Notes on Qualitative and Quantitative Research Methods (Transcript)

Qualitative Research Overview

  • Qualitative vs. quantitative focus (implied in the transcript): exploring depth of understanding, lived experiences, and context rather than just numbers.
  • Examples of qualitative methods:
    • Ethnography: long-term immersion in a setting to study people in their natural environment; aims to uncover in-depth information about cultures, practices, and lived experiences.
    • Participant observation: researcher is in the field with participants, often for extended periods; data collection occurs through observing and interacting.
  • Ethnographies emphasize stories and deep descriptions; may include interviews as a data source.
  • Environmental/real-world focus: like Jane Goodall studying chimpanzees, ethnography studies people in their own environments to understand what’s happening.
  • Lived experiences: aim to capture how people experience events and contexts, not just what happened.
  • Interviews in qualitative work:
    • Build rapport with participants to facilitate open sharing of experiences.
    • Open-ended questions: encourage narrative responses (e.g., "Tell me about your childhood").
    • Respondents are the participants who share their life stories (the "life history").
  • Key terms:
    • Rapport: friendly, comfortable presence that makes participants willing to share information.
    • Respondent: a participant who provides data (their life story or experiences).
    • Population vs. target population: population is the group being studied; target population is the broader group the study aims to generalize to; sampling needs to be systematic to avoid over- or under-representation.
  • Example discussion reference:
    • Parks and Rec focus group (Leslie Knope) with about 10 people: used to illustrate how focus groups can gather attitudes toward a political candidate.
  • Interview design considerations:
    • Open-ended questions enable respondents to take the conversation in meaningful directions.
    • Follow-up questions are used to probe for clarification or depth when respondents ask for explanations.
    • Avoiding leading questions:
    • Leading questions steer toward a desired answer and should be avoided to preserve objectivity.
    • Double-barreled questions:
    • Questions that ask two things at once (e.g., "How many of you have a pen and a water bottle?") can confuse respondents and should be avoided.
    • Life history focus: questions about people’s journeys, upbringing, and relationships to events or contexts.
  • Activity cue (interview questions):
    • If a respondent asks for clarification, the interviewer should provide an explanation and ask follow-ups.
    • In qualitative work, follow-up questions help deepen understanding.

Survey Research and Quantitative Data Collection

  • Distinction from qualitative methods: survey research relies more on structured data collection that can be quantified.
  • Survey question types:
    • Closed-ended questions: typically yield numerical or categorical answers (e.g., yes/no, numbers, frequency).
    • Open-ended questions: allow respondents to express thoughts in their own words; useful for large-scale surveys but require more analysis.
    • Likert scale items: used to gauge attitudes on a continuum (e.g., satisfaction or agreement levels).
    • Example scale categories mentioned: very satisfied, dissatisfied, and a range of agreement levels (strongly agree to strongly disagree).
    • Typical Likert scale options include:
      • Strongly agree, Agree, Somewhat agree, Somewhat disagree, Disagree, Strongly disagree.
    • Double-barreled questions: discouraged in surveys for the same reason as in interviews, because they ask two things at once and can confuse respondents.
    • Pretesting (pilot testing): administer the questionnaire to a small group before full deployment to check clarity and identify ambiguous terms or jargon.
  • Survey construction guidance:
    • Use simple, clear language; avoid heavy jargon that can confuse respondents.
    • Avoid negative wording (e.g., questions with negations like "not").
    • When possible, pretest the survey with a small group to catch issues early.
  • Question types emphasis:
    • Closed-ended items are often the core of survey questionnaires.
    • Open-ended items may be included but can lengthen analysis for large samples.
  • Interview vs. survey integration:
    • Interviews provide depth (qualitative) while surveys provide breadth (quantitative).
    • In large samples, a balance between open-ended and closed-ended questions can be challenging due to analysis time.
  • Sampling and representativeness in surveys:
    • Snowball sampling: a non-probability technique where participants recruit future respondents; useful when access is limited but not representative.
    • Gatekeepers: initial contacts who refer or connect researchers to potential participants.
    • Probability sampling: techniques like simple random sampling, cluster sampling, and systematic sampling where every individual has a known, equal chance of selection; improves representativeness.
    • Non-probability sampling: not all individuals have a known chance of selection; slower to generalize but useful in exploratory work.
  • Target population vs. population:
    • You should aim for a diverse sample to avoid biased results (e.g., a survey of only seniors at UNCW could skew results if not representative of the broader population).
  • Cross-sectional surveys:
    • Focus on a single point in time to measure current attitudes or states.
    • Limitation: causation is hard to infer from a single data point; temporal sequencing is not established.
    • Example mention: growth assessment by surveying students at the beginning and end of a semester to observe change.
  • Data quality and representativeness:
    • Response rate is critical: the proportion of invited respondents who complete the survey.
    • Example given: out of 35 students, 28 completed the survey.
    • Higher response rates generally indicate more representative results; low rates can lead to biased conclusions or anecdotal evidence.
  • Data analysis considerations:
    • Large numbers of open-ended responses can complicate analysis; careful coding strategies are required.
    • Noted preference for more data points and more respondents to infer causation more reliably.

Qualitative vs. Quantitative: Key Connections and Implications

  • Core difference: qualitative methods uncover depth and context; quantitative methods quantify prevalence and relationships.
  • Data collection methods often overlap (e.g., interviews used in both ethnography and survey follow-ups; focus groups can accompany surveys).
  • Ethical and practical implications:
    • Building rapport and trust is essential in qualitative research to obtain honest, rich data.
    • Clarity of questions reduces misinterpretation and ensures that respondents understand what is being asked.
    • Pretesting helps prevent measurement error due to jargon or confusing wording.
    • Selection strategies (probability vs non-probability) influence the extent to which findings can be generalized.
  • Foundational principles referenced:
    • Distinction between accessing settings and establishing trust (qualitative).
    • The importance of avoiding bias by using neutral, open-ended questions when appropriate.
    • The balance of depth (qualitative) and breadth (quantitative) to support robust conclusions.

Formulas and Notation (LaTeX)

  • Response rate:
    extResponserate=N<em>extcompletedN</em>extinvitedext{Response rate} = \frac{N<em>{ ext{completed}}}{N</em>{ ext{invited}}}
  • Likert scale representation (example):
    ext{Likert}_{ ext{type}}
    i ext{categories} = \{ ext{Strongly disagree}, ext{Disagree}, ext{Somewhat disagree}, ext{Somewhat agree}, ext{Agree}, ext{Strongly agree} \
    }
  • Cross-sectional study is associated with a single time point; longitudinal designs involve multiple time points (implied by the discussion of data points and causation).

Helpful Terminology Glossary (from the transcript)

  • Ethnography: qualitative study focusing on people in their natural environment to understand cultures and lived experiences.
  • Participant observation: researcher actively participates and observes within the setting.
  • Rapport: the friendly, comfortable connection that encourages participants to share information.
  • Respondent: the participant in an interview or survey.
  • Population: the broader group being studied.
  • Target population: the specific group the research aims to generalize to.
  • Simple random sampling, cluster sampling, systematic sampling: probability sampling methods.
  • Snowball sampling: non-probability method relying on participants to recruit others.
  • Cross-sectional survey: data collected at a single point in time.
  • Longitudinal data: data collected across multiple time points (referenced in the context of showing change over time).

Real-World Relevance and Takeaways

  • When planning studies, decide whether your aim is to describe experiences in depth (qualitative) or to measure prevalence/relationships across a population (quantitative).
  • Use qualitative methods to understand lived experiences and contexts; use interviews to gather nuanced stories while ensuring you build rapport and avoid leading questions.
  • Use surveys to collect structured, comparable data; design questions carefully to avoid ambiguity, bias, and double-barreled items.
  • Consider sampling strategy early:
    • If representativeness is crucial, lean on probability sampling.
    • If access is limited, Snowball sampling can help, but be mindful of representativeness and generalizability.
  • Always pretest instruments, keep language simple, and avoid negations in questions where possible to improve data quality.
  • To claim causation, collect data across multiple time points and shores up with robust sampling and thoughtful analysis.
  • The classroom activities illustrate practical steps: crafting interview questions, recognizing leading/double-barreled questions, and designing open-ended versus closed-ended survey items.

Practical Examples Referenced in the Transcript

  • Focus group example from Parks and Rec: a focus group of about 10 people to discuss a political candidate; demonstrates data collection through small-group discussion.
  • Jane Goodall analogy for ethnography: observing people in their lived environment to understand their experiences and environments.
  • Interview scenario: asking about childhood to explore life history and how early experiences shape later perspectives.
  • Survey scenario for discount offers: marketers use surveys to encourage return participation with incentives such as 10% off or free shipping; illustrates response motivation and survey use in marketing.