ARAŞTIRMA YÖNTEMLERİ

A mixed method research includes (i) hypothesis or quantitative research questions (ii) qualitative research questions, and (iii) mixed method research questions. As you know, previous sections have been dedicated to explaining how hypothesis or quantitative and qualitative research questions should be written and what their characteristics are. 

While planning mixed method research studies, research questions should be written in a way that transcends quantitative and qualitative methods and requires use of mixed method. In other words, mixed method research questions should not emphasize only quantitative or qualitative research approaches but they should combine both methods. Writing research questions in this way is also known as method centered approach. However, writing research questions in this way entails a certain command of knowledge about mixed method designs. Accordingly, a researcher should develop her/his research questions compatible with the research design s/he will employ.

The second approach to writing mixed method research questions is labeled as content-centered approach.

This design aims to integrate the results obtained from both qualitative and quantitative data analyses. Researchers adopting this design collect both qualitative and quantitative data simultaneously. In other words, collection of neither qualitative nor quantitative data is prioritized. Data is collected and analyzed separately. Later, the results produced after data analyses are combined. So, the researcher can check whether quantitative and qualitative results confirm each other.

* Abbreviations such as QUAN and QUAL indicate that either a quantitative or a qualitative method is dominant and prioritized in that mixed method research. If these two approaches are evenly employed within a mixed method research, then both of the upper-case initials are included.

* Lower case initials such as Quan and Qual represent the less dominant or recessive approach. 

* Plus (+) points out the integration of collected data, and it is also used to mark quantitative and qualitative data sets are collected simultaneously.

* Arrow “→” shows that data is collected consecutively. When this symbol is used, the researcher bases the approach (e.g. qualitative) s/he will utilize in the second stage onto the one in the first stage (e.g. quantitative).

*  Parentheses “( )” mean that there will be an addition to some parts of the research, and square brackets “[ ]” symbolize that another independent study has been embedded into the current research.

Scientific research is the process of systematic and planned data collection, data analysis, assessment and interpretation, and reporting in order to figure out reliable and valid solutions to problems by limiting them (Erkuş, 2011). According to another definition, it is a process to gather and analyze information so as to gain insight about a topic or issue (Creswell, 2012). Based on these definitions, it is possible to deduce that a scientific research process involves 1) problem identification, 2) data collection, 3) data analysis, 4) interpretation, and 5) report writing.

The positivist paradigm advocates that reality will surface precisely through logic and experiment.

Quantitative research is based on positivist paradigm, which advocates that reality will surface precisely through logic and experiment. Accordingly, it strives to formulate universal laws for each field of scientific study. Such a stance with respect to the nature of reality led to the birth of a research design to produce knowledge that is measurable, replicable, generalizable, intact, and value-free judgements. Being "value-laden" is a characteristic that is not desirable in quantitative research.

Issues regarding metaphysical events, philosophy, theology, and astrology are not suitable to form research problems in a scientific sense as they cannot be examined in empirical studies. Issues in psychology, however, can be empirically studied.

Primary building blocks of quantitative research are the variables (Christensen et al., 2014).

If a variable can only assume certain values or options, and if it can be expressed through only whole numbers, then it is a discrete variable. For example, gender variable can assume either male or female option.

Continuous variables are those that can take any value between their bottom and top limits, that is to say,
they can be expressed in fractions. For instance, the value that variable of weight can assume ranges from zero to infinity (Karasar, 1994).

Hypotheses are of two major types: statistical and research hypotheses. Statistical hypothesis (H0- neutral hypothesis, null hypothesis, absence hypothesis) denotes that there is either no relation or difference between the variables. Research hypothesis, on the contrary, (H1- difference hypothesis, alternative hypothesis) is the expression of the relation that a researcher hopes to confirm after relevant data collection and analysis (Altunışık, Coşkun, Bayraktaroğlu, and Yıldırım, 2005).

Repeated-Measurement design is preferred when the precise time for the emergence of independent variable’s effect is not certain and it is not clear when to conduct the most reliable pre-test.

In intervention analysis design, the dependent variable is subjected to pretest and post-test procedures prior to testing the independent variable experimentally.

It is possible to deduce that a scientific research process involves 1) problem identification, 2) data collection, 3) data analysis, 4) interpretation, and 5) report writing.

A well-defined quantitative research problem has to bear some certain features. First, the variables in the problem have to explain a relation. Second, it has to be formulated as a question.Third, a research problem has to be suitable for analysis based on collected data, or it has to be testable.

A hypothesis is the conversion of a research problem into a tangible form that can be examined and tested.A hypothesis is either an educated guess about the result of a problem or a temporary solution to a problem. Thus, a well-developed hypothesis should clearly point out the dependent and independent variables, their levels, the research model, and whether the relation or difference will be studied in that research (Erkuş, 2011). As a matter of fact, comprehensive knowledge about the field of study is indispensable to produce a well-developed hypothesis.

Research design is the arrangement necessary to collect and analyze research data in the most economical way. There are two primary research designs often utilized for quantitative research studies, which are survey and experimental designs. A researcher’s choice to employ either survey or experimental design is highly correlated with the hypothesis or research questions s/ he develops in the previous stage.

Longitudinal study aims to collect data at least two or more times. Such studies generally last for years. Thus, longitudinal studies may not be the best choice when sources and financial support is limited and quick results are expected.

Repeated-Measurement Design: This design is preferred when the precise time for the emergence of independent variable’s effect is not certain and when it is not clear when to conduct the most reliable pre-test. Accordingly, researchers administer different assessment and measurement tools before and after the experiment.

Qualitative research strives to build up a theory by investigating and understanding social phenomena in their natural environments (Yıldırım and Şimşek, 2013). During a qualitative research process, researchers focus on people’s behaviors, actions, and interactions. Research process aims to comprehensively understand human behaviors in their natural environments,