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 vs. Qualitative vs. Participatory/action research

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

Research design – Experimental, descriptive, exploratory


Logic of the inquiry

Purpose of the inquiry

Types of research design

Directions of reasoning (logic)


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


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


And verification of theory


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.


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


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.


Participant observation

Case studies

Formal and informal interviewing


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).


Discourse analysis

Narrative analysis

Content analysis

Thematic analysis


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.


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


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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