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Guide to undergraduate dissertations in the social sciences

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The data sets used for secondary analysis may be out-of-date, which makes them inappropriate for the current research project. For example, a researcher could not write a paper about today's political climate by using data collected in Also, the original research may not have been conducted rigorously and may have uncontrolled biases. Many public agencies collect data regularly that can be used for secondary research. The United States Census Bureau provides social and population data of the entire country every ten years with interim data collection in non-census years.

This data is available for free use or for a nominal fee. Private companies and universities are also considered good sources of existing data for secondary research. Many university professors collect data for research projects and may make their data sets available for secondary research. This data can be free or very expensive depending on the size of the data set and the source.

Many Internet search engines and websites collect data about user behavior. This is sometimes sold to market research agencies for secondary analysis or targeted advertising. This way, many people are involved in research projects without being aware. Users can check out a website's privacy policy if they are concerned about data collection. One of our editors will review your suggestion and make changes if warranted.

Note that depending on the number of suggestions we receive, this can take anywhere from a few hours to a few days. Information was arranged into mood boards for analysis. These findings led to a search for a new approach to the campaign that could make the Fall Winter ad unique. A brainstorming process was used once again and a final campaign evolved that met the expectations of stakeholders.

The company used a 14 years old fashion icon to be the face of the brand and the photo shot was done in a home setting, with the model doing ordinary things instead of posing in front of the camera.

Without the process of secondary research, the campaign would have likely had outcomes similar to their previous work. The Market Research Toolbox: A Concise Guide for Beginners, 3rd Edition. Thuy Linh Do Edited by Christine Keene Overview Secondary Research is a common research method; it involves using information that others have gathered through primary research. Assess easy, low-cost and quick knowledge; Clarify the research question; Help align the focus of primary research in a larger scale and can also help to identify the answer; and Rule out potentially irrelevant project proposals ex.

The proposed work may have already been carried out. Goes By This technique is also known as Desk Research. Variations There are two types of Secondary Research hence two types of data collected from this technique: Each Secondary Research process involves 4 steps that can be repeated as necessary: Identifying the subject domain and where to acquire the information; Gathering existing data; Comparing data from different sources, if necessary and if feasible; and Analyzing the data 1. Dissertations can be based on either quantitative or qualitative data, or on a combination of both.

How you choose this may depend on your preferences and abilities, and the suitability of particular approaches to your topic. You need to be able to justify why you have chosen to use such data. Quantitative data is particularly useful when you wish to discover how common particular forms of behaviour such as illegal drug use are for a particular age group. Qualitative data is particularly useful when you wish to find out why people engage in such behaviour. Think about the Research Methods modules you have taken so far.

Think about the different kinds of studies you have read for other modules. There is plenty of scope to use the approaches and methods that you are most comfortable with. You need to justify your approach and methods and to cite appropriate literature to help you do this.

You will probably want to use large datasets and undertake quantitative data analysis, and you will be adopting a realist approach to the topic studied. Quantitative dissertations are likely to be nearer to the lower end of the range of approved lengths for the dissertation e. They will also include tables and figures giving your important findings. Remember that all tables must be carefully titled and labelled and that sources of your data must be acknowledged.

You will probably want to use in-depth qualitative data, and you may wish to adopt a realist, a phenomenologist, or a constructionist approach to the topic. Qualitative dissertations will include descriptive material, usually extracts from interviews, conversations, documents or field notes, and are therefore likely to be nearer to the upper limit of your word range e.

The types of method suitable for a dissertation could include content analysis, a small scale ethnographic study, small scale in-depth qualitative interviewing. There are many ways in which qualitative and quantitative data and analysis can be combined. Here are two examples. Your supervisor or research methods tutor may be able to give you detailed examples of these or other ways to combine methods.

If you decide to do a primarily theoretical dissertation, it is almost certain that your dissertation will be entirely literature-based. This is likely to be the methodology of theoretical analysis: You might ask how useful certain concepts or theories are for understanding particular patterns of behaviour.

How useful is the concept of institutional racism? Is objectivity in the media possible? How useful is subcultural theory for understanding virtual communities? Here, the focus of attention is not so much to discover something about the social world, for example virtual communities, as to reach a judgement about the value of key concepts or theories in understanding that world. How the study is approached and how contrasting approaches are drawn upon needs to be stated very clearly.

A library-based or theoretical study is not necessarily 'easier' than an empirical study, indeed, it may well be harder. Remember that theoretical studies, like data-based studies, need to have their research design spelled out from the start. But even if your dissertation is more empirically focused, it could still be entirely literature-based. You might choose to conduct a review of a field of work. What does the research literature in this field tell us about x? While all dissertations will include a literature review, it is possible to produce a dissertation that is entirely based on a review of the literature.

If you do this, it is important to review the literature from an explicit angle and identify some themes to make the review distinctive. You might, for example, explore empirical debates in your chosen field across different countries or time periods. Whilst it is possible for dissertations to be entirely literature-based, the most common form of dissertation takes the form of a case study.

Here the focus of attention is on a particular community, organisation or set of documents. The attraction of this kind of dissertation is that it stems from empirical curiosity but is at the same time practical. You may be interested in a wider question but a case study enables you to focus on a specific example. A major challenge in case study dissertations is connecting your own primary research or re-analysis with the broader theoretical themes and empirical concerns of the existing literature.

Most dissertations demand either primary or secondary research. In other words, you usually have to analyse data that you have either collected yourself or data that is already available.

The reason for this is that the questions dissertations usually address take the following form: Why is x happening? Why is x changing? These questions demand primary or secondary analysis of data. Case Study 9 Think hard before you decide to undertake empirical research: Secondary analysis is when you analyse data which was collected by another researcher. It allows the researcher to explore areas of interest without having to go through the process of collecting data themselves in the field.

The problem with using fieldwork methods in an undergraduate dissertation, however, is that they are costly in terms of time which is relatively scarce in your final year! You may choose, therefore, to undertake secondary research, analysing existing data.

There are a range of documents that already contain research data that you can analyse. You may, for example, be interested in exploring whether gender stereotypes in the media are changing. This might entail content analysis of newspapers, magazines, video or other media over different time periods.

Here you would not be collecting your own data but instead would be analysing existing documents. Download Case Study 6 Media research. If you are interested, for example, in doing historical research, you may need to visit archives. Government reports and autobiographies may also be used as data. Other documents include official statistics, datasets statistical data , and banks of interview transcripts which are all freely available to the academic community.

Increasingly, documents, databases and archives are readily accessible online. Research Methods tutors on your course will be able to advise on the availability and accessibility of such data sets. There are some advantages of doing secondary analysis, particularly if you are doing a quantitative study. You will be able to work with much larger datasets than you could have collected yourself.

This has the following advantages:. Quantitative data may also result from non-participant observations or other measurements e. Also, sometimes data that are collected through qualitative processes participant observation, interviews are coded and quantified. Your research methods tutor can give you further information on these types of data, but here are some common quantitative data collection methods and their definitions:.

A series of questions that the respondent answers on their own. Self-completion questionnaires are good for collecting data on relatively simple topics, and for gaining a general overview of an issue. Questionnaires need to have clear questions, an easy to follow design, and not be too long. Similar to a self-completion questionnaire, except that the questions that are asked by an interviewer to the interviewee. The same questions are read out in the same way to all respondents.

There will typically be a fixed choice of answers for the respondents.


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Most research requires the collection of primary data (data that you collect at first hand), and this is what students concentrate on. Unfortunately, many research reports do not include secondary data in their findings section although it is perfectly acceptable to do so, providing you have analyzed it.

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Secondary Research is of value when information is compared and analyzed, when the researcher performs a critical review of the data, and when the researcher comes up with actionable findings to move the project forward.

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Data collection is a process of collecting information from all the relevant sources to find answers to the research problem, test the hypothesis and evaluate the outcomes. Data collection methods can be divided into two categories: secondary methods of data collection and primary methods of data collection. that secondary data analysis is a viable method to utilize in the process of inquiry when a systematic procedure is followed and presents an illustrative research application utilizing secondary data analysis in library and information science research.

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Quantitative secondary research is much more common than qualitative secondary research. However, this is not to say that you cannot use qualitative secondary data in your research project. This type of secondary data is used when you want the previously-collected . Secondary data analysis, on the other hand, is the use of data that was collected by someone else for some other considerableaps.tk this case, the researcher poses questions that are addressed through the analysis of a data set that they were not involved in collecting.