Doing Research

tekijä: Tanja Tuulikki Välisalo Viimeisin muutos tiistai 09. maaliskuuta 2010, 15.02

 

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Having compiled your work plan and work schedule and written up your research plan at the end of the second stage, now you need to put the plan into practice.

We suggest that you will often find the act of collecting and analysing your research data to be the most time consuming activities in the entire research process. During this stage, you initially collect the empirical data and then carry out the data analysis, both according to your research plan. We advise that you do not deviate from your research plan until you have unexpected and unexplainable results. Nevertheless, data collection and analysis often produce ideas and points of views, which you had not included during the planning stage of the research. If this happens in your research, you need to revise your research plan. Once you have completed the data analysis you can start making conclusions and interpretations on the basis of the analysis. These conclusions and interpretations answer your research questions and give a summary of the ideas and observations of your researched phenomena.

Your aim is to use reasoning to present your argumentation to the readers in a convincing manner. The reliability of your research depends on the quality of your research and the validity of your conclusions. Other researchers will evaluate the reliability of your research throughout the research process. The concepts of reliability and validity are central to their evaluations. Consequently, you should present your argumentation both clearly and logically. You may use one of a variety of modes of reasoning to present your argumentation (inductive, deductive, abductive or analogic).

Essential phases of this research stage are: 

 

Data collection

Data is the basis of empirical scientific research. The data may consist of already existing materials or your research can produce the data. If you decide to collect existing materials, you may need initially to investigate where the materials are located and whether or not the materials are retrievable for your research purposes. Existing materials can be, for example, books, pictures, documents, letters and media texts. Existing data consists of data, which other researchers or organisations have collected. If you decide to produce your own data during the research process, the collection methods need careful planning. You need to understand the correlation between the systematic aspect as well as the quantity of the data and whether the data will answer your research questions. Some topics will enable you to collect plenty of data. In this case, you need to decide on the basis of the extent and depth of the aims of your research how you will reduce the quantity. If your intention is to do statistical analysis, you must have systematic and coherent data. In collecting data you also need to be aware of your own skills, and that some kinds of data are more difficult to collect than others.

For detailed information on data collection. 

 

Data analysis

In scientific research, data is analyzed in a way, which produces scientifically valid arguments. The research problem and the aims of the research will influence your choice of data analysis method. If you are seeking answers for certain kinds of research questions, you will need to choose particular kinds of data analysis methods. Other factors that will influence your choice of methods of analysis are:

  • Your personal analysis skills
  • Discipline specific methods of analysis
  • Popular versus traditional versus out-of-date methods of analysis
  • The type of data

You are not limited to using existing methods of analysis. You are free to combine contemporary methods to form a new method of your own devising or even devise a completely new method. Whichever method or methods of analysis you chose, you need to present an argument for their use in your research. 

For detailed information on data analysis.  

 

Making conclusions and interpretations

Describing and presenting your analysis of your data in the research report does not reveal the results of your research. You still have to make conclusions and interpretations based on your analysis of the researched topic. An essential factor you need to keep in mind, when making conclusions and interpretations, is to understand and present their connections to the research literature and previous research results. In the conclusions and interpretations you present the actual results of your research, i.e. they answer the research questions and provide a summary of the core ideas of the researched problem. You must present your conclusions and interpretations as a reasoned argument in the research report. How you present your conclusions and interpretations depends on your aims of research.

If you have used quantitative (particularly statistical) methods of analysis in a research project using an experiment, you may express the conclusions and interpretations as exact statements. If you have used qualitative methods of analysis in a research project based examination of concrete archive materials, i.e. history research, you may express your conclusions or interpretations as discursive summaries of central themes or phenomena observed during the research process.

Links to more information:

Shuttleworth, Martyn, 2008. Drawing Conclusions. Experiment Resources.

 

Reasoning

In scientific research, various modes of reasoning form the basis of the production of new knowledge. Your aim is to use reasoning to present your argumentation to the readers in a convincing manner. The reliability of your research depends on the quality of your research and the validity of your conclusions. Other researchers will evaluate the reliability of your research throughout the research process. The concepts of reliability and validity are central to their evaluations. Consequently, you should present your argumentation both clearly and logically.

You may use one of a variety of modes of reasoning to present your argumentation:

Inductive – observations of the researched phenomenon produce a generalisation or theory.

Deductive – a generalisation or theory produces new knowledge of the researched phenomenon

Abductive – rationality and probability, from the available evidence, form the best possible explanation of the researched phenomenon.

Analogic – a coherent and logical explanation of a similar phenomenon produces knowledge of the research phenomenon.

Links to more information: 

Reasoning. Wikipedia, The Free Encyclopedia.

Trochim, William M., 2006. Deduction & Induction. Research Methods Knowledge Base, 2nd Edition.

 

Reliability and validity of the research

The concepts of reliability and validity are central in the evaluation of the research. Reliability refers to consistency of the analysis and repeatability of the measuring results. Validity refers to the evaluation of the analysis indicators: they have to measure those factors which they are supposed to measure. The reliability of your research depends on the quality of your research and the validity of your conclusions. The total reliability of your research will be evaluated throughout the whole research process. One way to increase the reliability of your research is to use various types of data and different theories, points of views and methods of analysis. This practice is called triangulation. The aim of using triangulation is to prove that the results are not random, i.e. you can obtain the same results from a variety of methods. You need to bear in mind that triangulation is not suited to those qualitative research methods, which stress the significance of the subject in the production of knowledge. Nevertheless, the results of qualitative based research cannot be random. You can evaluate the validity of your qualitative research in several ways of which the most relevant are generalisation and transferability.

Links to more information:

Reliability (Statistics). Wikipedia, The Free Encyclopedia.

Validity (Statistics). Wikipedia, The Free Encyclopedia.

Trochim, William M., 2006. Reliability. Research Methods Knowledge Base, 2nd Edition.

Colosi, Laura A., 1997. Reliability and Validity: What´s the Difference? The Layman´s Guide to Social Research Methods.

Shuttleworth, Martyn, 2008. Validity and Reliability. Experiment Resources.