Research design and methods Part II - UWC

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Research design and methods Part II Dr Brian van Wyk POST-GRADUATE ENROLMENT AND THROUGHPUT

From last week… •

Research methodology – Quantitative vs. Qualitative vs. Participatory/action research



Research methods – Methods of sampling, data collection and data analysis



Research design – Experimental, descriptive, exploratory

RESEARCH DESIGN •

Logic of the inquiry



Purpose of the inquiry



Types of research design



Directions of reasoning (logic)

QUANTITATIVE RESEARCH •

Is best suited to the investigation of structure rather than process



Can answer “how many”, “what” and “where” questions



Relies on predetermined response categories and standardised data collection instruments



The standardised measurement and sampling procedures are intended to enhance the validity and reliability of observation (counting) and to facilitate replication studies

SAMPLING IN QUANTITATIVE RESEARCH •



Aim for generalisation to a larger (study) population. –

Sample size = large



Random sampling from study population is preferred when possible, where not possible systematic, stratified and cluster sampling methods may be used



Why?

And verification of theory

DATA ANALYSIS IN QUANTITATIVE RESEARCH

I. Descriptive statistics •

Simple distribution (one variable)



Bivariate relationships (2 variables., e.g. frequency distributions)



More than 2 variables (tri/multivariate, e.g. multiple regression analysis)

Inferential statistics Use probability theory: •

to test hypotheses



to draw inferences as to whether results from a random sample hold true for a designated study population (generalisability)



to test whether descriptive results are likely to be due to random factors or to a real relationship. It helps researchers decide whether a relationship really exists between different sets of statistical results

NEED TO KNOW - CONCEPTS Statistical significance •



means that results are not likely to be due to chance factors – the probability of finding a relationship in the sample when there is none in the population. It tells the researcher whether the results are produced by random error in random sampling. Results an be statistically significant but theoretically meaningless or trivial. BEWARE OF THE STATISTICIAN!

Probability theory •

refers to a process that generates a mathematically random result – that is, the selection process operates in a truly random method and a researcher can calculate the probability of outcomes. It is a true random process in that each element has an equal probability of being selected.

STEPS IN DESIGNING A QUANTITATIVE STUDY • • • •

Formulate a researchable question Review related literature State hypotheses Determine the variables to be studied – Identify dependent, independent, control and other variables – Determine how these variables will be operationalised – Determine level of measurement

• • •

Determine research plan/method of data collection Define population Determine what instruments will be used to collect data – Pretest instruments



Determine statistical tests to use

DATA COLLECTION IN QUANTITATIVE STUDIES • Experimental – Simple post-test – Classic pre-test, post-test – Pre-test, post-test, control group

• Secondary analysis of quantitative data • Observation – Use check or tally sheet

• Surveys – Use questionnaires

QUALITATIVE RESEARCH •

The aim of qualitative research is to “get close to the data in their natural setting”



It is designed to best reflect an individual’s experience in the context of their everyday life.



It uses smaller sample sizes and digs deeply for data.

DATA COLLECTION IN QUALITATIVE RESEARCH •

Participant observation



Case studies



Formal and informal interviewing



Videotaping



Archival data surveys OR document review



Emphasises comprehensive, interdependent, dynamic and holistic structures



Is appropriate in the investigation of “messy” problems and complex, interdependent issues, and allows for the collection of rich data that can explore the “why” and “how” of the problem, and not just the “what” (quantitative research)



Often draws on multiple sources of data



Is particularly appropriate to the investigation of research problems that are under-theorised, given its strength in generating / developing theory (inductive).

DATA ANALYSIS IN QUALITATIVE STUDIES •

Discourse analysis



Narrative analysis



Content analysis



Thematic analysis

SAMPLING IN QUALITATIVE RESEARCH •

Sampling is mostly purposive – with specific criteria in mind!



Seek conceptual applicability rather than representativeness (quantitative representivity)



You want to capture the range of views/experiences



Or seek after/pursue saturation of data



Or to draw theory from data.

TRIANGULATION IN QUALITATIVE RESEARCH •

Data triangulation – multiple data sources to understand a phenomenon



Methods triangulation – multiple research methods to study a phenomenon



Researcher triangulation – multiple investigators in analysing and interpreting the data



Theory triangulation – multiple theories and perspectives to help interpret and explain the data

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Research design and methods Part II - UWC

Research design and methods Part II Dr Brian van Wyk POST-GRADUATE ENROLMENT AND THROUGHPUT From last week… • Research methodology – Quantitative v...

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