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Advice about empirical research and secondary (library based) research

Developed from a web file compiled by Alison Britton (1996) and reshaped in the light of the other sources indicated

Stages of a research project

We will think of a research as having the following logical stages. These stages are not, however, separate in practice. You should begin thinking about the last stage as soon as soon as you start on the first.
  1. Stage one: Planning and framing issues
  2. Stage two: Gathering and recording
  3. Stage three: Analysing the information
  4. Stage four: Writing and Sharing

Planning and framing issues:

Choosing a topic and grounding your research
Forming a research statement
Generating Ideas Story telling
Preliminary Reading
Research Proposal
Pilot Study
Indicators - Relating your ideas to the empirical world

Gathering and Recording Information

Keeping records
Secondary and Primary Data
Methods of Collecting Data

Analysing (Interpreting) Information

Coding Data
Analysing Data

Writing Up and Publishing

Sharing (Publishing)
Writing a Report

Planning and framing issues

Framing a research project means devising the parts that will give it its structure and purpose. It includes
choosing a topic and forming the question. Setting out the aims and the objectives of the project. Working out a timetable for the project. And, possibly, developing a formal Research Proposal It could also include a pilot study.

Choosing a topic and grounding your research

The first thing that you must do is to choose the topic you want to research. You may be given a list of suitable subjects. Or you may be left to choose your own.

You will want to ground your ideas in any work that has already been done: To relate your ideas to other people's ideas. Carole Adams says in a course handbook:

"..on most research topics there is already a body of knowledge in existence, which researchers must, as part of the research process, search for, secure and evaluate." (See preliminary reading)

Howard and Sharp say research is:

The point they are making is that you should try to tackle an issue that needs to be tackled, and where results might have some significance.

You may want to start by choosing a general area in which you are interested. Maybe you have several possible ideas. Write them all down. Do not reject any ideas at this point.

To get your ideas moving on the areas, consider all the aspects of each that might be relevant. Think about the issues, talk to people, read around the subject and write something about them.

Preliminary Reading

To get an idea of what kind of project is practical you will almost certainly need to read and talk with people. For ideas and to gain focus, try some or all of the following:

Reading Notes

Your preliminary reading will not only be useful for choosing your topic. You will need to go back to some of the same sources to do a Literature Review for your project. So keep careful notes at every stage.

Your reading notes can include article summaries from Abstracts If you are using a computerized bibliographic source, you might be able to transfer information to your own disk or print it out there and then. Do not expect to remember what you have searched and where you found things. It is very easy to forget.

Label your notes so that somebody else could read and understand them. This should mean that you, too, understand them when you reread them.

Forming the question
Forming a Research Statement

A research statement turns your
original ideas into something that can be researched. It may be a statement or a question. It is not necessarily the title of the project, but rather the topic or problem on which you will focus.
An example research statement might be:

    The research will be an investigation into the design of a Personal Development Portfolio for clerical and managerial staff. It will look at what the staff think the portfolio will be is used for, establish the cost of setting it up, and make recommendations.
When you have drafted a research statement it is sensible to carry out a short investigation to see if there will be enough information for you to work with. If the sources seem deficient, you could reword your research statement, or even change the topic.

You should avoid making your topic so broad that it does not allow you to do anything well, and you should avoid making it so narrow that it will not provide enough material for research.

Be clear about what is required. What should the project look like when it is finished? It is important that when you present a project you meet all the requirements.

Your Research Proposal must not be something you do and forget. It guides you through your work and can eventually be adapted to form part of the introduction to the written report on your work. Research proposals, like essay plans, are altered as the work progresses. As you read in the field, your work will take on more focus and what you intend to do will change. You should start with a clear plan, and change it when you need to. It is sensible to consult your supervisor about changes in your research plan.

Developing a Research Proposal or Research Outline

A research proposal helps you focus your ideas. That means bringing them to a point. We start with rather hazy, general ideas and in developing a research proposal, we make them much more useful.

Sometimes you will be required to develop a formal research proposal - But, required or not, it is something you will need to do.

A research proposal will usually contain:

  • a proposed title

    It was very helpful when teachers provided you with essay titles to focus on. Now you have to do the work of deciding what to focus on. Your title is your main focus, and you should keep it in mind throughout your research

  • the project's aim or your hypothesis

    A hypothesis is a tentative statement of what you think you are likely to find out in your research.

  • the questions you need to answer

  • your methodology and

  • the time scale in which you propose to carry out the work.

    A research proposal describes what the researcher intends to do. The description should be clear enough that a competent reader would be able to do roughly the same, just on the basis of the description.

    To start forming a research proposal, consider your topic, research statement and project ideas. How are you going to approach the topic?

    Ask yourself relevant questions beginning 'Who' 'What' 'Where' 'When' 'Why' and 'How?'.

    You need to be very clear in your own mind about what you plan to investigate, and how you plan to go about it. Without a clear plan you are in danger of collecting a quantity of data, but of having little idea what to do with it.

    Then consider your sources of information: books, journals, pamphlets, videos, people. Consider your methodology: interviews, questionnaires, observations, experimentation . . .

    But do not produce a plan that's too complex to be summarised on one side of paper.

    The form of a proposal, and of the project itself, varies.

    Experimental work in the sciences and social sciences is usually clearer if it follows the standard set of headings for laboratory reports and journal articles, and for a general idea of how to structure your work, you might find it helpful to look at journal articles in your field.

    A good way to organise a proposal is to use the categories as the project itself, (with some commonsense differences), using some of the standard Parts of a Report.

    There should be a proposed title or an initial short statement about what you intend to do, if you have not come up with a title.

    The introduction will be more sketchy than in the later report. But it should explain the following: Why are you doing this work? (What is your aim?) What problem are you wanting to investigate? What questions will you ask? What other research is relevant to your work? Description of your methodology materials, etc. may be tentative at this stage as you may not have made a final decision about your methods. But you may describe a range of possibilities.

    There will be no results unless you have done some brief trial or pilot work, but it is helpful to indicate any expectations you have concerning the results (any hypothesis) and how you will analyse the information you collect.

    Likewise, although you cannot have a discussion of results you do not have, you could give some ideas of how you plan to interpret and discuss various possible results.

    A proposal could also include a rough timetable of when you plan to carry out different stages of the work.

    Timetable your Research and Report

    You have to be able carry out your research and write it up by the deadline.

    Basic time management skills may be even more relevant here than in other aspects of study. At the start of your research period you must already know exactly when your project is due. Using that, construct a timetable, working backwards, with plenty of time for writing up.

    Do not underestimate the time needed for writing up and finishing your report. As well as planning extra time for unforseen problems, allow time for feedback on your draft (from a tutor, for example) and for revising it. If the report has to be bound, know how this is done, and allow time for that. Also take into account the extra pressure on your time if writing up the report coincides with exams and the completion of your other assessments.

    You will save a lot of time by being very clear about the format your research report should take. Usually, much of your report will not depend on the research findings. All these parts should be drafted in advance so that the research findings can be slotted in when you have them.

    In preparing your research plan, allow for unexpected delays and setbacks. You are cooperating with other human beings who will not usually attach the same importance to what you are doing as you do.

    If possible, use a pilot study to anticipate and avoid problems in the research

    There are special problems about timetabling research which are only learnt by experience. If this is your first piece of research, you will not have had that experience, so take what opportunities you have to discuss with experienced researchers in your field their tricks and techniques for finishing on time.

    Pilot study

    A pilot is a test run of something to see how it works before you commit yourself to the full version. If you can allow the time, it is an excellent idea to carry out a small Pilot Study. That is, collect and analyse a small amount of data before you start to collect your main data. It is best to discover any obvious problems with your methods right at the start.

    It is particularly important to pilot questionnaires and interviews before you start your proper research. You should get several people to complete the questionnaire to see whether they are able to understand and answer the questions. Similary you should cary out at least one interview, where you can also get an idea of how much time the interviews might take.

    Indicators - Relating your ideas to the empirical world

    The ideas that we use for our theories cannot just be applied to the empirical world. We need to convert the concepts in the theories to things we will use as indicators of those concepts.

    Julie Ford gives this example:

    "Let us suppose that you have a theory from which you have derived the hypothesis that academic success amongst sociology students increases with political involvement" Ford, J. 1975, p.173)

    The hypothesis seems clear enough: The more politically involved your sociology students, the more you expect them to be academically successful.

    The things that change are called variables. So the variables in this hypothesis are political involvement and academic success. You have to decide what you will use as the indicator of these variables. Here are two simple possibilities:

    variable indicator
    political involvement membership of one of a list that you make of political groups
    academic success grades in specified examinations

    In Dr Webley's chemical analysis, the quantity of phosphorus (a measurable element) is used as an indicator of the "purity" of a sample

    We want our indicators to be valid and reliable

    By valid is meant that it is a good indicator of what we want to count or measure. For example, you want to count the number of people who are working class and the number who are not. Would how much each earns be a good indicator? Or, perhaps we should ask how good an indicator it would be. - [See crime statistics example]

    "An observation is valid if one has observed what one wants to observe" Johan Galtung 1967 p.29

    Are unstructured interviews more valid
    and structured ones more reliable (see below)?

    By reliable is meant that the indicator produces results that do not vary in an irrelevant way. For example: You might put coins in piles of tens and then check that there are ten in each pile by measuring the height of the pile. This is reliable if all the coins are the same thickness. If some are thinner than others, it is not reliable. [See crime statistics example]

    Devising empirical indicators that are valid and reliable for the concepts in a hypothesis is called operationalisation or operationalising concepts - because it makes the hypothesis operational or ready to be used. Emphasising the difficulty of doing this, Julie Ford compares it to building a rope bridge across a chasm between the world of ideas and the world of observation (which she also calls "the world of appearances"). (Ford, J. 1975, chapter 8)

    Are these valid and reliable indicators of crime and class?

    See National Archives

    Have a look at an early (1845) effort to use crime statistics. Here, Engels wants to know what proportion of crimes are committed by working class (proletarian) people. Unfortunately, the Home Office has not coded its data by class. It has noted what proportion of criminals can read and write. Engels takes not being able to read and write as an indicator of being proletarian.

    1) How good (valid) do you think this indicator? Is it the best he has?

    2) Would it be reliable over time? For example, could you use it on statistics from 1845 and 1945 to see what proportion of crimes were committed by working class people? [Education of the working class would make the results vary in an irrelevant way. The changes being measured would be more education than class]

    What indicators would you use for ethnicity?

    In the United Kingdom's National DNA Database, samples are categorised for ethnicity on "the operational judgement of the arresting officer" into Arabic or North African - Asian - Black - Chinese - Japanese or other South East Asian - White North European - White South European.

    How valid and reliable would you consider this procedure?

    The Annual Report for 2007/2009 said:

    "The information which accompanies the subject profile loaded onto the NDNAD holds very little information about a subject's identity - only their name, date of birth, gender and ethnic appearance; the latter is determined by the police officer who took the sample, consequently this is not the same as ethnicity"

    But do you think "ethnic appearance" is an indicator of ethnicity? - See ethnic statistics and indicators for alternatives.

    What would indicate an evangelical or a utilitarian?

    An example of the difficulty and the importance of indicators is given by thinking about the concept Evangelical which occurs in many English history books. People researching 19th century organisations often look for the evangelical and utilitarian influences on it. How could you possibly measure that? One way might be to see if you could count the number of people in the management of the organisation who could be called evangelical (or utilitarian). If this is what you decide to do, how do you identify them? Many historians seem just to rummage around for anything that might indicate. This might include a) someone else saying the person was an evangelical, b) the person going to church, c) the person belonging to a religious group, d) the person belonging to an organisation whose membership was restricted to Evangelicals, or meant for Evangelicals. If the historian states what his or her indicators are, this gives others the opportunity to evaluate whether the indicator really indicates the concept (what do you think of the above ones?) and to see clearly the basis on which any data is constructed. In practice, historians rarely provide their indicators, so little meaning can be attached to statements such as "several of the leading members were Evangelicals".

    One indicator I suggested when analysing the biographies of members of the 19th century Lunacy Commission was membership of the Church Missionary Society. Follow the links and think about the advantages and disadvantages of this as indicator.

    Gathering and Recording Information

    The stage of your research in which you collect and record data information is sometimes called the research stage. The information you collect is called your
    data. This stage includes devising techniques to record data, especially primary data, choosing the method for collecting data and carrying out the collection within the timetable you decided on.

    Keeping Records

    You will need to create your own system for recording and storing information as soon as you start your research. Record keeping skills for empirical research are built on the record keeping skills you have developed in your general studies, but the material you need to record is considerably greater.

    You will need a method of :

    You will almost certainly need a system that has clear, separate, records, rather than a continuous flow of recording. An example of a separate data record might be the written record or tape of an interview or a completed questionnaire. You will need a system of labelling these records.

    You could devise your own form and make copies.

    You could use index cards (which come in different sizes)

    You could record the data in computer files.

    Using separate forms or cards, or using computer files, will make it easier to organise your data than if it were written continuously in a notebook.

    If you use index cards, it is best to make only one point on each card and to use only one side of the card. This gives you maximum flexibility sorting the information. You can move it around and regroup it under different topics and questions. When you write up your research, you can organise your data for each section that you have to write.

    Recording the Source

    In addition to the relevant quotations and the information and ideas that your research has uncovered you must record the source.

    Note everything you read, being careful to record all the details you will need for referencing the source if you refer to it in your report.

    For books the information you will need for referencing is:
      name of author(s) (surname and first initial)
      date of publication
      place of publication and publisher
      page number
    For data you collect you will need to devise a system of relevant details to identify each source. In the case of an interview, these might be: the name of the interviewee, and the date and place of the interview. For a visit, these might be the place and date and context of the observation, and so on.

    Labelling and Categorising Data

    You will have different kinds of data, and it may help if you organise the different kinds according to where you will be using each. Data needed for a literature review, for example, is different from the Data Records you will be analysing to produce results. These are distinct from the notes you will be using in your discussion and your drafts of your conclusion.

    When you are reading, photocopy or copy out quotations as well as information. When you are writing up your report you do not want to spend a lot of time searching for quotations you noticed as you were reading, but did not record.

    You need to label each Data Record. For a simple example, consider data records that are completed questionnaires on single sheets. You need the total number of questionnaires, a way of identifying each sheet, and a label to help you avoid confusion as your are coding the data. All these purposes could be served by numbering the sheets somewhere distinct, like the top right hand corner.

    You will need to categorise your data for analysis. You may do this by labelling the data. As a simple example, Data Records about spelling might be labelled "good", "average", or "poor".

    In some case the data will have been pre-categorised (by a tightly constrained questionnaire for example). Often, however, you will need to draft a system of categories when you start researching and modify it as you go along. Doing this kind of labelling in pencil will make it easier to recategorize if the categories prove unsuitable.

    Ethical principles

    Research ethics usually apply to the moral rights and wrongs of how you relate to people you interview, give questionnaires to, or include in experiments. They can also apply to how you relate to the academic community.

    The first set of ethical issues mainly relates to primary research, but how you relate to the academic community relates to primary and secondary research.

    A good way to learn about research ethics is to study some of the documents created to guide researchers such as the European The RESPECT Code of Practice and codes compiled by bodies like the Social Research Association - British Sociological Association - British Society of Criminology, - and think about how they might apply to what you do. I have included some extracts that you might find particularly useful - But the full text will be found by following the links.

    With respect to secondary research, The RESPECT Code of Practice is particularly useful.

    With respect to primary research, these are some simple rules of thumb that one researcher drew up.

    If you are interviewing, be sure that your interviewees are happy to talk with you. Do not demand too much of their time.

    If necessary, clear the interview with their 'superiors'.

    With the people whom you are observing or interviewing be clear about what will happen with the data you collect. Assure them that what they tell you will be kept anonymous and confidential.

    The RESPECT Code of Practice


    The RESPECT project was funded by the European Commission's Information Society Technologies (IST) Programme, to draw up professional and ethical guidelines for the conduct of socio-economic research.

    The RESPECT code is based on three main principles:

    1 Upholding scientific standards

    2 Compliance with the law

    3 Avoidance of social and personal harm.

    The first main principle is equally relevant to secondary or primary research. The third is particularly relevant to primary research.

    Points made with respect to upholding scientific standards include endeavouring to

  • ensure factual accuracy and avoid misrepresentation, fabrication, suppression or misinterpretation of data

  • take account of other people's research, including research that challenges your own results

  • acknowledge fully any debts to previous research as a source of knowledge, data, concepts and methodology

  • make sure that your research questions and conceptualisation do not predetermine the outcome of your research

  • Do not exclude unwanted findings

  • demonstrate an awareness of the limitations of the research, including the ways in which your characteristics or values may have influenced the research process and outcomes.

  • Report fully on your methodologies and the results you obtained

  • When reporting survey results say when and where the survey was carried out and features like sample size and the number of non-responses and probability of error.

  • ensure methodology and findings are open for discussion and that other people can check them (full peer review)

  • ensure that research findings are reported truthfully, accurately, comprehensively and without distortion.

  • In order to avoid misinterpretation of findings and misunderstandings, researchers have a duty to seek the greatest possible clarity of language when imparting research results.

    Social Research Association Ethical Guidelines

    At http://the-sra.org.uk/wp-content/uploads/ethics03.pdf

    These include:

    "3.2 Exposing and reviewing their methods and findings

    Within the limits of confidentiality requirements social researchers should provide adequate information about their methods to colleagues to permit procedures, techniques and findings to be assessed by others."

    Statement of ethical practice. British Sociological Association

    At: http://www.britsoc.co.uk/about/equality/statement-of-ethical-practice.aspx

    This includes:

    "16) As far as possible participation in sociological research should be based on the freely given informed consent of those studied. This implies a responsibility on the sociologist to explain in appropriate detail, and in terms meaningful to participants, what the research is about, who is undertaking and financing it, why it is being undertaken, and how it is to be disseminated and used"

    "18) Research participants should understand how far they will be afforded anonymity and confidentiality and should be able to reject the use of data-gathering devices such as tape recorders and video cameras."

    British Society of Criminology's Code of Ethics for Researchers in the Field of Criminology

    At http://www.britsoccrim.org/docs/CodeofEthics.pdf

    Practical situations that present an ethical dilemma are discussed in a "Frequently asked questions section" at the end. These include

    Q2: "I've been doing some focus group discussions with school children about their views on crime and punishment. In a small group of ten year olds one day, they started talking about a man called John who gives them sweets at the gate of the school. There was a lot of hushing and shushing and exchanged glances at this point, and it became clear that I was being told something I wasn't meant to hear because of their parents. What should I do?"

    A2: The welfare of vulnerable participants in research, such as children, overrides other concerns. See sections 4i and 4iii of the Code of Ethics. Research with children should only be undertaken by people who have themselves been cleared for the purpose by the Criminal Records Bureau. If research uncovers suspected child abuse, this must be disclosed to the proper authorities for investigation. In this case, the suspicion is vague but valid: the researcher should inform a senior staff member at the school of what was said.

    Types of research

    Theoretical - Secondary - Primary

    Theoretical research

    Theoretical research is focused on theory rather than data. Wendy Maycraft Kall, for example, says on page 27 of The Governance Gap: Central-local steering and mental health reform in Britain and Sweden (2011) that the objective her thesis is "theory development" and not "theory testing"

    Secondary and Primary Resarch

    Secondary and Primary Data

    Secondary data is data collected by someone else.
    Secondary methodology draws its information from the existing literature.
    Secondary research is research based on exploring other people's research. Other terms for secondary research are documentary research - Library Research and Desktop Research.
    Secondary analysis is the re-analyis of data

    They are contrasted with primary data and research.

    Even if your research is based on original (primary) data you collect yourself, you must also be familiar with secondary sources. You need to read the important things that have been written about the area that you are researching and you may be required to write a review of the literature on the topic.

    Data that is secondary for some research may be primary for other kinds of research. The following sources would be secondary for most research.

    You will certainly read some of the following:

      Books, encyclopedias, newspapers, journals, magazines, conference proceedings, and reports.
    You might also need to look at unpublished sources, such as
      Letters, documents, memos, files, minutes of meetings etc. and unpublished dissertations.
    The lists are not complete. What you need to read will be much influenced by the subject you are studying. You may, for example, need to use sources such as
      Films, photographs, videos, radio recordings...
    For media studies and historical research some of the sources listed above could be primary data. Newspapers, magazines, letters, documents, films and radio recordings, for example, could all be primary data for the historian.

    Secondary Analysis

    Secondary analysis of statistical data and qualitative data

    The data produced by other people's surveys is shared in various ways, including through archives such as the UK Data Archive. If this data is re-analysed, it is called Secondary Analysis.

    Secondary analysis is defined by Bryman as

    "the analysis of data by researchers who will probably not have been involved in the collection of those data for purposes that may not have been envisaged by those responsible for the data" (Bryman, A. 2008, p.698).

    Student dissertations do not often re-analyse quantitative or qualitative data sets collected by other people such as those in the UK Data Archive. They do, frequently, analyse what has been written about a topic, including the data presented. In this sense, they may be called secondary research. However, it may be clearer to describe dissertations that do not report primary research as Documentary Research

    Primary data

    Primary Data is original information that you gather yourself.
    Methods of collecting primary data include Questionnaires - Interviews - Fieldwork - Focus groups

    For many topics a great deal of secondary data will already exist. You may need to be selective about which secondary sources you consult and what primary data you collect.

    For other topics there may be very little published data and therefore you will need to follow up every lead to secondary findings, and be inventive in producing your own data.

    It is essential that you establish a good routine way to keep records of all the data you collect.

    Methods of Collecting Data

    A research method is a systematic plan for conducting research.
    Macionis, J. and Plummer, K. 1998 p.42)

    There are many different ways of collecting data. Which method or combination of methods you use will depend upon your subject area. These are some of the terms used to describe different methods.

    The method(s) that you use will depend upon the topic you choose and your subject discipline.

    Qualitative Data and
    Quantitative Data
    Qualitative data is data that is mainly words, sounds or images.

    Qualitative Research Methods include participant observation - in-depth interviews - and focus groups

    See Research and QualitativeResearch subject indexes

    Quantitative Data

    Quantitative data is data that is mainly numbers. Quantitative research in the social sciences is mainly statistical. See statistics

    See Research and Quantitative Research subject indexes

    Mixed methods

    Mixed methods are research methods that use both qualitative and quantitative data

    See Research and Mixed Methods subject indexes

    Structured and Unstructured Data Structured data is organised, unstructured data is relatively disorganised. Structured data can be produced by closed questions, unstructured data can be produced by open questions.

    Closed questions can make analysing the data relatively easy, but they restrict the responses. For example, on many courses students are given a standard list of features (e.g. lectures, books, assessment, tutorial support) and asked to indicate on a
    five point scale how satisfied or dissatisfied they are with the feature. These are highly structured (precoded) closed questions.

    The same form may have a space for the student to make any comments he or she wishes to make on the course. This is an open question which will produce almost completely unstructured data. Although the open question produces data that is difficult to organise and code, it allows subjects to respond freely and express shades of opinion rather than forcing them to have precoded opinions.

    Questionnaires and Surveys:

    A questionnaire is a series of written questions a researcher supplies to subjects, requesting their response. Usually the questionnaire is self-administered in that it is posted to the subjects, asking them to complete it and post it back. (
    Macionis, J. and Plummer, K. 1998 p.44)

    The way you will be analysing the data may influence the layout of the questionnaire. For example, closed questions provide boxes for the respondent to tick (giving easily coded information), whereas an open question provides or a box for the respondent to write answers in (giving more freedom of information, but more difficulty coding).

    Questionnaire design should bear in mind who your respondents will be, and what personal details you need to know about them. Keep your questionnaire short, less than thirty items. Do not ask for information just for the sake of it; only ask what you need to know. Consider whether you will ask them the questions yourself or leave them to fill in the answers by themselves. Be wary of traps when wording your questions.

    You may use a questionnaire with only a few respondents. In this case you will probably use a detailed questionnaire. But a shorter one can be used as a method of extracting attitudes and opinions from a sizeable sample of respondents. This is a survey.


    An interview is a series of questions a researcher addresses personally to respondents. (
    Macionis, J. and Plummer, K. 1998 p.44)

    An interview may be structured (where you ask clearly defined questions) or unstructured, where you allow some of your questioning to be led by the responses of the interviewee. Especially when using unstructured interviews, using a tape recorder can be a good idea, if it does not affect the relationship with the person being interviewed.

    In an in-depth interview the interviewer conducts a semi-structured exchange with the person being interviewed, in order to explore the interviewee's perspective on the issue in his or her own terms. The interviewer asks questions in a neutral manner, listening attentively to responses, and asking follow-up questions based on the interviewee's responses.

    Focus Groups One or two researchers and several participants meet as a group to discuss a topic. One researcher (the moderator) may lead the discussion by asking participants to respond to open-ended questions while a second researcher (the notetaker) takes detailed notes.

    Laboratory Experiments: If your primary data are to be collected in the laboratory you must be scrupulously careful about the way your equipment is designed and set up. You must devise a method for recording your results that can be interpreted by others as well as by you. Results should be able to be repeated by another experimenter. Laboratory experiments may relevant to all major research groupings, with the possible exception of the humanities, but are primarily used in physical science, life science, and engineering research.

    Field Experiments: In the context of research methods, a field experiment suggests that an investigation subjected to certain controls is conducted in non laboratory conditions. For example, a new low fat ice cream may have been developed as a result of laboratory research and a field experiment may be set up to see how well it is liked by students.

    Field Work; Participant Observation and Ethnography:

    Field work In the development of biology teaching at London University, students were taken to salt marshes in Brittany to study the distribution of plants (ecology) from 1904. Previous practical work had been with a microscope in the laboratory, studying the structure of plants (morphology)

    Participant Observation is a method by which researchers systematically observe people while joining in their activities. Cultural Anthropologists developed these methods (which they call fieldwork) to study communities in other societies. Anthropologists call the studies they write describing other societies: ethnographies. Sociologists and others using participant observation to describe people in particular social settings within their own society may call their work case studies. ( Macionis, J. and Plummer, K. 1998 p.48)

    Although names like field work and participant observation were developed in the 20th century, the practice of observation whilst living in the situation is much older. An example from 1827-1830 is Edward Gibbon Wakefield who took advantage of a three year prison sentence to carry out social investigations in Newgate prison.

    Observation and Visits: You can collect data by observation when you make a visit to anywhere that is appropriate to your research: a nursery, a residential home, a factory, a building site, an office, a shopping centre, etc. Think and plan in advance the questions you are looking for answers to and also think and plan your methods of recording, storing and retrieving the material. It is not always convenient or acceptable to make notes as you go along so a useful technique is to write a report of what you have heard and seen immediately afterwards.

    Case Studies: A case study is often the basis for a student project, especially in the social sciences. In this type of research a student may spend a period in an organisation and the comments and conclusions that emerge will be based solely on his or her experiences in that setting. Reference would usually be made to written records of the organisation too. (See also, Action Research).

    Action Research This approach is used to investigate a concrete problem located in a particular situation. For example, an education student might carry out on the spot research in the classroom and a tourism student might do it in a hotel in which s/he is working. A variety of mechanisms can be used to collect data: questionnaires, interviews, observations, case studies, diaries etc.

    Historical Research

    Historical research may, in some way, create and critically examine a narrative of development of (for example) a movement, a concept, or an issue.

    These are three examples of historical research by sociology students:

  • examination of the concept of the normal person in evaluating lunatic asylums in the nineteenth century. (Greene, D. 2006)

  • examination of Comte's ideas about the progression towards scientific positivism, with reference to the evolution of human religious ideas throughout history. (Hassan, H. 2008)

  • Hitler's theory of history: An examination of sociological and political explanations for power and authority in Nazi Germany. (Roddy, S. 2008)

    A diversity of secondary and primary data may need to be collected and analysed in a historical research project, and you may need to be aware of the criteria by which historians evaluate sources.

    Media Research

    There are different ways of analysing the output of media. These range from informal, unstructured commentary on a collection of newspaper articles to the formal quantitative content analysis of a systematically collected sample.

    Documentary Research is sometimes called Secondary Research - sometimes Desktop Research and sometimes Library Research. To do it, you systematically and objectively locate (find), evidence relevant to your research, in documents that are already in existence (secondary data), rather than collecting your own (primary) data. This evidence is analysed, evaluated, and, possibly, synthesised in your report or dissertation, in order to establish the facts and/or draw conclusions.

    Triangulation: In connection with research, triangulation usually means using three (or more) research methods in a study in the hope that they will reach the same results. The idea was described by Eugene Webb and others in 1966.

    See article by Alan E. Bryman - offline and Wikipedia


    Adapted from
    Kane, E. 1985 Doing Your Own Research

    This is a list of traps to avoid when you write your questions. Some of them are based on common sense, but others might strike you only when you get baffling or useless replies. A question that to you seems extra carefully worded may be a mindbender to your respondents.

    Pretesting your questions on a practice group will help to ensure that you give your respondents appropriate questions and all the relevant choices of answers.

    The double question: Like 'Do you walk to school or carry your lunch?' The wording of such questions makes them difficult or impossible to answer accurately. Some may contain two or more unrelated parts. Some may contain contradictory parts, the answers to which may be different: 'Would you agree that it is not unlikely that our next mayor will not be a woman?'

    The wrong choice question: 'Is your hair yellow, purple, green or blue?' needs to have an alternative. Commonsense is often not enough to ensure you give respondents enough choice, for what may appear bizarre or unthinkable behaviour to you (and therefore ignored in your questionnaire) may be a way of life to some of your respondents.

    The 'fuzzy word' question: 'Should middleaged people live it up?' has two problems. 'Middleaged' does not mean the same age group to everyone, and 'living it up' can mean anything from wearing red to keeping a harem. Fuzzy words can creep into almost any question: 'Do you attend dances frequently?' (or 'rarely' or 'occasionally' or 'often') will give meaningless answers.

    The cover the world question: 'What do you think of the President?' could refer to the man or woman personally, or to how s/he is carrying out the role of president of a company or a nation. 'What's the neighbourhood like?' is useful in some interviews, but if you know what aspect of the neighbourhood interests you, ask specifically about that.

    Jargon questions: Jargon and technical terms should be avoided. 'Do you feel that your husband has a self actualising autonomous personality structure?' is an affront to the respondent and also to the English language. Also, be careful about words that have one meaning to the professionals in your field and another, or none, to the public. 'Culture,' 'personality,' 'role,' or 'institution,' cannot be treated as if all respondents shared a common understanding of the professional meaning you intended. More generally, the language and style of the questionnaire must be comfortable'to the respondent. 'Writing down' is insulting, and using dialect or 'in' words to reach a group of which you are obviously not a member is usually inappropriate.

    The kitchen sink question: 'Please list all the places you have worked in the past five years, the type of work done and salary received, and why you left.' To save confusion in replying, recording and coding the answers, ask each part of the question separately.

    Dream questions: Hypothetical questions do not necessarily produce comparable answers from different respondents. 'What kind of education would you like for your child?' might produce a 'sky's the limit' answer from a person who is stating an absolute ideal; from another person you might receive a modest statement of the best he or she thinks the child is likely to get. Make sure you know whether your question examines wishes or expectations.

    Leading questions: 'Why are you happy here in Newtown?' or 'Why do you think the community looks up to doctors?' gives the respondent little opening to say s/he is miserable in Newtown and thinks that most of the people in the community feel that doctors are charlatans.

    Hearsay questions: 'Do you think your neighbours are happy about the new school?' Do not ask one person the opinions or attitudes of another, unless you wish to compare the first person's impressions with facts that you will establish from the second person.(Or unless you are a socal scientist studying perception). You cannot cut down on your sample number by asking a small number of people what they think the attitudes of other people might be.

    Fallout questions: These are sets of questions in which something important gets lost on the way. Here is a real life example: a woman who normally dyes her hair red went to a hairdresser who required that his clients fill out a questionnaire before getting their hair done. Bad dyes of any colour will turn hair red. The questionnaire asked:
    • 1. Do you colour your hair? Yes..... No.....
    • 2. If yes, does it ever turn red? Yes..... No....
    • 3. If yes, what product do you use? ...................................................
    The conclusion which the hairdresser drew was that anyone who answered 'yes' to Question 2 was using bad hair dye a conclusion that was invalidated by the women purposely dying their hair red.

    If uninfluenced answers are required, you do not put questions in the form of 'You don't think . . . do you?'

    But the researcher's biases can be projected in more subtle ways. In an example of mothers with children under five, the focus of inquiry might be their views about adult education opportunities for themselves, and their aspirations for their children. The wording of these questions can easily imply that adult education or certain kinds of educational aspirations are something the researcher values, and therefore the mother may feel she is expected to make particular choices.

    Analysing (Interpreting) Information (data)

    Coding Data
    Based on
    Ford, J. 1975 and Ford, J. and Foley 1991

    The initial evidence or raw data that a researcher collects has to be converted ( coded) into a form of language that can be written clearly and unambiguously in standardised symbols that can be used for analysis.

    The standardised symbols are often numbers. But they may be letters (A, B, C, D, etc) or tags of three or four letters (For example: FAT, SKI, ATH, for fat, skinny and athletic).

    To begin translating raw data into the symbols, the researcher defines the coding units and creates a coding frame. How difficult this will be will largely depend on the kind of data your research has produced.

    At one extreme will be data like that from highly structured questionnaires that may be precoded (already coded). For example, a questionnaire with the following instructions has precoded the answers:
      Please tick the boxes using the following scale
      Very Satisfied: +2
      Satisfied +1
      Average 0
      Dissatisfied -1
      Very Dissatisfied -2
    The ticks on this questionnaire will already be distributed along a
    scale from -2 to +2. This is structured data.

    At the other extreme the data may be very raw - a pile of photographs, tape recordings, unstructured handwritten notes from interviews or fieldwork diaries. Data like this will need a lot of work doing on it before it can be analysed.

    Scales Coded data will be arranged on scales of numbers and symbols. Only some of these scales will be of the
    real numbers that we use in measurement. The researcher needs to know the kind of scale that is being used in order to know what kind of operations can be performed with it.

    There are five different sorts of scale which may emerge from your data. The way to understand any one of them is to understand all five, so that you can see how they relate to each other.

    Ratio scales are most often found in engineering and the natural sciences. Frances Clegg says that "chemists, physicists and biologists" do not have many difficulties about the kind of scale ("level of measurement") they are using, because the ones they mostly deal with are ratio scales or interval scales "and quite suitable for sophisticated arithmetical treatment". ( Clegg, F. 1990 p. 84)

    Ordinal scales are frequently produced by questionnaires when respondents are asked how strongly they agree or disagree with a statement. To distinguish ordinal scales from ratio and interval scales, Ford and Foley suggest that they should all be coded by letters in alphabetical order (A, B, C, D etc). They also suggest that all such scales should be turned the same way for coding so that A is always the highest value. ( Ford, J. and Foley 1991 4.5)

    Nominal scales and binary scales are typical of unstructured data, but are also produced by some questions in precoded questionnaires.

    To distinguish nominal scales, Ford and Foley suggest that they should be coded by tags of three or four letters. For example, marital status could be coded as follows:
      single: SIG
      married: MAR
      separated: SEP
      divorced: DIV
      cohabiting: COH

    Analysing Data
    Based on
    Ford, J. and Foley 1991 Chapter 5

    You will not wish or be able to present all your data in your Research Report, and the raw data may not, in itself, be very helpful. For the data to become useful you will need to analyse it.

    Analysis will include summarising it in a way that explains it to the reader ( Descriptive Statistics) and using it to test your research hypothesis ( Inferential Statistics).

    If your data is entirely qualitative (words, images, etc) it will be necessary to select examples for each category used in the coding and quote these. Usually, however, some frequency counts are also possible so that you can make summarising statements like "fifty eight per cent of the women sampled..", "out of forty nine passages expressing grief, only two.."

    Writing Up and Publishing


    Macionis and Plummer's final stage of carrying out a research project is to Share your results. Writing a Report on the research is the usual way that one does this. However, Macionis and Plummer suggest other ways:

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    Action Research
    Analysing Data
    Assessment Criteria
    Case Studies
    Categorising Data
    Coding Data
    Collecting Data
    Data Record
    Documentary Research
    Ethical principles
    Field Experiments
    Field Work
    Generating Ideas
    Getting Started
    Labelling Data
    Laboratory Experiments
    Literature Review
    Literature Search
    Mixed methods
    Preliminary Reading
    Primary Data
    Qualitative Data
    Quantitative Data
    Reading Notes
    Reliable indicators
    Report parts
    Research Methods
    Research Books
    Research Outline
    Research Proposal
    Research Statement
    Statistical experiments
    Structured Data
    Unstructured Data
    Valid indicators