1. Research methodology A plan and structure of the investigation in order to obtain evidence to answer the research questions. RM Involves a. choosing the subjects b. data collection techniques/tools c. procedures/steps for collecting data d. data analysis techniques/tools e. procedures/steps for analysing data

2. Working definition Quantitative research involves data collection procedures that result primarily in numerical data which is then analyzed primarily by statistical methods. Eg: survey research using questionnaire, analysed by statistical software such as SPSS.

3. Features of quantitative research method 1.Centred around numbers However, numbers need contextual backing. We need to specify the category we use the number for, eg what do the numbers 1, 2, 3 mean. 2. A priori categorisation Since numbers dominate the data collection phase, the categories and values are specified prior to the actual study. Eg: if respondents are asked to encircle figures in a questionnaire, they need to know what those figures represent, and to make sure each respondent gives their numerical answer based on the same understanding, in order to avoid ambiguity.

4. 3. Variables rather than cases Quantitative research is interested in common features of groups of people. Large samples are taken and the results show commonalities that exist in the sample normally through through the use of averages. Qualitative research on the other hand looks at individuals as cases.

5. 4. Statistics Salient feature of quantitative research. Statistical analyses is quite advanced ranging from simple averages /mean to complex multivariate analyses. The language of statistics is part of the quantitative vocabulary. 5. Standardized procedures to assess objective reality Procedures are standard to ensure they remain stable across investigators and subjects. When different researchers observe the same phenomenon using standardized measures, their findings will show agreement and convergence. Objective independent of researcher’s subjective perceptions.

6. 6. Quest for generalizability and universal laws There is a quest for generalizability in the results obtained. The design aspires for wide ranging applicability in the findings.

7. Strengths Quant inquiry is systematic, rigorous, tightly controlled, involves precise measurement, produces reliable and replicable data, and is generalizable to other contexts. The use of statistics offers quality checks that support the validity of the quan findings. Practically, the research process is quick and offers value for money because the data analysis can be done fast using statistical computer software. Quan findings enjoy high reputation with any audience or stakeholder groups.

8. Weaknesses Does not account for the subjective variety of individual life. This is because the method averages responses across the whole group of participants. Not sensitive in uncovering reasons for particular observations or the dynamics underlying the phenomenon or situation. Quan method cannot explain the why. The exploratory capacity is limited. Often labelled as overly simplistic, decontextualised, reductionist in its generalisations, and fail to capture the meanings that subjects attach to their lives.

9. Quan research designs Designs are templates which involve standard guidelines for doing the research. Common quan research designs are: a. descriptive research or survey b. correlational research c. experimental research

10. Descriptive research or survey Involves making careful descriptions of the phenomena studied. Involves getting the thoughts, perceptions and opinions of a large population regarding an issue. The major purpose is to describe the characteristics of a population and how the members of the population distributes themselves on the phenomena investigated.

11. The research involves the administration of questionnaires or interviews to sample groups of research participants. A number of questions related to the issue are asked. Responses are reported in the form of frequencies or percentages. Two types of surveys: cross-sectional and longitudinal.

12. Correlational research Correlational research is a type of descriptive research because it does describe an existing condition. The design involves collecting data to determine whether and to what degree a relationship exists between two or more quantifiable variables. The degree of relationship is expressed as a correlation coefficient. If a relationship exists between two variables, scores within a certain range on one variable are associated with scores within a certain range on the other variable.

13. The purpose of a correlational study is to basically determine relationships between variables and use these relationships to make predictions. It provides a numerical estimate of how closely or how distantly related two variables are. The higher the correlation, the closer the two variables are related and the more accurate the predictions based on the relationship. The quality of correlational research is in the selection of the variables to be correlated to one another.

14. Experimental research Experimental research is conducted to establish cause and effect relationships. One variable is manipulated (independent variable) and observes the effect on another variable (dependent variable- one or more). The independent variable may be a treatment, such as a method of instruction, type of learning materials, a program, etc that causes some outcome or result. The dependent variable may be measured through a test. It is the posttest variable.

15. Quantitative and qualitative research methods The difference between the two involves method of data collection, the nature of the collected data, the method of data analysis used to process the data and to obtain results. Although they are two different approaches to empirical research, they are not exclusive of each other. Their principled combination has led to an emerging third research approach – mixed method approach.

16. Qualitative research – Working definition Qualitative research involves data collection procedures that result primarily in open- ended, non-numerical data which is then analysed primarily by non-statistical methods. Eg: interview research, with the transcribed recordings analysed by content analysis.

17. Features of qualitative research 1.Emergent research design The design of the study emerges as the research progresses. The design is seldom a priori. Research methods are not tightly prefigured and are kept open so that the study can respond in a flexible way to new details that may emerge in the process of the research. See pg 39

18. 2. The nature of qualitative data Wide range of data - recorded interviews (transcribed), written texts such as documents, field notes, journal and diary entries, and images such as photos and videos. The data deals with words. It captures rich and complex details in order to make sense and describe a social phenomenon. ‘thick’ description.

19. 3. Natural research setting Because qual research describes a social phenomenon, the research setting is natural, unmanipulated. The researcher often needs to immerse in the research setting in order to be able to capture the details of the natural context. Immersion is often intense and involves prolonged contact.

20. 4. Insider meaning Qual research is concerned with opinions, experiences and feelings of individuals in the situation studied. Qual research is concerned with meaning as understood by people in particular situations and contexts. The design strives to view social phenomena from the perspectives of the ‘insiders’ and thus the term ‘insiders’ perspective’.

21. 5. Small sample size Since the concern is on descriptions of social meaning from the perspective of individuals, qual research is labour intensive and can only deal with small sample size, ranging from 2- 15.

22. 6. Interpretive analysis The research outcome is fundamentally the product of the researcher’s subjective interpretation of the data. Pg 38.

23. Strengths 1.Exploratory nature The method is good for work that is exploring new, uncharted areas. 2. Making sense of complexity Useful for making sense of complex situations. In complex situations, participant-sensitivity is helpful in deciding what aspects require special attention because the voice of the participants are prioritised in qual research.

24. 3. Answering ‘why’ questions Provides ‘thick’ descriptions and is able to explain social phenomena. 4. Broadening our understanding Broadens the repertoire of possible interpretations of human experience through thick descriptions.

25. 5. Longitudinal examination of dynamic phenomena Useful for longitudinal research in order to examine sequential patterns and changes that occur over time. 6. Flexibility when things go wrong Because the design is flexible and is not a priori.

26. 7.Rich material for the research report Because the research is data-driven. Makes use of words and categories of the participants.

27. Weaknesses 1.Lacking generalizability Cannot be broadly applied to others as a result of small sample size and specific conditions in the situation and context. 2. Researcher role Interpretation of data is dependent on the researcher’s values, personal history and position on characteristics such as gender, culture, class and so on. As a result findings can be influenced by researcher bias.

28. 3. Time consuming and labour-intensive. Takes months to produce the findings.

29. Mixed methods research involves different combinations of qualitative and quantitative research either at the data collection or at the analysis levels. Eg: interrelated questionnaire and interview studies.