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{R} Design

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A research design is “an integrated statement of and justification for the technical decisions involved in planning a research project” (Blaikie, “Designing Social Research”, p. 15).



Methodology

This chapter situates the study within a particular methodological tradition, provides a rationale for that approach, describes the research setting and sample, and describes data collection and analysis methods. The chapter provides a detailed description of all aspects of the design and procedures of the study.

• Introduction: The introduction restates the research purpose and describes the organization of the chapter.

• Rationale for research approach: This section describes the research tradition or paradigm (qualitative research) and the research methodology (phenomenology, case study, action research, etc.) with a rationale for their suitability regarding addressing the research questions, and citing appropriate methodological literature.

• Research setting/context: This section describes and justifies selection of the research setting, thereby providing the history, background, and issues germane to the problem.

• Research sample and data sources: This section:

− explains and justifies the sample used and how participants were selected (including population and sampling procedures);

− describes the characteristics and size of the sample, and provides other pertinent demographic information; and

− outlines ethical considerations pertaining to participants, shedding light on how rights of participants were protected, with reference to conventions of research ethics and the IRB (institutional review board) process.

• Data collection methods: This section describes and justifies all data collection methods, tools, instruments, and procedures, including how, when, where, and by whom data were collected.

• Data analysis methods: This section describes and justifies all methods and tools used for analysis of data (manual and/or computational).

• Issues of trustworthiness: This section discusses measures taken to enhance the study, as well as credibility (validity) and dependability (reliability).

• Limitations and delimitations: This section identifies potential weaknesses of the study and the scope of the study. Limitations are external conditions that restrict or constrain the study’s scope or may affect its outcome. Delimitations are conditions or parameters that the researcher intentionally imposes in order to limit the scope of a study (e.g., using participants of certain ages, genders, or groups; conducting the research in a single setting). Generalizability is not the goal of qualitative research; rather, the focus is on transferability—that is, the ability to apply findings in similar contexts or settings.

• Summary: A comprehensive summary overview covers all the sections of this chapter, recapping and highlighting all the important points. Discussion is concise and precise.

Reason
The study is the basis for the conclusions and recommendations. In many ways, it is what makes the difference between a dissertation and other forms of extended writing. A clear description of the research sample, setting, methodology, limitations, and delimitations and acknowledgement of trustworthiness issues provide readers with a basis for accepting (or not accepting) the conclusions and recommendations that follow.

Quality Markers
A quality study achieves the purposes outlined in the introduction’s research problem and research questions. The relationship of the research paradigm and type of data collection and analysis used in this study is clear. All relevant information is clearly articulated and presented. Narrative is accompanied by clear and descriptive visuals (charts, figures, tables).

Frequent Errors
Errors occur when data are not clearly presented; the study is not applicable to purposes outlined in the introduction; and methods of gathering and analyzing data and trustworthiness issues are insufficient or not clearly explained.

◥ University. {q} PhD. {tr} Training. {R} Design. Operationalization. An example of operationally defining "personal space".[1] The concept of operationalization was first presented by the British physicist N. R. Campbell in his 'Physics: The Elements' (Cambridge, 1920). This concept next spread to humanities and social sciences. It remains in use in physics.[2][3][4][5][6][7] Theory[edit] History[edit] Operationalization is used to specifically refer to the scientific practice of operationally defining, where even the most basic concepts are defined through the operations by which we measure them. Bridgman's theory was criticized because we measure "length" in various ways (e.g. it's impossible to use a measuring rod if we want to measure the distance to the Moon), "length" logically isn't one concept but many, some concepts requiring knowledge of geometry.

Bridgman notes that in the theory of relativity we see how a concept like "duration" can split into multiple different concepts. Operationalization[edit] In the social sciences[edit] Anger example[edit] Research Design. Research purposes. Research purposes[edit] Research involves systematic investigation of phenomena, the purpose of which could be for: Information gathering and/or Exploratory: e.g., discovering, uncovering, exploringDescriptive: e.g., gathering info, describing, summarisingTheory testingExplanatory: e.g., testing and understanding causal relationsPredictive: e.g., predicting what might happen in various scenarios Examples of research studies with these different purposes can be found in this practice quiz.

See also[edit] External links[edit] Case and Grounded Theory As Qualitative Research Methods. Case and grounded theory are two methods of qualitative research. Both methods have their roots in sociology and are focused on understanding, explaining, and/or predicting human behavior. They are ideal methods for nursing research, as they are useful for exploring human responses to health problems. The theoretical underpinnings, methodologies, strategies for data collection, requirements for trustworthiness, and examples of research using case and grounded theory are described. Two methods of qualitative inquiry axe case method and grounded theory. The two methods will be discussed together because although they have different goals, their roots are in sociology and they employ several of the same strategies for data collection.

The goal of case method is to describe a contemporary situation within its real-life context (Stake, 1995; Yin, 2003). Case Method Case studies are familiar to most nurses. A research study can be designed to study a single case, or multiple cases. Documents. Longitudinal study. A longitudinal survey is a correlational research study that involves repeated observations of the same variables over long periods of time — often many decades.

It is a type of observational study. Longitudinal studies are often used in psychology to study developmental trends across the life span, and in sociology to study life events throughout lifetimes or generations. The reason for this is that, unlike cross-sectional studies, in which different individuals with same characteristics are compared,[1] longitudinal studies track the same people, and therefore the differences observed in those people are less likely to be the result of cultural differences across generations. Because of this benefit, longitudinal studies make observing changes more accurate, and they are applied in various other fields. In medicine, the design is used to uncover predictors of certain diseases. A retrospective study is a longitudinal study that looks back in time.

Examples[edit] See also[edit] GOV.org - Publications: Research and analysis. SEO services, PPC management and Web analytics consulting by ivantage. A Framework for Analysis of Data Quality Research. Creating a Data Management Framework. Who should read this? This guide is for research institutions which are intending to improve their infrastructure to support data management. Background Good research data management practices ensure that researchers and institutions are able to meet their obligations to funders, improve the efficiency of research, and make data available for sharing, validation and re-use. To support these goals, it is imperative that research data management is done properly from the outset; through the stages of planning, collection, analysis, publication, archiving and later re-use. Good data management depends on a number of players.

Good data management is integral to the development of the Australian Research Data Commons. Principles The Data Management Framework is underpinned by a number of principles: The Data Management Framework The Framework as set out below outlines the basic elements required within an institutional context to support effective data management. Data Quality and Data Quality Assurance Policy, Planning and Resource Allocation. Purpose 1. The University needs timely, accurate and reliable data in order to manage activities and meet internal and external requirements to demonstrate accountability through accurate reporting. 2. Specifically the University needs to ensure its data quality so that it can: Provide effective and efficient services to students, staff and other stakeholders.

Scope 3. 4. Responsibility for Data Quality and Data Quality Assurance Audit and Scrutiny Committee 5. The Code states: "…we are seeking assurances from designated officers and audit committees about the management and quality assurance arrangements for data submitted to the Higher Education Statistics Agency (HESA), HEFCE and other funding bodies. HEFCE's guidance to audit committees on how they need to reach the required opinion on data quality states that the committee 'needs to be sure that management has assessed the risks posed by data accuracy and taken appropriate mitigating actions'. Data Assurance Group 6. 7.

Risk 8. Quality Data.