Qualitative Research Designs Day 4 The Curious Skeptics at work

Agenda Quickly revisit literature reviews Revisit variables Analyzing a Qualitative Research Article Characteristics of qualitative research –Sampling –Interviews/observations –Data analysis –Trustworthiness Practice in Analyzing!

Revisiting variables… Independent & Dependent –Independent variables act as the “precursor” in that they precede, influence, and predict the dependent variable –Dependent variables act as the “outcome” in that they change as a result of being influenced by an independent variable

Independent & Dependent Examples –The effect of two instructional approaches (independent variable) on student achievement (dependent variable) –The use of SAT scores (independent variable) to predict freshman grade point averages (dependent variable)

Extraneous & Confounding Extraneous variables are those that affect the dependent variable but are not controlled adequately by the researcher –Not controlling for the key-boarding skills of students in a study of computer-assisted instruction Confounding variables are those that vary systematically with the independent variable and exert influence of the dependent variable –Not using counselors with similar levels of experience in a study comparing the effectiveness of two counseling approaches

Continuous & Categorical Continuous variables are measured on a scale that theoretically can take on an infinite number of values Test scores range from a low of 0 to a high of 100 Attitude scales that range from very negative at 0 to very positive at 5 Students’ ages

Continuous & Categorical Categorical variables are measured and assigned to groups on the basis of specific characteristics –Gender: male and female –Socio-economic status: low, middle, and high

Continuous & Categorical Thought Question… –Can continuous variables be converted to categorical variables, or categorical variables be converted to continuous variables? IQ is a continuous variable, but the researcher can choose to group students into three levels based on IQ scores - low is below a score of 84, middle is between 85 and 115, and high is above 116

Schlosser Article Group 1 – up to “Method” Group 2 – up to “Procedures for Analyzing Data” Group 3 – up to “Results” Group 4 – up to “Discussion” 1) Indicate what is happening in paragraphs/ sections 2) Identify terms 3) Evaluate based on criteria at end of McMillan Ch. 11

Qualitative Research Problems When to use a Qualitative design –To understand a phenomenon about which little is known (exploratory) –To gain a novel slant about a phenomenon we do know about (novelty) –To obtain greater detail about phenomenon that are difficult to understand through solely quantitative methods (process)

Qualitative Research Problems Characteristics –Includes a single, central phenomena –Open-ended –General in nature –Emergent –Neutral with respect to what will be learned No hypotheses, but still may have “hunches” Open to new information No expected outcomes

Sample Research Question “How do students at an alternative school for students at-risk of dropping out of school perceive their learning environment?” “What changes do teachers and counselors make when their school is placed on probation under the No Child Left Behind Law? What remains the same?”

Qualitative Research Problems Criteria for evaluating qualitative research problems –Should not be too general or too specific –Should be amenable to change as data is collected and analyzed –Should not be biased with restrictive assumptions or desired findings –Should be written in “how” and “what” forms to focus on describing the phenomena –The problem can include the participants and the site Key Idea: Emergent

Interviews: Selecting Participants Use of purposeful sampling strategies to select “information rich” participants Not intended to be representative of larger population! (i.e., not random sampling). Contrast with most quantitative studies. Be clear about why selecting participants or state “convenience sampling”

Selecting Participants Purposeful sampling strategies –Maximum variation - selecting individuals or cases to represent extremes Very positive or very negative attitudes Highest and lowest achieving students –Snowball (i.e. network) - initially selected participants recommend others for involvement

Selecting Participants Purposeful sampling strategies –Sampling by case - selecting individuals or cases for their unique characteristics Extreme Typical Reputation –Key informant - selecting an individual(s) particularly knowledgeable about the setting and/or topic –Comprehensive - selecting all relevant individuals or cases

Interview Protocols Rapport Unstructured in nature, yet have focus General (“grand tour”) questions to specific questions based on participant responses Tape recording and transcribing interviews afford the opportunity to study the data carefully

Observations Unstructured in nature, yet have focus Participant-observer role of the researcher –Continuum between observer and participant Complete ObserverParticipantComplete ObserverParticipantObserverParticipant –This should be clear in the study!

Trustworthiness QualitativeQuantMeaning CredibilityInternal Validity Degree of truth for individuals Transferability External Validity Degree of application to other contexts DependabilityReliabilityReplicable Confirmability ObjectivityFindings are product of inquiry

Data Analysis Systematically examine, summarize, and synthesize the data Data collection and data analysis tightly coupled (constant comparative method) This should be explained thoroughly in the report!

Data Analysis Coding –Organizing the data into reasonable, meaningful units that are coded with words or very short phrases that signify a category –Use of major codes and sub-codes is common –Types Open Selective Negative case analysis/ deviant cases

Data Analysis “Because the creation of codes is up to each researcher and is critical to the study, it is important to know something about how the codes were created” (McMillan, 2004, p. 268). BE SPECIFIC AND EXPLICIT!

Data Analysis Summarizing the coded data Pattern seeking and synthesizing –Identify relationships –Draws inferences –Enlarge, combine, subsume, and create new categories that make sense –Seek data that does not fit

Let’s do some Data Analysis!

Field Notes Researcher records observations –Descriptive –Reflective Theoretical (TN) – identify underlying issues Methodological (MN) – possible adjustments to research methods Personal (PN) – personal interpretations of observations –Accuracy vital