Data are the raw materials with which research can build. The term data means systematically collected groups of information that represents the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. It often viewed as the lowest level of abstraction from which information and knowledge are derived. Data collection itself involves administrating instruments as well as gathering and organizing responses and measures for analysis. So for making a well-planned data collection process, the major task is to define data clearly that it can fulfil the research requirement. The researcher may bring different assumptions to his work; data gathered by different methods may provide different windows onto the social world (Gilbert, 2008).
Now the question requires explaining the factors which are needed to define the data of a study. That means, before starting data collection, what would be the essential steps in order to meet the research demand. Basically, the researcher needs to interconnect with theory and methods which affect each other. Data is meaningless in the absence of a theory. Absence of it, no reasonable operational techniques or inductive procedures exist for extracting anything from data that can lead to insight or understanding in-focus area. Besides this, the theory is needed for deciding the methods of gathering data. For instance, descriptive theories are generated and tested by descriptive research which can employ empirical methods of data collection. The several factors which are needed to define data are described below.
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Principle of the Research
The research process usually begins with the theoretical perception or formulation of the research topic (Sarantakos, 2005). Before start, the researcher obviously needs to have some ideas on what area he going to deal with. Finding the focus involves identifying what is the researcher wants to gather information about (Robson, 2002). Except for this, planning for doing research is impossible. For instance, a researcher has the interest to understand why students dislike mathematics. However, this initial interest is far too broad to study in any single research project. The researcher has to narrow the question down to one that can reasonably be studied in a research project. This might involves formulating a hypothesis or a focus question. A researcher might hypothesize that a particular mathematical method avoided by school students in a specific district. At the narrowest point of the research hourglass, the researcher is engaged in direct measurement or observation of the question of interest. The principle of the research should be clearly defined by researcher; it can be varying but the presence and necessity are taken for granted (Sarantakos, 2005). There are three basic research paradigms – positivism (quantitative, scientific approach), interpretivism (qualitative approach), and critical science (Cantrell, 2006). These paradigms based on the assumption of the world.
The term ‘Positivism’ has applied to the conventional approach to research which incorporates methods and principles of natural science for the study of human behaviour (Burns, 2000). It includes a fairly sharp distinction between theory and research and includes elements of both deduction and induction (Bryman & Teevan, 2005). Actually, social research demands solid and repeatable results. Before initiate a research project, a researcher faces confusion on using appropriate theoretical perspectives, methodologies and the philosophical basis that need to encompass. This seemingly meticulous structure for the research process is aimed toward providing the researcher with a direction which they can go on to develop themselves to coincide with their particular research purposes (Cortty, 1998). Once a researcher has developed a set of research questions, he must consider what methods going to employ in the research, what theoretical perspective lies behind the methodology, and what epistemology informs this theoretical perspective. This will have a salient impact on the kind of data which can collect in order to validate their arguments concerning the methodology. A researcher’s choice of methods will be conditioned by theoretical perspectives, the way one sees the social world. Researchers can use a wide variety of research methods to gain and enhance knowledge and theory. The different types of research methodologies, quantitative and qualitative, are associated with the epistemological and theoretical perspectives the researcher wishes to adopt.
Positivism means a scientific approach, which is suitable for quantitative research. On the other hand, interpretivism, or the qualitative approach, is a way to gain insights through discovering meanings by improving our comprehension of the whole. These two methods of reasoning have a very different “feel” for conducting research. Qualitative research explores the richness, depth, and complexity of any phenomena. Broadly defined, any kind of research that produces findings not arrived at by means of statistical procedures or other means of quantification (Corbin & Strauss, 2009). Before using qualitative techniques, it is essential to cover some general issues about the nature and purpose of qualitative enquiry (Travers, 2001). Researchers have to have a good reason to choose an interview, observation, focus group or another kind of qualitative method. The underlying assumption of interpretivism is that the whole needs to be examined in order to understand phenomena. Interpretivism is critical of positivism because it seeks to collect and analyze data from parts of phenomena and, in so doing, positivism can miss important aspects of a comprehensive understanding of the whole. Interpretivism proposes that there are multiple realities, not single realities of phenomena and that these realities can differ across time and place. Unlike quantitative research, there is no overarching framework for how qualitative research should be conducted; rather each type of qualitative research is guided by particular philosophical stances that are taken in relation by the research to each fact.
All scientific research, indeed all human knowledge, follows a set of procedures that must begin with a group of assumptions, a set of beliefs and a paradigm. However, once a paradigm for research has been chosen, it is by no means settled what strategies and types of data collection and analysis are to be employed. All too often, research studies are criticized for their methodology without any consideration of the paradigm within which they fall. The critical theories are regularly used in post-modernism, advocacy and feminist research. Both quantitative and qualitative methods can be utilized and the researcher has to employ value-laden methods and procedures. Critical researchers assume that social reality is historically constituted and produced and reproduced by people. Although people can consciously act to change their social and economic circumstances, critical researchers recognize that their ability to do so is constrained by various forms of social, cultural and political domination. The main task of critical research is seen as being one of social critique, whereby the restrictive and alienating conditions of the status quo are brought to light. Critical research focuses on the oppositions, conflicts and contradictions in contemporary society, and seeks to be emancipator.
The Research Process
Before starting a research project, the questions come first, ‘where do begin’ and ‘what is the next step’ or ‘what is the first step for doing research’ and ‘what would be the right step after that’. The first step towards doing research is to develop a research plan which can describe the summary of its main elements; what would be studied and how it would be accomplished; and finally how the data would be gathered, analyzed and published. This manner would be conducted in determining the methodology that underlies the research. A researcher can adopt a different way to conduct qualitative and quantitative research. Basically, any research process has five basic criteria but before data collection, the three major steps should be performed by the researcher. Firstly, the research topic and methodology should be decided on. After that, the methodological construction of the topic, and then the sampling procedure should be determined. Subsequently, the data collection plan and execution, the fourth data analysis and interpretation and finally the report writing procedure would be followed. Here, the steps before defining data are summarized.
Define Research Goals and Objectives
An important initial step before defining data is to make an inventory of the type of data the researcher wants to collect and from whom it would be collected. Research questions can use as a guideline in order to define goals and objectives. Most social research originates from some general problems or questions. Usually, the problem is broad enough that one could not hope to address it adequately in a single research study. Consequently, researchers typically narrow the problem down to a more specific research question that can hope to address. The research question is often stated in the context of some theories that have been advanced to address the problem. Researchers may use different approaches in collecting data, such as the grounded theory practice, narratology, storytelling, sample survey, classical ethnography, or shadowing. Qualitative methods are loosely present in other methodological approaches, such as action research or actor-network theory. Forms of the data collection can include interviews and group discussions, observation and reflection field notes, various texts, pictures, and other materials.
Define Nominal and Operational Definitions of Data
In methodology, it should clearly define what type of data will be collected and how it will accomplish. It should be decided what is going to evaluate and determine, how a numerical value will assign. In research, conceptual definitions can explain what the researcher constructs by showing how they relate to other constructs. This explanation and all of the constructs it refers to are abstract — their existence is only as real and concrete as the thoughts researcher have. To work with constructs, the researcher must have to establish a connection between them and the concrete reality in practice. This process is called operationalization. Operational definitions describe the variables that will use as indicators and the procedures will use to observe or measure. A researcher needs an operational definition because he can’t measure anything without one, no matter how good a conceptual definition it might be. It is the best way to obtain a complete understanding of an agreement on all the applicable definitions, procedures and guidelines that will be used in the data collection process. Overlooking this step can create misleading results if interpreting loosely defined terms differently when collecting data. In the case of examining historical data, careful attention should be paid to how reliable the data and its source have been, and whether it is advisable to continue using such data. Data that proves to be suspect should be discarded.
Ensuring Data Repeatability, Reproducibility, Accuracy and Stability
In social research, data is collected and measured will be repeatable if the same operator is able to reach essentially the same outcome multiple times on one particular item with the same equipment. Also, data will be reproducible, if all the operators who are measuring the same items with the same equipment are reaching essentially the same outcomes. In addition, the degree to which the measurement system is accurate will generally be the difference between an observed average measurement and the associated known with a standard value. The degree to which the measurement system is stable is generally expressed by the variation resulting from the same operator measuring the same item, with the same equipment, over an extended period. To improve this situation, a researcher has to cognizant of all the possible factors that would cause reductions in repeatability, reproducibility, accuracy and stability – over any length of time – that in turn may render unreliable data. It is good practice to test, perhaps on a small scale, how the data collection and measurements will proceed. It should become apparent upon simulation what the possible factors are, and what could be done to mitigate the effects of the factors or to eliminate the factors altogether. Many researchers thought that validity is more important than reliability because if an instrument does not accurately measure what it is supposed to, there is no reason to use it even if it measures consistently (reliably). There is a common misconception that if someone adopts a validated instrument, he does not need to check the reliability and validity of his own data. However, there can be validity without reliability and any repetitive measurement needs to change and examine. In addition, low reliability is a signal of high measurement error which reflects gaps between respondent’s actual knowledge and what they answered.
Improving Measurement System and Construct Data Collection Guidelines
Measurement is the assignment of numbers to objects or events in a systematic approach. Four levels of measurement scales are commonly distinguished: nominal, ordinal, interval, and ratio. There is a relationship between the level of measurement and the appropriateness of various statistical procedures. These scales of measure are expressions that typically refer to the theory of scale types developed by the psychologist Stanley Smith Stevens. It is important to very clear about what are measuring, how it is to be measured, and who is to measure it. Many statistical methods are appropriate only for data of certain measurement scales. When selecting a statistical method, it is essential to understand how the data to be analyzed were measured. The best stage of investigation for thoughtful measurement scales is the design stage, at which the statistical limitations imposed by certain measurement scales may influence your choice of observations and methods of measurement. There are several crucial steps that needed to be addressed to ensure that the data collection process and measurement systems are stable and reliable. Incorporating these steps into a data collection plan will improve the likelihood that the data and measurements can be used to support the ensuing analysis. To describe these steps, a checklist, populated with dummy responses, is also provided to illustrate the importance of building a well-defined data collection plan prior to execution.
Sampling in Data Collection
There is common understating, sample is a part of a population whose properties are studied to gain information about the whole (Webster, 1985). It is a process of selecting a respondent form a larger part for the purpose of a study. There are several types of sampling techniques are used in research but there is a danger to use inappropriate sampling technique. Researchers have to have a keen understanding of different types of sampling procedure, determine sample size, sampling errors and also the way of minimizing these errors. Deciding on sample size for qualitative inquiry can be even more difficult than quantitative because there are no definite rules to be followed. It will depend on what the researcher wants to know, the purpose of the inquiry, what is at stake, what will be useful, what will have credibility and what can be done with the available time and resources. In sampling, the sample should be judged on the basis of the purpose and rationale for each study and the sampling strategy used to achieve the studies purpose. Prior to any data collection, pre-collection activity or piloting is one of the most crucial steps in the process. It is often discovered too late that the value of the interview information is discounted as a consequence of poor sampling of both questions and informants and poor elicitation techniques. After the pre-collection activity is fully completed, data collection in the field, whether by interviewing or other methods, can be carried out in a structured, systematic and scientific way.
Defining data is not easy to process, a well-defining research topic, research questions and hypothesis are the base of obtaining accurate and consistence information. After that, establish an operational definition and create suitable measurement scales which need to standardize by testing several times. Researchers have to skill enough to blend their theoretical knowledge with practical situation. Long and careful planning is needed before data collection. Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. Different ways of collecting evaluation data are useful for different purposes, and each has advantages and disadvantages. Various factors will influence to choose the choice of a data collection method: the questions the researcher wants to investigate, resources available to him, his timeline, and so on. A formal data collection process should be well-defined and accurate that embodied validity in the findings.
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