝗬𝗼𝘂𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗳𝗶𝗻𝗱𝗶𝗻𝗴𝘀 𝗴𝗼𝘁 𝗿𝗲𝗷𝗲𝗰𝘁𝗲𝗱. 𝗡𝗼𝘁 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝘄𝗮𝘀 𝘄𝗿𝗼𝗻𝗴. Because your 𝘀𝗮𝗺𝗽𝗹𝗲 𝘀𝗶𝘇𝗲 𝘄𝗮𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁𝗶𝗳𝗶𝗲𝗱. I've reviewed hundreds of theses and proposals. And the most common mistake I see: ❌ Writing "𝗻 = 𝟭𝟬𝟬 𝘄𝗮𝘀 𝗱𝗲𝗲𝗺𝗲𝗱 𝗮𝗱𝗲𝗾𝘂𝗮𝘁𝗲" — with zero justification ❌ Using 𝗥𝘂𝗹𝗲 𝗼𝗳 𝗧𝗵𝘂𝗺𝗯 for a study that needed 𝗣𝗼𝘄𝗲𝗿 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 ❌ Applying 𝗦𝗹𝗼𝘃𝗶𝗻'𝘀 𝗙𝗼𝗿𝗺𝘂𝗹𝗮 when the population size was 𝘂𝗻𝗸𝗻𝗼𝘄𝗻 ❌ Ignoring 𝗙𝗶𝗻𝗶𝘁𝗲 𝗣𝗼𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝗼𝗻 when sample was large relative to population Here are the 𝟵 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 𝗳𝗼𝗿 𝗖𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗦𝗮𝗺𝗽𝗹𝗲 𝗦𝗶𝘇𝗲 👇 𝟬𝟭 — 𝗖𝗼𝗰𝗵𝗿𝗮𝗻'𝘀 𝗙𝗼𝗿𝗺𝘂𝗹𝗮 Best for large populations requiring proportion estimates. Used in surveys, market research, and social science studies. 𝟬𝟮 — 𝗦𝗹𝗼𝘃𝗶𝗻'𝘀 𝗙𝗼𝗿𝗺𝘂𝗹𝗮 Simple and quick — when population is known but variability data is unavailable. Used in student research and small projects. 𝟬𝟯 — 𝗣𝗼𝘄𝗲𝗿 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Uses effect size, significance level, and desired power. Used in clinical trials, psychology, and experimental studies. 𝟬𝟰 — 𝗞𝗿𝗲𝗷𝗰𝗶𝗲-𝗠𝗼𝗿𝗴𝗮𝗻 𝗧𝗮𝗯𝗹𝗲 A ready-made table — look up population size, read sample size. Used in educational and organisational research. 𝟬𝟱 — 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗮𝗹 𝗠𝗲𝘁𝗵𝗼𝗱 Ensures estimates fall within a defined precision range. Used in public polling and demographic surveys. 𝟬𝟲 — 𝗥𝘂𝗹𝗲 𝗼𝗳 𝗧𝗵𝘂𝗺𝗯 Informal minimum guidelines — minimum 30 observations. Only valid for exploratory or pilot research. 𝗡𝗼𝘁 𝗿𝗶𝗴𝗼𝗿𝗼𝘂𝘀 𝗲𝗻𝗼𝘂𝗴𝗵 𝗮𝗹𝗼𝗻𝗲. 𝟬𝟳 — 𝗣𝗶𝗹𝗼𝘁 𝗦𝘁𝘂𝗱𝘆 𝗠𝗲𝘁𝗵𝗼𝗱 Run a small study first — estimate variance, then calculate final sample. Used in clinical trials and experimental research. 𝟬𝟴 — 𝗙𝗶𝗻𝗶𝘁𝗲 𝗣𝗼𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝗼𝗻 Reduces sample size when population is small relative to sample. Used in school, organisational, and community research. 𝟬𝟵 — 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲-𝗕𝗮𝘀𝗲𝗱 𝗠𝗲𝘁𝗵𝗼𝗱 Determines size based on time, budget, and access limits. Used in field studies and qualitative investigations. --- 𝗧𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗺𝗲𝘁𝗵𝗼𝗱 𝗱𝗲𝗽𝗲𝗻𝗱𝘀 𝗼𝗻 𝘆𝗼𝘂𝗿: → Population size (known or unknown?) → Research design (experimental, survey, qualitative?) → Available resources (time, budget, access?) 📩 asma@researchcrave.com 🌐 www.researchcrave.com whatsapp: https://wa.link/bbvf22 #SampleSize #ResearchMethods #PhDLife #AcademicWriting #ResearchCrave #ThesisWriting #DoctoralResearch #ResearchMethodology #PhDTips #AcademicSuccess #GradSchool #MastersStudents #PhDStudent #ResearchSkills #AcademicResearch #HigherEducation #PhDJourney #ThesisTips #DissertationHelp #PhDCommunity #ResearchProposal

QUALITATIVE RESEARCH CONCEPTS every scholar needs to know by Dr. Blessing Osaro-Martins 1. PHILOSOPHICAL FOUNDATIONS (Your Research Backbone) These define your worldview and must align with your methodology. - Ontology: Nature of reality (single vs multiple realities) - Epistemology: Nature of knowledge (objective vs co-constructed) - Axiology: Role of values in research - Methodology: Overall research strategy while methods is the specific techniques used Paradigms to know includes: Positivism, Post-positivism, Interpretivism, Constructivism, Critical theory, Pragmatism and Transformative paradigm (some are for Quantitative and Mixed-methods) 2. QUALITATIVE RESEARCH DESIGNS (Methodological Approaches) Each design answers a different type of research question: - Phenomenology: Lived experiences - Grounded Theory: Theory development - Ethnography: Culture and social practices - Narrative Inquiry: Life stories - Case Study: Bounded systems - Action Research: Change-oriented inquiry - Participatory Research: Co-creation with participants 3. SAMPLING TECHNIQUES (Who and Why) - Purposive Sampling: Selecting participants with relevant experience - Theoretical Sampling: Sampling guided by emerging theory - Snowball Sampling: Participant referrals - Maximum Variation Sampling: Capturing diverse perspectives - Homogeneous Sampling: Similar participants for depth - Sample Size Justification: Based on saturation, not numbers 4. DATA COLLECTION TECHNIQUES - In-depth Interviews - Semi-structured Interviews - Unstructured Interviews - Focus Groups - Participant Observation - Non-participant Observation - Field Notes - Reflexive Journals - Document Analysis - Audio/Visual Data Collection 5. CORE ANALYTICAL CONCEPTS - Coding: Assigning meaning to data - Open Coding: Initial categorization - Axial Coding: Linking categories - Selective Coding: Core category integration - Thematic Analysis: Identifying patterns/themes - Content Analysis: Systematic categorization - Narrative Analysis: Story structure analysis - Discourse Analysis: Language and power - Constant Comparative Method: Ongoing comparison of data 6. TYPES OF CODING (Very Important for PhD Work) - Descriptive Coding - In Vivo/Verbatim Coding - Process Coding - Pattern Coding - Emotion Coding - Values Coding 7. TRUSTWORTHINESS (Qualitative Rigor) Instead of validity and reliability, qualitative research uses: - Credibility: Truthfulness of findings - Transferability: Applicability to other contexts - Dependability: Consistency of findings - Confirmability: Neutrality and auditability ... cont'd 👇 Qualitative research is not just about collecting stories; it is about systematically interpreting meaning within a philosophical, methodological, and analytical framework. Find insightful? LIKE, COMMENT AND FOLLOW #research #PhD #academicwriting #qualitative