ARAŞTIRMA YÖNTEMLERİ - Deneme Sınavı - 15

The term “research ethics” has also been associated with how researchers ought to treat research participants in terms of protecting their rights (such as causing them no harm, respecting their autonomy, or preserving their privacy, etc.). According to Schüklenk (2005, p. 3), for example, “Research ethics is basically about means of ensuring that vulnerable people are protected from exploitation and other forms of harm.”

Hammersley and Traianou (2012) conceptualize “research ethics” as a form of “occupational/professional ethics” and assert that a distinction needs to be made between “intrinsic” and “extrinsic” values of research. Intrinsic values (such as dedication, objectivity, and independence of researchers) relate to the goal of research (i.e., the production of knowledge) while extrinsic values relate to how research participants ought to be treated in the course of research (such as respecting for autonomy, protection of privacy, and/or minimization of harm).

The Nuremberg Code is the most important milestone in research ethics. Because the ethic codes developed in different areas of social sciences were based on the Nuremberg Code.

A widely accepted definition of “research misconduct”, as it appears in the USA Federal Policy on Research Misconduct (https://www.aps. org/policy/statements/upload/federalpolicy.pdf) is as follows: •Research misconduct is defined as fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. •Fabrication is making up data or results and recording or reporting them. •Falsification is manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record. •Plagiarism is the appropriation of another person’s ideas, processes, results, or words without giving appropriate credit. •Research misconduct does not include honest error or honest difference of opinion. Consent:  A voluntarily and competently given permission to be researched. Autonomy:  The capacity of a participant to make a reasoned decision for himself/herself, for example, whether to take part in a research voluntarily.

Correlational studies enable the researcher to identify how one or a set of variables are related to another or enable the researcher to make predictions. Especially in the case where it is difficult to conduct an experimental study, the researcher can make use of the available data to analyze the relationships among different variables. Correlational research contradicts with experimental research in the sense that no variable is manipulated in this method. Thus, it is important to say that correlation should not be confused with causal relation, it only provides an existing or nonexisting relationship between variables.

Causal comparative research which is also called as ex post facto (after the fact for Latin) attempts to determine the cause or consequences of differences that already exist between identified set of subjects. An example research study could be that of Weinschenk and Dawes (2017). They were interested in examining the roots of individuals’ politial engagement and explored if biological and psychological factors play a role in the formation of politcal interest.

A popular strategy for doing survey research is cross-sectional research, which means collecting data through a survey across a pretermined population at one point in time. Thus, the survey is administered to a representative sample at the same time.

The researcher needs to avoid four types of errors as cornerstones of good quality surveys.

• Coverage error, which refers to drawing samples form a list of irrelevant samples to represent the population

• Sampling error, which exists any time when the researcher reaches some of the sample and not all members. For instance, instance, to understand the attitudes of political participation of university students the researcher only randomly selects students from one province as the available population rather than the whole country to generalize the findings to the target population;

• Nonresponse error, which occurs when some particular units of analysis tend to answer some particular items which are likely to influence the estimate of the findings;

• Measurement error is described as the difference between the estimate produced and the true value in case the respondents may answer inaccurately to the survey questions.

Response rate probability is the poorest when data is collected per mail whereas it is very high with telephone calls and face-to-face interviews.

Face-to-face data collection does not allow for group administration; however, it does allow for random sampling, its cost efficiency is high, and standardization of responses is very hard.

Research questions should be feasible so that there is available time, energy, and even sufficient budget to investigate them. For instance, rather than administering a questionnaire to the entire population, a random sampling strategy could be selected and generalized to the population.

A variable is a concept that may refer to any variation in a context. For example, artifacts used in elections can be a variable. Gender, education, nationality are all nouns that can be counted as variables.

Systematic sampling is the selection of a sample systematically from the population- it belongs to the non-random sampling strategy. Consider the 4000 students in a list of a university campus, you may systematically select the 10th student. In other words, the researcher selects from the list the student number 10, 20, 30, and so on, until 4000. In case the researcher wants to make sure to avoid any biases possible, can randomly select the first number from a box numbered 1-10, and if the figure 2 appears, he or she can select the every 12th, 22nd, 32nd and so forth.

Mixed methods research can be defined as research designs using qualitative and quantitative data collection and analysis techniques in either parallel or sequential phases. The MMR can be stated as a process of research when researchers integrate quantitative methods of data collection and analysis and qualitative methods of data collection and analysis to understand a research problem. It corresponds to the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts or language into a single study.

Mixed methods research can be conducted in the following steps:

Greene, Caracelli, and Graham (1989) suggest that five major objectives or motivations exist for conducting MMR. The first one is ‘triangulation’, which provides validation and concurrence of results gained from various methods and designs investigating the same circumstance. ‘Complementarity’, as the second motivation, seeks for further detailing, improvement, interpretation and description of the results obtained from one method with results from the other method. The third one is ‘initiation’, which means unearthing the bias, and discrepancies that cause re-designing of the research question. ‘Development’, the fourth motivation, includes utilizing the findings from one method to deliver clues to other method. The last motivation, ‘expansion’, seeks to expand the size of research with different methods for different investigation factors.

In respect of limitations, a single researcher may have some difficulties on conducting both qualitative and quantitative research when s/he intends to use two or more ways all at once. Thus, a research team may be needed to get the best results. Furthermore, learning about multiple methods and approaches and understanding how to mix them aptly should be regarded as a must. Conducting MMR can also be more expensive, time consuming and may require formulating how to mix paradigm, analysing quantitative data or interpreting the paradoxical results by research methodologist

Five major standard research objectives are pertinent for the quantitative and qualitative phases of the study: a) exploration, b) description, c) explanation, d) prediction, and/or e) influence. The first type of research objective, exploration, comprises inductive methods to figure out an opinion, argument and the like. In this way, it brings about intuition, hypotheses, deductions or generalization. Description, the second type, means clarifying and defining the previous experiences, relations, and the nature of the incident. One should develop or broaden a theory to achieve ‘explanation’ to find out the phenomena. Another type of research, prediction, enables the researcher to predict future events by means of previous knowledge. The fifth type of objective, influence, includes ‘the manipulation of a variable or construct’ so as to achieve an outcome.

Participant enrichment means making sampling better by blending quantitative and qualitative research approaches in order to select eligible participants for the study. It involves blending quantitative and qualitative research to better the sample using approaches that encompass recruiting participants, dealing with activities such as institutional review board interviews assuring that each participant chosen is eligible for involvement.