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ARTICLE 89: Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 2 of 7

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Written by Dr. Hannes Nel

Hello, I am Hannes Nel and I discuss comparative and content analysis in this article.

Although quite simple, comparative and content analysis are most valuable for your research towards a master’s degree or a Ph. D.

It does not matter what the topic of your research is – you will compare concepts, events or phenomena and you will study the content of existing data sources.

What you need to know, is how to analyse and use such data.

Comparative analysis

Comparative analysis is a means of analysing the causal contribution of different conditions to an outcome of interest. It is especially suitable for analysing situations of causal complexity, that is, situations in which an outcome may result from several different combinations of causal conditions. The diversity, variety and extent of an analysis can be increased, and the significance potential of empirical data can be improved through comparative analysis. The human element plays an important role in comparative research because it is often human activities and manifestations that are compared.

Although theoretical abstractions from reality can be and, in some instances are the only way in which to do valid comparison, the units of analysis can also be whole societies or systems within societies. Comparative research does not simply mean comparing different societies or the same society over time – it might involve searching systematically for similarities and differences between the cases under consideration.

Comparative researchers usually base their research on secondary sources, such as policy papers, historical documents or official statistics, but some degree of interviewing and observation could also be involved. A measure of verification is achieved by consulting more than one source on a particular issue.

Qualitative research approaches are most suitable for the conduct of comparative analysis, with the result that many paradigmatic approaches can be used. Examples include behaviourism, critical race theory, critical theory, ethnomethodology, feminism, hermeneutics and many more.

Content analysis

Content analysis is a systematic approach to qualitative data analysis, making it suitable to serve as the foundation of qualitative research software. It is an objective and systematic way in which to identify and summarise message content. The term ‘content analysis’ refers to the analysis of such things as books, brochures, written or typed documents, transcripts, news reports, visual media as well as the analysis of narratives such as diaries or journals. Although mostly associated with qualitative research approaches, statistical and other numerical data can also be analysed, making content analysis suitable for quantitative research as well. Sampling and coding are ubiquitous elements of content analysis.

The most obvious example of content analysis is the literature study that any researcher needs to do when preparing a research proposal as well as when conducting the actual research for a doctoral or master’s degree.

Especially (but not only) inexperienced students often think that volume is equal to quality, with the result that they include any content in their thesis or dissertations without even asking themselves if it is relevant to the research that they are doing. The information that you include in your thesis or dissertation must be relevant and it must add value to your thesis or dissertation.

We analyse the characteristics of language as communication regarding its content. This means examining words or phrases within a wide range of texts, including books, book chapters, essays, interviews and speeches as well as informal conversation and headlines. By examining the presence or repetition of certain words and phrases in these texts you are able to make inferences about the philosophical assumptions of a writer, a written piece, the audience for which a piece is written, and even the culture and time in which the text is embedded. Due to this wide array of applications, content analysis is used in literature and rhetoric, marketing psychology and cognitive science, etc.

The purpose of content analysis is to identify patterns, themes, biases and meanings. Classical content analysis will look at patterns in terms used, ideas expressed, associations among ideas, justifications, and explanations. It is a process of looking at data from different angles with a view to identifying key arguments, principles or facts in the text that will help us to understand and interpret the raw data. It is an inductive and iterative process where we look for similarities and differences in text that would corroborate or disprove theory or a hypothesis. A typical content analysis would be to evaluate the contents of a newly written academic book to see if it is on a suitable level and aligned with the learning outcomes of a curriculum.

Content analysis can also be used to analyse ethnographic data. Ethnographic data can be used to prove or disprove a hypothesis. However, in this case validity might be suspect, primarily because a hypothesis should be proven or rejected on account of valid evidence. Quantitative analysis is often regarded as more “scientific” and therefore more accurate than qualitative data. This, however, is a perception that only holds true if the quantitative data can be shown to be objective, accurate and authentic. Qualitative data that is sufficiently corroborated is often more valid and accurate than quantitative data based on inaccurate or manipulated statistics.

Content analysis would typically comprise of three stages: stating the research problem, collecting and retrieving the text and employing sampling methods, interpretation and analysis. Stating the problem will typically be done early in the thesis or dissertation. Collecting and retrieving text and employing sampling methods are typically the actual research process, which may include interviewing, literature study, etc.

It is a good idea to code your work as you write. Find one or more key words for every section and keep record of it. In this manner you will be able to find arguments that belong together more easily, and you will be able to avoid duplication of the same content at different places in your thesis or dissertation. Most dedicated computer software enables you to not only keep content with the same code together, but also to access and even print it. This is especially valuable for structuring the contents of your thesis or dissertation in a logical narrative format and to come to conclusions without contradicting yourself.

Content analysis sometimes incorporates a quantitative element. It is based on examining data for recurrent instances, i.e. patterns, of some kind. These instances are then systematically identified across the data set and grouped together. You should first decide on the unit of analysis: this could be the whole group, the group dynamics, the individual participants, or the participant’s utterances. The unit of analysis provides the basis for developing a coding system, and the codes are then applied systematically across a transcript. Once the data have been coded, a further issue is whether to quantify them via counting instances. Counting is an effective way in which to provide a summary or overview of the data set as a whole.

Interviewing is mostly used prior to doing content analysis, although literature study can also be used. Analysing data obtained through interviewing includes analysing data obtained from a focus group. This variation of content analysis usually begins by examining the text of similarly used words, themes, or answers to questions. Analysed data need to be arranged to fit the purpose of the research. This can, for example, be achieved by indexing data under certain topics or subjects or by using dedicated research software. In addition to individual ideas, the flow of ideas throughout the group should also be examined. It is, for example, important to determine which ideas enjoy the most support and agreement.

Paradigmatic approaches that fit well with content analysis include feminism, hermeneutics, interpretivism, modernism, post-colonialism and rationalism.

Summary

Comparative analysis:

  1. Analyses the conditions that lead to an outcome.
  2. Involves searching systematically for similarities and differences.
  3. Mostly uses secondary data sources.
  4. Is mostly used with qualitative research.

Theoretical abstracts can be used for comparative analysis.

Comparative analysis is used:

1.      To increase the diversity, variety and extent of an analysis.

2.      To analyse human activities.

3.      To analyse whole societies and systems within societies.

Content analysis:

  1. Can serve as the foundation for qualitative research.
  2. Can be used with qualitative and quantitative research.
  3. Extensively uses literature as data.
  4. Can also be used to analyse ethnographic data.

The purpose of content analysis is to identify patterns, themes, biases and meanings.

It would typically comprise of three stages: stating the research problem, collecting data, and analysing data.

Coding can be used with good effect in content analysis.

Close

You probably already noticed that the differences between different data analysis methods are just a matter of emphasis.

They share many elements.

For example, both comparative analysis and content analysis use literature as sources of data.

Both fit in better with qualitative research than with quantitative research.

This means that you can use more than one data analysis method to achieve the purpose of your research.

Enjoy your studies.

Thank you.

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ARTICLE 88: Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis Methods Part 1 of 7 Parts

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Written by Dr. Hannes Nel

Isn’t life strange?

There are so many ways in which we can learn.

And the interrelatedness of events, phenomena and behaviour can be researched in so many ways.  

And we can discover truths and learn lesson by linking data, paradigms, research methods, dada collection and analysis methods.

And by changing the combination of research concepts, we can discover new lessons, knowledge and truths.

Research often deals with the analysis of data to discriminate between right and wrong, true and false.

Furthermore, people and life form a system with a multitude of links and correlations.

Consequently, we can learn by conducting research on even just an individual. 

I discuss the following two data analysis methods in this article:

  1. Analytical induction.
  2. Biographical analysis.

Analytical induction

Induction, in contrast to deduction, involves inferring general conclusions from particular instances. It is a way of gaining understanding of concepts and procedures by identifying and testing causal links between them. Analytical induction is, therefore, a procedure for analysing data which requires systematic analysis.

It aims to ensure that the analyst’s theoretical conclusions cover the entire range of the available data.

Analytical induction is a data analysis method that is often regarded as a research method. It uses inductive, as opposed to deductive reasoning. Qualitative data can be analysed without making use of statistical methods. The process to be explained and the factors that explain the phenomenon are progressively redefined in an iterative process to maintain a perfect relationship between them.

The procedure of analytical induction means that you, as the researcher, form an initial hypothesis or a series of hypotheses or a problem statement or question and then search for false evidence in the data at your disposal and formulate or modify your conclusions based on the available evidence. This is especially important if you work on a hypothesis, seeing that evidence can prove or refute a hypothesis.

Data are studied and analysed to generate or identify categories of phenomena; relationships between these categories are sought and working typologies and summaries are written based on the data that you examined. These are then refined by subsequent cases and through analysis. You should not only look for evidence that corroborates your premise but also for evidence that refutes it or calls for modification. Your original explanation or theory may be modified, accepted, enlarged or restricted, based on the conclusions to which the data leads you. Analytical induction will typically follow the following procedure:     

  1. A rough definition of the phenomenon to be explained is formulated.
  2. A hypothetical explanation of the phenomenon is formulated.
  3. A real-life case is studied in the light of the hypothesis, with the object of determining whether the hypothesis fits the facts in the case.
  4. If the hypothesis does not fit the facts, either the hypothesis is reformulated or the phenomenon to be explained is redefined, so that the case is excluded.
  5. Practical certainty may be attained after a small number of cases have been examined, but the discovery of negative evidence disproves the explanation and requires a reformulation.
  6. The procedure of examining cases, redefining the phenomenon, and reformulating the hypothesis is continued until a universal relationship is established, each negative case calling for a redefinition or a reformulation.
  7. Theories generated by logical deduction from a priori assumptions.

Paradigmatic approaches that can be used with analytical induction include all paradigms where real-life case studies are conducted, for example transformative research, romanticism, relativism, rationalism, post-structuralism, neoliberalism and many more.

Biographical analysis

Biographical analysis focuses on an individual. It would mostly focus on a certain period in a person’s life when she or he did something or was somebody of note. Biographical analysis can include research on individual biographies, autobiographies, life histories and the history of somebody told by those who know it. Data for a biographical analysis will mostly be archived documents or at least documents that belong in an archive. Interviews can also be used if the person is still alive or by interviewing people who knew the individual well when still alive.

Although biographical analysis mostly deals with prominent individuals, it can also deal with humble people, people with tragic life experiences, people from whose life experiences lessons can be learned, etc. Regardless of whether the individual is or was a prominent person or not, you as the researcher will need to collect extensive information on the individual, develop a clear understanding of the historical and contextual background, and have the ability to write in a good narrative format.

You can approach an autobiographical analysis as a classical biography or as an interpretive biography. A classical biography is one in which you, as the researcher, would be concerned about the validity and criticism of primary sources so that you will develop a factual base for explanations. An interpretive biography is a study in which your presence and your point of view are acknowledged in the narrative. Interpretive biographies recognise that in a sense, the writer ‘creates’ the person in the narrative.  

Summary

Analytical induction:

  1. Is a procedure for analysing data.
  2. Requires systematic analysis.
  3. Identifies and tests causal links between phenomena.
  4. Ensures complete coverage of data through theoretical conclusions.
  5. Is regarded as a research method by some.
  6. Progressively refines the explanation of phenomena.
  7. Searches for false information through hypothesis testing.
  8. Searches for relationships between phenomena.
  9. Modifies wrong conclusions.
  10. Identifies categories of phenomena.
  11. Enables the researcher to write and summarise working typologies.

Biographical analysis:

  1. Focuses on the individual.
  2. Can include research on individual biographies, autobiographies and life histories.
  3. Mostly fall back on archival documents.
  4. Can deal with anybody’s experiences from which others can gain value and learn lessons.
  5. Can be a classical or interpretive biography.

Close

In this video, we saw how we can gain knowledge by testing the validity, authenticity and accuracy of data.

We also saw that we can learn from the experiences of others.

There are many other ways in which we can discover knowledge by analysing existing data.

We will discuss them in the six articles following on this one.

Enjoy your studies.

Thank you.

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ARTICLE 87: Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis Through Coding

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Written by Dr. Hannes Nel

Introduction

Hello, I am Hannes Nel and I introduce the data analysis process and ways in which to analyse data in this article. 

You need to know what the different data analysis methods mean if you are to conduct professional academic research. There are a range of approaches to data analysis and they share a common focus. Initially most of them focus on a close reading and description of the collected data. Over time, they seek to explore, discover, and generate connections and patterns underlying the data.

You would probably need to code the data that you collect before you will be able to link it to the problem statement, problem question or hypothesis for your research. Making use of dedicated computer software would be the most efficient way to do this. However, even if you arrange and structure your data by means of more basic computer software, such as Microsoft Excel or, even more previous century, cards on which you write information, you will still be coding the data.

The fundamentals of data analysis

The way you collect, code and analyse data would largely depend on the purpose of your research. Quantitative and qualitative data analysis are different in many ways. However, the fundamentals of data analysis can mostly be applied to both. In the case of quantitative research, the principles of natural science and the tenets of mathematics can often be added to the fundamentals. Therefore, the fundamentals that I discuss here refer mostly to qualitative research and the narrative parts of quantitative research reports. For our purposes a research report can be a thesis or dissertation.

You should “instinctively” recognise possible codes and groupings by just focusing on the research problem statement or hypothesis. Even so, the following hints, or fundamentals on collecting and analysing data remain more or less the same, regardless of which data analysis method and dedicated computer software you may use:

  1. Always start by engaging in close, detailed reading of a sample of your data. Close, detailed reading means looking for key, essential, striking, odd, interesting, repetitive things people or texts say or do. Try to identify a pattern, make notes, jot down remarks, etc.
  2. Always read and systematically code your collection of data. Code key, essential, striking, odd, linked or related and interesting things that are relevant to your research topic. You should use the same code for events, concepts or phenomena that are repeated many times or are similar in terms of one or more characteristics. These codes can be drawn from ideas emerging from your close, detailed reading of your collection of data, as well as from your prior reading of empirical and theoretical works. Review your prior coding practices with each new application of a code and see if what you want to code fits what has gone before. Use the code if it is still relevant or create a new code if the old one is no longer of value for your purposes. You may want to modify your understanding of a code if it can still be of value, even if the original reason why you adopted it changed or has diminished in significance.
  3. Always reflect on why you have done what you have done. Prepare a document that lists your codes. It might be useful to give some key examples, explain what you are trying to get at, what sort of things should go together under specific codes. Dedicated computer software offers you a multitude of additional functions with which you can sort, arrange, and manipulate objects, concepts, events or phenomena, for example memoranda, quotations, super codes, families, images, etc.

Memoranda can be separate “objects” in their own right that can be linked to any other object.

Quotations are passages of text which have been selected to become free quotations.

Super codes can be queries that typically consists of several combined codes.

And families are clusters of primary documents (PDs)), images that belong together, etc.

  • Always review and refine your codes and coding practices. For each code, accumulate all the data to which you gave the code. Ask yourself whether the data and ideas collected under this code are coherent. Also ask yourself what the key properties and dimensions of all the data collected under the code are. Try to combine your initial codes, look for links between them, look for repetitions, exceptions and try to reduce them to key ones. This will often mean shifting from verbatim, descriptive codes to more conceptual, abstract and analytical codes. Keep evaluating, adjusting, altering and modifying your codes and coding practices. Go back over what you have already done and recode it with your new arguments or ideas.
  • Always focus on what you feel are the key codes and the relationship between them. Key codes should have a direct bearing on the purpose of your research. Make some judgements about what you feel are the central codes and focus on them. Try to look for links, patterns, associations, arrangements, relationships, sequences, etc.
  • Always make notes of the thinking behind why you have done what you have done. Make notes on ideas that emerge before or while you are engaged in coding or reading work related to your research project. Make some diagrams, tables, maps, models that enable you to conceptualise, witness, generate and show connections and relationships between codes.
  • Always return to the field with the knowledge you have already gained in mind and let this knowledge modify, guide or shape the data you want to collect next. This should enable you to analyse the data that you collected and sorted, to do some deconstruction and create new knowledge. Creating new knowledge requires deep thinking and thorough background knowledge of the topic of your research.

How data analysis should be approached

When undertaking data analysis, you need to be prepared to be led down novel and unexpected paths, to be open to new interpretations and to be fascinated. Potential ideas can emerge from any quarter – from your reading, your knowledge of the field, engagements with your data, conversations with colleagues or people whom you interview. You need to be open-minded enough to change your preconceived ideas and to let the information change your mind. You also need to listen to and value your intuition. Most importantly, you need to develop the ability to come to logical conclusions from the information at your disposal.

Do not try to twist conclusions on the data that you gather to suit your opinion or preferences. Your computer allows you to return to what you previously wrote and to change it. This will often be necessary if you are to develop scientifically founded new knowledge. Your conclusions and ideas might change repeatedly as you collect new information.       

Do not be frustrated if, as you progress with your research, you find that the codes on which you decided initially no longer work. Again, you can easily change your codes on computer or cards. You must do this in the interests of conducting scientific research. You will typically allocate primary codes to the issues that you regard as important and sub-codes to less important data or further elaborations on your main arguments. You can change this and change your coding structure if necessary.

The process of coding requires skill, confidence and a measure of diligence. Pre-coding is advisable, but you still need to accept that the codes that you decided upon in advance will probably change as you work through the data that you collect.

At some point you need to start engaging in a more systematic style of coding. You can work on paper when starting with the coding, although there is no reason why you can’t start to work on computer from the word go, seeing that you can change your codes on computer at any time with relative ease. Besides, you can make backups of your coding on computer. This can be valuable if, at some stage, you discover that your initial or earlier codes work better than the new ones after all. You can then return to a previous backup without having to redo all the work that you already did.

You need to understand how the computer software that you are using works and what it can provide you with. Different software has different purposes and ways in which codes can be used. It serves no purpose claiming to have used a particular software if you do not really understand how it works, how you should use it and what it can offer you. Previous students will not always be able to teach you the software because most of the software is rewritten all the time. Rather do a formal course on the latest version of the software that you wish to use.

Summary

Most data analysis methods share a common focus.

Data analysis is simplified by coding the data and making use of dedicated computer software.

You can also use coding with simple data analysis methods, for example Microsoft Excel or a card system.

The fundamentals of data analysis apply to qualitative and quantitative research.

You should code data by focusing on the purpose of your research and the research problem statement, question or hypothesis.

The following are the fundamentals of data analysis through coding: Always:

  1. Start by engaging in close, detailed reading of a sample of your data.
  2. Read and systematically code your collection of data.
  3. Reflect on why you have done what you have done.
  4. Review and refine your codes and coding practices.
  5. Focus on what you feel are the key codes and the relationship between them.
  6. Make notes of the thinking behind why you have done what you have done.
  7. And always return to the field with the knowledge you have already gained in mind and let this knowledge modify, guide or shape the data you want to collect next.

In addition to the fundamentals, you should also adhere to the following requirements for the analysis and coding of data:

  1. Be flexible and keep an open mind.
    1. Learn how to come to objective and logical conclusions from the data that you analyse.
    1. Change your codes at any stage during your research if it becomes necessary.
    1. Develop your data analysis coding skills, confidence and diligence.
    1. Acquire a good understanding of the computer software that you will use for data analysis.
    1. Work systematically.

Close

You will use the fundamentals of data analysis and coding with most data analysis methods.

Almost all recent dedicated data analysis software use coding.

I will discuss the following analysis methods in my next seven or eight videos:

  1. Analytical induction.
  2. Biographical analysis.
  3. Comparative analysis.
  4. Content analysis.
  5. Conversation and discourse analysis.
  6. Elementary analysis.
  7. Ethnographic analysis.
  8. Inductive thematic analysis (ITA).
  9. Narrative analysis.
  10. Retrospective analysis.
  11. Schema analysis.
  12. Situational analysis.
  13. Textual analysis.
  14. Thematic analysis.
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ARTICLE 86: Research Method for Ph. D. and Master’s Degree Studies: Preparing for Data Collection

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Written by Dr. Hannes Nel

How long do you think will it take you to complete a thesis or dissertation?

You probably know the old saying that work expands to fill the time available for its completion.

That is also true for academic research.

I guess the average student will need one or two years for a thesis towards a master’s degree and two to ten years for a dissertation towards a Ph. D.

This is not a lot of time.

Believe me, you will need every second that you can spare to complete the work in the available time.

And you will need to plan your research project as accurately as you possibly can.

I discuss how to plan and organise data collection for research in this article.

Organising data collection. Once you have decided on the research approach and data collection instruments you will use you should be able to draw up a draft schedule for your research. This will relate the time you have available in which to carry out the research – a given number of hours, days, weeks or perhaps years – to your other responsibilities and commitments. You can then slot in the various research activities you will need to engage in at times when you expect to be both free and, in the mood, to work on your research.

Many universities require of students to report on their progress at specific stages. This is not in line with the principles of adult learning, although it is often necessary. Even if such due dates are not set by a study leader, it is still a good idea to draft a schedule for your research work. You know that you will probably have only limited time in which to do the work, so sketch out what you will be doing, month by month or week by week, in order to achieve your objectives. Remember to leave yourself some flexibility and some ‘spare time’, for when things do not go exactly as planned. This means that you need to do some contingency planning as well.

Just because you have drawn up a schedule, however, does not mean that you will go to jail if you do not keep strictly to it. It is difficult, even with experience, to precisely estimate the time that different research activities will take. Some will take longer than expected, whereas others may need less time. Some will be abandoned, whereas other unanticipated activities will demand attention. It is a good idea to allow for some spare time and flexibility in your scheduling. You should also revisit your schedule from time to time, and make revisions, to allow for such changes and to keep yourself on track.

One thing you must avoid is to put off work until the last minute. If you drag your feet you will not be able to submit on the due date. Rather try to work ahead of your schedule so that you will have some spare time, should you need it because of unforeseen eventualities.

There are several ways of scheduling your research time. Project management software offer sophisticated ways in which to illustrate your research project diagrammatically or graphically. 

Such charts suggest a simplified, rational view of research. They are useful in conveying the overlap of concurrences between the tasks to be carried out and can serve as a guide to monitor your progress. In practice there will be numerous minor changes to your plans as set out, and perhaps some major ones as well.

Piloting instruments for the collection of data. It is advisable to pilot your data collection instruments before you use them on your actual target group. In this manner you can save lots of time and money, because it would be a catastrophe if, for example, you were to send out 10 000 questionnaires of which you receive 2 000 back only to find that you cannot use any because of some simple technical error.

Rather carry out a couple of interviews with friends or colleagues in advance or have them fill out some questionnaires or observe some organisational activities – or whatever else you plan on using to gather data with. You will learn a great deal from the activity, for example the amount of time that collecting data can take. You will also know if your instruments work or not. You need to pilot your instruments early enough so that you will still have time to change them or even your data collecting strategy if necessary.

Do not underestimate the value of pilot research. Things never work out quite the way you expected them to, even if you have done them many times before, and they have a nasty habit of turning out differently from how you expected them to. If you do not pilot your data collection instruments and procedure first, you will probably find that your initial period of data collection turns into a pilot study in any case. 

And yes, the surprise that you get will be a pleasant one if you planned and conducted your data collection well.

Summary

You can use the following steps to plan and organise your data collection:

  1. Decide which research approach and method or methods you will use.
  2. Choose the data collection methods and instruments that you will use.
  3. Decide how much time you will need to conduct your research I you did not decide already.
  4. Fit your research activities into the time that you have available for research.
  5. Draft a schedule for your research work.
  6. Do contingency planning if you did not do so already.
  7. Allow for some spare time in your schedule.
  8. Allow for time to meet with your study leader.
  9. Pilot the data collection instruments that you will use.

Close

Do not put off any research work until the last minute.

Pilot the data collection instruments early enough so that you will have time to correct and improve them.

Keep your study leader informed about your progress.

Enjoy your studies.

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ARTICLE 85: Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods: Written Documents

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Written by Dr. Hannes Nel

I guess many of us were conditioned from the day we started school to regard what is written on paper or what we can see on our computer monitors or cell phones as knowledge.

And as we grew older, we were taught to write things.

Probably most teachers and, later, lecturers, teach pupils and students that there are other sources of data apart from written documents.

But somehow, when we need to write a report of any kind, we fall back on written documents as our main, sometimes only, sources of data.

It is a good starting point.

Just keep in mind that what is written on paper or electronically is already old.

And the world is dynamic.

And we must be able to adapt to changes in the environment rapidly.

And especially on doctoral level, we need to develop new knowledge.

And existing knowledge is sometimes an obstacle in the way of progress.

I discuss the use of written documents as a data source in this article.

Almost all research projects involve, to a greater or lesser extent, the use and analysis of documents. You are expected to read, understand and critically analyse the writing of others, whether fellow researchers, practitioners or policymakers. For some research projects the focus of data collection is wholly or almost entirely, on documents of various kinds.

Documents are records of past events that are written or printed; they may be anecdotal notes, letters, diaries, reports and, of course, books. Official documents include internal papers, communications to various public, student and personal files, programme descriptions, and institutional statistical data.

In interactive data collection techniques, you can find these documents at the site or a participant may offer to share these personal records with you. Documents are the most important data source in concept analysis and historical studies. Documents are usually catalogued and preserved in archives, manuscript collection repositories, or libraries. Documents might, for example:

  1. Be library-based, aimed at producing a critical synopsis of an existing area of research writing.
  2. Be computer-based, consisting largely of the analysis of previously collected data sets.
  3. Be work-based, drawing on material produced within an organisation.
  4. Have a policy focus, examining material relevant to a particular set of policy decisions.
  5. Have a historical orientation, making use of available archival and other surviving documentary evidence.

Using documents can be a relatively unobtrusive form of research, one which does not necessarily require you to approach respondents directly. Reading documents is usually supplemented by other data collection methods. You will probably make considerable use of secondary data, i.e. data which has already been collected, and possibly also analysed, by somebody else. Technically speaking most documents are secondary data, the most common forms of which are official statistics collected by governments and government agencies.

One needs to be cautious when analysing secondary data. The questions you need to ask of any existing document are:

  1. What were the conditions of its production? For example, why, and when, was the document written and for whom?
  2. If you are using statistical data sets, have the variables changed over time?
  3. Have the indicators of statistical data sets that you used to measure variables changed? For example, the measurement of unemployment has undergone many changes in the past two decades, and even today different research agencies use different definitions of unemployment as well as different statistical models, so that they produce different figures for what should be the same thing. This makes comparison of figures difficult and sometimes unrealistic.

You will invariably make use of written documents, including books and your own notes taken during interviews and fieldwork (observation), as sources of information. You will already have used such documents when you prepared your study proposal. Another important data collection activity where you will extensively use written documents will be when you do your literature review. 

The notes taken during interviews need to be a true and accurate reflection of what has been said by the interviewees. You need to distinguish between capturing the exact words and paraphrasing. This is important for showing proof that you did not commit plagiarism and that the way you used the data is accurate, valid and consistent.

Notes that you take can be rather voluminous. However, you should still pay attention to taking accurate notes. You should also note the names of people who you interviewed or spoke to, who said what during focus group meetings and the time, dates and places where the interviews or discussions took place.

Treat the opportunity to review any material as if it were your only opportunity to access and read the documents. By doing so, you will reduce the frustration created by having to return to the material later. You will also minimise inconveniencing any people who may have had to retrieve the material for you.

People whom you interviewed will not always be available or willing to repeat the interview, should you lose your notes. It is always a good idea to make duplicates of written documents. This, of course, is easier if you could just make a backup of an electronic version of the documents. Also type a copy of a voice recording as soon as you have an opportunity to do so. Check that the recorder is working before you do an interview or focus group.

Summary

Almost all research projects use written documents as a source of data.

A document can be anything that is written or printed.

Documents can be found in libraries, personal collections, in bookshops, archives and many more.

The contents of documents are often supplemented by other sources of data.

Most documents are secondary data.

You must corroborate written data.

Be careful of not committing plagiarism when using documents as a source of data.

Make sure that your notes and other documents that you prepare are accurate and relevant to your research.

It is advisable to store your notes electronically or to make printed or written duplicates.

Close

The requirements for the collection and use of documents as sources of data are in many ways the same as for most data collection methods.

  1. All data should be corroborated, regardless of how it was collected.
  2. All data that you collect, and use must be relevant to your research.
  3. You must acknowledge the origin of data that you use in your thesis or dissertation.
  4. You must be able to provide evidence of the data that you refer to in your thesis or dissertation, should your study leader, an external evaluator or any other stakeholder question it.

Enjoy your studies.

Thank you.

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ARTICLE 84: Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods: Online Data Sources Part 2 of 2 Parts

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Written by Dr. Hannes Nel

Did you notice how many experts of all shapes and sizes post videos on the internet in which they predict the end of the world?

Some of them even give a date and time for the ultimate catastrophe.

And when it does not happen, they simply shift the date.

Do you believe them?

And if you do, what criteria should they meet for you to regard them as trustworthy prophets of doom?

I discuss the requirements for accuracy and authenticity of data in this video.

The internet can be a valuable source of information. However, people doing research need to be careful when using information obtained from internet sources. Any individual can upload information on the internet and all web site hosts are not equally responsible when it comes to accepting contributions. All information that you use in your research should be corroborated. This is an important consideration because electronic documents are not always quality assured, and documents are sometimes distributed electronically because publishers are not interested in them.

The accuracy an authenticity of information can be evaluated by checking the following:

  1. Checking the author.
  2. Checking the purpose.
  3. Checking for objectivity.
  4. Checking for accuracy.
  5. Checking for reliability and credibility.
  6. Checking for coverage.
  7. Checking for currency.
  8. Checking links.

Checking the author. You can check personal homepages on the World Wide Web, campus directory entries and information retrieved through search engines to find relevant information about an author. You can also check print sources in the library reference area and other biographical sources, for information such as the following:

  1. Is the name of the author/creator on the page?
  2. Is the page signed?
  3. Are his/her relevant profile and credentials listed, including occupation, years of experience, position or education? Stated differently, is the author suitably qualified to write on the given topic?
  4. Is there contact information, such as an email or web site address on the page?
  5. If there is a link to a web site address, is it for an individual or for an organisation?
  6. What is the relationship of the author with the organisation, if the address is that of an organisation, for example a university or consulting company?

Checking the purpose. It is often easier to judge the contents of a source if you know for what purpose the article was written. Also check for whom the article is intended.

Checking for objectivity. Objectivity is a prerequisite of any research. Even so, political and social issues are strong temptations to misuse and misinterpret information to fit a particular agenda. The following questions can be used to check if your interpretation of data is objective or not:

  1. Is there any indication if the information is claimed to be factual, just the opinion of an individual, or the propaganda of a body with ulterior motives, for example a political body, radical or religious group?
  2. Judging from the formulation and tone of the document, does the author’s point of view appear to be objective and impartial or not?
  3. Is the language and tone in which the document is written free of or loaded with emotional words and bias?
  4. Is the author affiliated with an organisation, the values and objectives of which might render the information biased and subjective?
  5. Is the document free of or cluttered with advertisements or sponsored links?

Checking for accuracy. Accuracy can mean different things to different people, depending on which paradigmatic approach you follow. However, data and the interpretation of data need to be valid, authentic, free of deliberate, accidental or coincidental misrepresentations and logical, to be of value for research purposes. The following questions can be used to check the accuracy of data and your research findings:

  1. Are the sources of factual information clearly and accurately acknowledged so that the information can be verified?
  2. Is it clear who has the ultimate responsibility for the accuracy of the content of the material and is the profile of this individual or group of experts known?
  3. Is the information corroborated by other sources or can you verify the information from your own knowledge?
  4. Has the information been reviewed or referred by an individual or group of experts with the necessary knowledge to conduct professional evaluation?
  5. Has the document been written on an acceptable academic level and is the information free of grammatical, spelling, and typographical errors?

Checking for reliability and credibility. Reliability and credibility go hand in hand with accuracy. Reliable information is information that is consistently the same over time and across at least the target group for the research, although it should ideally be the same in as wide a context as possible. Credibility is dependent on the authenticity, accuracy and trustworthiness of the data and research findings. You, as the researcher, will be responsible for credibility, which means that you will need to conduct the research in an accountable, honest and ethical manner. Reliability and credibility can be checked by asking and answering the following questions: 

  1. Why should anyone believe information from this source?
  2. Judging from the content and layout, does the information appear to be valid and well-researched, or is it written in an unstructured manner and inaccurately supported or not supported at all by evidence of authenticity?
  3. Has the document been published by a publisher with a good reputation for only publishing quality content that has been checked for accuracy, authenticity and objectivity?
  4. Are quotations and other strong statements or claims backed by sources that you could check through other means, and are the sources acknowledged where the statements or claims are made?
  5. Which university, college, research experts or scientists support or endorse the information?
  6. Do the university, college, research experts or scientists who support or endorse the information have a good reputation as being objective and an authority in the field of the document?
  7. Is the electronic material also available in hard (book or magazine) format?

Checking for coverage. Coverage refers to the notion of saturation. Your research findings should not be biased or rendered inaccurate because you did not consult enough, or the wrong sources of information. Although the extent of research is always limited by factors such as capacity, available time, funds, and the co-operation of members of the target group, you should at least achieve the purpose of your research. Coverage can be checked by asking and answering the following questions:

  1. Is the information relevant to the topic of your research?
  2. Does the document have information that is not available elsewhere?
  3. How in-depth is the material?

Checking for currency. The most important factor determining currency is, of course, recency. The more recent the information that you collected is, the more accurate, valid and relevant will your research analysis and findings be. Currency can be checked by asking and answering the following questions:

  1. Is the document reviewed regularly by someone who has the relevant knowledge and skills?
  2. Does the document or posting show when it was originally written, when and how often it was reviewed and when it was last reviewed?

Checking links. Each web site should be checked independently because the quality of web pages linked to the original web page may vary. This can be done by asking and answering the following questions:

  1. Are the links related to the topic of the document and are the web sites that are linked articulated to the purpose of the site and the content of the document?
  2. Are the links still current, or have some or all of them been deactivated or simply abandoned?
  3. What kinds of other sources are linked and are they in any way related to the contents and purpose of the document in which you are interested?
  4. Are the links maintained, evaluated and reviewed and do they show growth in terms of traffic volume, quality of content and the user-friendliness and professional and attractive layout of the sites?

Summary

Anybody can post data on the internet. Therefore, you need to be careful when using such data in your research.

The accuracy and authenticity of information can be evaluated by checking the following:

  1. The author. The author should be a known and reputable authority in the field of study. Also, the author should be acknowledged in the data source that you consult.
  2. The purpose of the data source. The data source should be relevant to your research topic.
  3. Objectivity. Be wary of articles, videos and other data source on the internet that were posted with ulterior, possibly damaging motives in mind.
  4. Accuracy. Data must be valid, authentic, free of misinterpretation and logical.
  5. Reliability and credibility. Data should be consistently the same over time and context.
  6. Coverage. Data should answer at least part of your research question and add value to your thesis or dissertation. On doctoral level the data should lead to new and improved knowledge.
  7. Currency. Data must still be relevant to the field of your research.
  8. Links. Quality data will mostly be shared and supported by more than one authority in the field of study. The more academic web pages deal with the topic and agree with the arguments, the more likely it is to be valid, authentic, accurate and recent.

Close

You will ultimately be responsible for the quality of data that you collect and use in your thesis or dissertation.

You will also be accountable for the way you use the data.

It serves no purpose checking the accuracy and authenticity of the data that you collect if you bend the meaning of the original author to serve your purpose.

Or if you use accurate data to achieve ulterior, damaging motives.

As with all data that you collect and use, ethics is a critically important requirement for your research.

Enjoy your studies.

Thank you.

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ARTICLE 83: Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods: Online Data Sources Part 1 of 2 Parts

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Written by Dr. Hannes Nel

Should you steer clear from using data found on the internet for your research?

Are the possibilities that such data will be false or tainted too high to justify its use?

Is information in books more authentic, accurate and valid than data on the internet?

How does your study leader feel about this?

I discuss the internet as a source of data in this article and the article following on this one.

Written documents, oral interviews, demonstrations and many other data sources can be found on the internet. The internet can be used to gather data as well as to actively construct meaning through participation in social media networks.  It is true that many internet sources of information are of poor quality, not well-researched and unreliable. However, internet data is often much more recent than what is written in books and old information is often no longer relevant and, therefore, worth less than information on the internet. What is needed when consulting and using internet data is a good measure of logical thinking and corroboration. Triangulation is the obvious way in which to ensure that the data that you find on the internet is valid, although, as many of you probably already noticed, surprisingly many internet articles contain much the same, sometimes even identical information. This is probably because people obtain information on the internet and use it in their own articles without acknowledging their sources or making any effort to rephrase what they copied.

The internet is an umbrella term for innumerable technologies, capacities, uses, and social spaces. Because the types of social interaction made possible by the internet vary so widely, qualitative researchers find it necessary to define the concept more narrowly within individual studies. This is complicated by the fact that the study of the internet cuts across all academic disciplines. There are no central methodological or theoretical guidelines, and research findings are widely distributed and decentralised.

Internet technologies are ubiquitous and mobile. You have access to more books, articles and other data sources via your cell phone than what can be found in the books in university libraries (although university libraries now also offer access to the internet).

The internet is often regarded as a tool for collecting information because of how easily researchers can gain access to groups, download texts, capture conversations, observe individual and group behaviour, or interact with participants at a distance. A researcher might also utilise various capacities and interfaces available via the internet to augment or replace traditional qualitative methods of collecting, storing, sorting and analysing information. The internet is also associated with the use of data analysis software, even if it is not strictly necessary to enable the functioning of such analytical tools.

The internet can also be experienced as a place. Therefore, you might conceptualise it as a field site.  The internet facilitates the formation of relationships and communities. If these cultural formations rely on the internet for their composition or function, they are considered ‘internet-mediated’ or ‘digitally saturated’. Researchers of such cultural formations or network sociality might take their methods from a wide range of disciplines.

You will find that your emphasis in the use of the internet will shift depending on your ontological and epistemological premise, research goals and the specific form of the research question, hypothesis or problem statement. Rigorously analysing the connections between your questions, the subject of inquiry and the possible methods of collection, analysis and interpretation is an essential part of all good qualitative research. As the purpose of your research is identified and your study unfolds, certain characteristics of the internet will become more meaningful to you and those who will read your research report.

The following characteristics portray the internet much like a two-edged sword – it offers valuable facilities but also some flaws and threats:

1.         Communicating and connecting.

2.         Presence and location.

3.         Flexible time.

4.         Contexts of social construction.

Communicating and connecting. As a communication medium, the internet provides multiple means and modes of interaction, offering many choices and platforms for finding self-identity, building relationships and developing communities. We use the internet to help with many communicative activities.

For the most part, researchers focus less on the actual platforms for performance or networks of connections, than the communities made possible by the networks or the texts, still and moving images, and sounds facilitated by these networks. Researchers use the internet in ways that parallel but depart from or extend earlier communication media, such as letters, telephone, bulletin-boards, etc. Keep in mind, though, that the internet does not fully replace, but rather augments earlier communication media, at least for the time being.

A deficiency of the internet as a means of communication is that people easily misinterpret messages if they can’t see the speaker or writer. This is because social media, such as emails and Facebook, do not show the communicator’s body language, tone of voice or facial expressions. Even when using media where the communicator can be seen, for example in some visual media, the communicator can interfere with the clarity or meaning of the message, for example by wearing a mask and masking the voice.

If used as a research tool, the internet and its capabilities should be matched to the goals, topics and participants of the research project. There are many creative possibilities. Examples are not given here because the internet changes rapidly and new tools become available while old ones change all the time. Besides, students use social media not only for academic research but also in everyday social communication, with the result that most of them can think of better and more recent examples than what are written in a book, which might be a year or more old.

Presence and location. The internet brings many people who are geographically dispersed into contact with one another regardless of the distance between them. In this manner people can establish interactive contact globally through sight and hearing. In other words, the internet extends our senses, allowing us to see, listen and reach well beyond our local sensory limits. Many decades ago, we could communicate over long distances by telephone and two-way radio, telegraph and facsimile. Electronics, specifically the improvement of digital and networked quality of communication and information-sharing, substantially improved our ability to communicate while geographically dispersed.

Thanks to the internet, the meaning of “presence” has changed to include being able to communicate via the internet rather than just proximity to one another. We can communicate while seeing one another on our computer or cell phone screens.

The internet facilitates the development of varied cultural forms. Researchers might study communities that exist solely online in immersive environments. These ‘virtual worlds’ can have defined boundaries and stable cultural patterns. Alternatively, researchers might study how location or presence is more a temporary gathering of several people. We have witnessed how students in many countries rally to air their frustration with high university tuition fees. They extensively use the internet to start and grow the campaign and to gain international support for their plight.

Flexible time. The internet is not time bound. You can read something on the internet, stop halfway through the document and continue from where you stopped later. This enable us to manipulate time to suit our own schedule and the time that we have available for doing research.

Interaction on the internet occurs in multiple modes, alternately or simultaneously. This multi-modality is meaningful when designing or capturing interactions in the research context.  We normally employ more than one internet-modality at the same time. You can send status updates to your social network, play interactive games with friends, download music, update your blog and watch videos simultaneously. Even more, your computer can warn you when a message is received, and you can check the message without closing any of the other modalities on which you are working. These functions can be studied as phenomena or used as tools to augment the ways in which you engage and communicate with the target group for your research.

You can also use the facilities that your computer offers to conduct interviews. Creative researchers can even use technologies in ways unintended by the designers. Also, what you are doing on your computer is mostly invisible to other people (unless you intentionally involve them in your work), which gives you a good measure of confidentiality.

Contexts of social construction. Computers and smart phones can filter our worlds to bring only information that we are interested in, to our attention. Different applications allow you to access and use many different sources of information and electronic tools. Some of the applications might be interactive, allowing you to participate in certain activities or communication while others allow you access but not to manipulate the information or services provided.

We often use different applications to communicate with different audiences. Some tools allow us to select the participants with whom we wish to communicate. This is especially useful for interviewing and communicating with focus groups.

The internet comprises expansive forms of presentation and interaction that can be observed immediately and archived. This capacity facilitates our ability to witness and analyse the structure of talk, the negotiation of meaning and identity, the development of relationships and communities, and the construction of social structures. Linguistic and social structures emerging through social interaction via the internet provide us with an opportunity to track and analyse how language builds and sustains social reality.

The internet is unique in that it leaves visible traces of actions, movements and interactions. Internet technologies allow us to see the visible artefacts of this negotiation process in forms divorced from both the source and the intended or actual audience. This can give you, as a researcher, a means of studying the way social realities are displayed or how these might be negotiated over time.

Summary

The internet:

  1. Is an umbrella term for innumerable technologies, capacities, uses and social spaces.
  2. Is associated with the use of data analysis software.
  3. Facilitates the formation of relationships and communities.
  4. Is a communication medium.
  5. Is dynamic and continually expands and improves.
  6. Brings many people who are geographically dispersed into contact with one another.
  7. Offers us different applications to communicate with different audiences.
  8. Facilitates the development of varied cultural forms.
  9. Is not time bound.
  10. Can filter out events and phenomena to bring only information that we are interested in, to our attention.
  11. Leaves visible traces of actions, movements and interactions.

Not only can you find data on the internet; you can also use it to construct meaning.

Internet presentation and interactions can be observed and archived.

Data found on the internet must be checked for validity and accuracy.

You must give recognition to internet data sources that you use in your research.

Both researchers using qualitative and quantitative research approaches can use the internet as a source of information and for many other purposes.

Close

The internet has become so rich and flexible in the data and research facilities that it offers that we can no longer ignore it.

Even so, you still need to accept information that you find on the internet with great circumspection.

Because some of the information on the internet is false.

Some people deliberately post information with deviant motives in mind.

But this also applies to books and articles that people write.

Even things that people say are not always true.

Therefore, you need to corroborate all the data that you gather, regardless of the source where you found it.

Enjoy your studies.

Thank you.

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ARTICLE 82: Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods: Observation Part 2 of 2 Parts: Participant Observation versus Non-participant Observation

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Written by Dr. Hannes Nel

Does participant observation mean that a player is also made the referee?

Should you, as a researcher, intervene in the problem that you are studying?

Is it ethically justifiable to observe and collect information about people without them knowing what you are doing?

Can you do research on yourself?

I discuss possible answers to these questions in this article.

Participant observation versus non-participant observation. Participant observation is also direct observation. It is a mode of field-based research whereby researchers locate themselves in the real-world field setting being studied, participating and observing in the setting while also collecting data and taking notes about the field setting, its participants, and its events.

As a participant observer you will participate in the event or action about which data is being collected. An example of this would be if you participate in an advocacy campaign while taking photos or perhaps just notes, on the behaviour of members of a crowd marching on a government office building.

Making observations as part of qualitative research will probably not involve either a formal observational instrument or a large sample of observations made under highly comparable conditions. Instead, your observations will likely be part of a participant-observer role or will be made more by chance during your interviews or other field activities. Most importantly, in most qualitative research, you are unlikely to be making multiple and repetitive observations at a single, fixed location or at pre-specified time intervals.

In acting as a participant-observer, you are likely to locate yourself in some field setting that is fluid in time and space. Such fluidity will require you to make explicit decisions about your observational choices. For instance, the fluidity means that you cannot be at all places at the same time. You also cannot watch everything that is going on, especially if the event that you are observing is complex or takes place at different places at the same time. You will, therefore, need to decide where to position yourself. It might also be necessary to use the assistance of other people.

You should plan your observation procedure well to ensure that you collect the data that you need to satisfy your research question. Record keeping is important and should reflect what you observed and when. You will need to write down who participated in the process that you observed, what you saw, how it is relevant to your research topic and the conclusions that you can make from your observations.

Objectivity, representativeness, authenticity and accuracy can be improved by repeating observations at different times or different, though similar locations.

It would be unrealistic to list all possible observations that can be done for research purposes. Some examples include observing the characteristics of individual people (mannerisms, clothes, behaviour, etc.); interactions between and among people; processes; physical surroundings, etc.

A host of different paradigmatic approaches can be used with participant observation, including, behaviourism, constructivism, ethnomethodology, functionalism, phenomenology, pragmatism, radicalism, romanticism, scientism, and symbolic interactionism.

Participant observation is an interactive technique of “participating” to some degree in naturally occurring situations over an extended time and writing extensive field notes to describe what occurs. You should not collect data to answer a specific hypothesis; rather the explanations are inductively derived from the field notes. Since the context of the observations is important, you should be careful to document your role in the situation and what effect that may have on the findings.

Most field workers remain a respectful distance from the informants – cultivating empathy but not sympathy, rapport but not friendship. Collaborative and participatory research introduces the notion of active participation by you and sharing the research role with the participants. In each variation of participant observation, the research role is established at the beginning of the study and then monitored while records are kept.

To intervene or not is an important question when doing participant observation. Your intervention in an event or action, for example asking members of your target group questions while they are doing something, might change their behaviour. Perhaps this is what you want – you need to observe how people react to certain stimuli, which you will produce or arrange. However, mostly your observations will be much more natural and valid if you don’t intervene with the target group and what they do.

As a non-participant observer, you will observe “from the outside”. In this instance you will not participate in the event. If we use the example of an advocacy campaign – you might take video footage from the top of a building of a marching crowd becoming involved in a violent riot and clashes with the police. You should recognise this as an etic approach.

Overt observation versus covert observation. Overt observation would be if you observe an event, phenomenon openly and, if necessary, with the permission of those who have an interest in the event or phenomenon. You might, for example, need the permission of the police to take footage of a march in support of an advocacy campaign.

Covert observation would be if you collect images without those who are being observed, or those who should give permission, knowing that the data is being collected. This often happens when the events or actions will be different, probably artificial, if people know that they are being observed, especially if evidence, such as photos or video footage, is being collected.

Obstacles in the way of observation. Observation can be a valuable tool with which to collect and analyse data, but it is by no means perfect.

One of the most important considerations to keep in mind when doing observations is ethics. Especially covert observation and intervening with the activities of your target group can be contentious. Collecting evidence without the consent of the target group might violate the requirement of informed consent, invade the privacy and private space of participants, and insult people by treating them as research objects.

However, the validity, authenticity and accuracy of research sometimes depend on conducting covert observation. Covert observation might, for example, be necessary for groups who would otherwise not agree to being observed even though the research is in their interest. Another example is where people will not act naturally, thereby damaging the validity of the research, if they know that they are being observed. A third scenario justifying covert observation is where the knowledge of being observed might move people to act in an unsafe manner, for example a peaceful march turning violent to provoke the police or people doing dangerous deeds because they know that video cameras are on them.

People who act illegally and under the protection of “darkness” such as burglars, child abusers, murderers, etc. can and should usually not be asked for their permission to be observed, although this might lead to rather serious arguments about denying people their constitutional rights. The ethical dilemmas are numerous. At issue is the dilemma that arises between protecting the rights of an individual versus protecting the rights of the community at large.  

A second obstacle in the way of objective and accurate observation is intervention. Should you intervene if you observe a child being abused, a person being murdered or raped, a crime being committed when your intervention will deny you a once in a lifetime opportunity to obtain valuable data for your research?

These are issues that cannot be solved by means of a code of conduct. Legislation, religion and your personal value system might serve as a guideline to help you decide. However, you will probably need to consider a host of variables to decide what you should do when confronted with ethical considerations.

A third obstacle in the way of collecting valid and reliable information through observation is the issue of bias. All human beings are subjective and largely, if not entirely, guided by their own perceptions. The following are examples of factors that can lead you to the wrong interpretations and conclusions:

  1. Our focus decides what we see and how we interpret what we see. We can easily be distracted.
  2. People do not behave the same when they know that they are being watched as when they think they are alone or can hide in a crowd or in the dark.
  3. Your state of mind, state of health and whether you are tired or not influence how you observe and think.
  4. Body language can lead us astray.
  5. Our personal preferences and value system largely determine what we see and how we interpret what we see.
  6. The longer we take to record our observations, the more likely it is that we will have forgotten details, facts and the order of events.
  7. We are subjectively influenced by our memory – what we observed previously. We tend to believe that events will repeat themselves and people will always act and respond the same under the same or similar circumstances. 
  8. We are influenced by what we expect or wish to happen.

Self-observation versus observation of others. It is possible to conduct research on the self. An example of self-observation is where a person recorded video footage and wrote down his feelings and reactions while taking drugs. Mostly, however, you would observe the target for your research.

Summary

Participant observation is also direct observation and fieldwork.

It is an interactive technique.

Therefore, you will mostly follow and emic approach.

An etic approach is also possible.

You need to decide what your role towards the target group for your research will be before you start collecting data.

To intervene with the target group or not is an important decision to make when planning observation.

Participant observation can often be semi-structured or even unstructured in qualitative research.

Even so, it is advisable to plan your observation procedure well.

You can use the assistance of other people when using participant observation to collect data.

You need to keep record of what you observed and when.

Corroboration of data can be achieved by repeating observations at different times but at similar locations.

Participant observation fits in well with the interpretivist paradigms, although it can sometimes also be used in conjunction with technicist and critical paradigms.

Overt observation would be if you observe an event or phenomenon openly.

Covert observation would be if you collect images or other data without the knowledge or permission of the target for your research.

Covert observation is sometimes necessary but needs to be done with circumspection.

Ethics is an important consideration when using observation to collect data.

A second important consideration is if you should intervene in an event or phenomenon that is relevant to your research.

A third important consideration is bias.

This means that you need to persistently guard against subjectivity in your data collection and interpretation.

It is possible and can be valuable to conduct research on yourself.

Close

I hope you noticed that it is possible to act as player and referee when collecting data through observation.

There are three preconditions for this.

Firstly, you need to act ethically.

Secondly, you should not intervene in the activities of the target group for your research, unless ethical considerations make intervention necessary.

And thirdly, you need to persistently act objectively when collecting and interpreting data.

Enjoy your studies.

Thank you.

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ARTICLE 81: Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods: Observation: Part 1 of 2 Parts

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Written by Dr. Hannes Nel

I could live for ever just seeing, hearing, tasting, touching and smelling things.

Astronomers must have a wonderful time trying to figure out the universe.

As do microbiologists trying to make sense of the micro world.

They, and all the natural and social scientists between these two extremes can use observation to collect data for research.

I discuss direct, indirect, structured, semi-structured and unstructured observation in this article.

In a way, all data collection techniques involve observation of some kind. Observational research methods refer to a specific method of collecting information that is different from interviews or questionnaires. As a technique for collecting information, the observational method relies on seeing and hearing things and recording those observations, rather than relying on a subject’s self-report responses to questions or statements. You can also use your other senses to observe things.

The role of the observer is to remain detached from the group or process, and thus act as an observer only. You may, for example, wish to study the way students express their dissatisfaction with study-related issues by observing what they do and how they behave in such situations. You, as the observer, must not participate in the activities but rather just observe and record the information (an etic approach). It is, however, also possible to observe from the inside, i.e. as a member of the target group being observed (an emic approach).

Your role as an observer depends on the degree of inference or judgement that is required. At an extreme, you may make high inference observations, which require you to make judgements or inferences based on the observed behaviour.

What is recorded with high inference observation is your judgement as the observer. For example, a high inference observation of a teacher would be a rating made by the principal on factors such as classroom management, facilitation skills, enthusiasm, etc. You need to summarise the main points made or main developments at the event that you are observing. The principal would observe the class and make a rating of excellent, good, fair, or poor on each of the criteria measured.

Low inference observation, on the other hand, requires the observer to record specific behaviour without making judgements in a more global sense. Thus, the principal might record the number of rebukes or cues used by the teacher as information that is used subsequently to judge classroom management. Low inference observation usually is more reliable, but the approach that you follow will largely depend on the purpose of the research. Whatever the purpose of the research, it is important to report all observed outcomes as accurately and impartially as possible. It will mostly be necessary to present critical comment on strengths and weaknesses of the event, supported with reasons.

Observation always takes place in a specific context, with the result that different observations made at different locations and times will seldom deliver the same results. Such scenarios will mostly be one of the following five possibilities:

  1. Direct observation versus indirect observation.
  2. Structured, semi-structured and unstructured observation.
  3. Participant observation versus non-participant observation.
  4. Overt observation versus covert observation.
  5. Self-observation versus observation of others.

I will discuss the first two (direct observation versus indirect observation and structured, semi-structured and unstructured observation) in this article. The remaining three scenarios (participant observation versus non-participant observation; overt observation versus covert observation and self-observation versus observation of others) in the second part of the articles on observation.

Direct observation versus indirect observation.Direct observation is observation that takes place during fieldwork. As such it offers you the opportunity to gather ‘live’ data from naturally occurring situations. The use of direct observation has the potential to yield more valid and authentic data than would be the case when making use of any ‘indirect’ source of information.

Field observation is fundamental to most qualitative research – direct, eyewitness accounts of everyday social action and settings taking the form of field notes. Field observation is especially favoured by research based on ethnomethodology. Qualitative field observations are detailed descriptions of events, people, actions, and objects in settings.

Field observation is used in interactive data collection, such as participant observation and in-depth interviewing. In the former, you will rely on careful observation as you will initially explore several areas of interest at a site, selecting those to study in detail, and searching for patterns of behaviour and relationships. In the latter, you will note the nonverbal body language and facial expressions of the interviewee to help interpret the verbal data.

Indirect observation would be observation that takes place in unnatural, artificial settings. An unnatural setting would, for example, be observations in a laboratory, observation of video footage, photos, etc.

Direct observation coupled with indirect observation, for example video and audio recordings that you took, provide ‘permanent’ evidence of an event, facts, action or phenomenon. Some people would rather be observed than to complete a questionnaire or answer questions during an interview. Furthermore, the duration of observations can be measured quite accurately when it is necessary, for example when it is important to know how long an individual spoke, a crowd rioted, etc.

Video recordings of observations can also show body language, facial expressions, tone of voice, extreme (or not) reaction to a question, attack, insult, etc. You can also test your interpretation of your observations by asking others to air their views or perceptions of what you video recorded. Video recordings can be replayed as many times as you wish.

Video recordings are not without challenges. Lack of control when observing and recording a natural setting may limit the value of your observations. What happens ‘outside’ the picture can often shed a completely different meaning to the images than what you see. Measuring lengths, heights, distance and width can be difficult if you do not have known images in the footage.

Structured, semi-structured and unstructured observation. A highly structured and systematic observation is based on proper and detailed planning. It can also be pre-ordinate, meaning that you will decide in advance what kind of pictures you will be looking for. In this instance you will already have formulated your hypothesis, problem statement or problem question so that you will know what kind of data you need. Collecting information in image format systematically means that you should work according to your plan, which might include venues, time, type of images to collect, etc. Structured observation is often directed at collecting qualitative data although the collection of quantitative data is also possible.

A semi-structured observation will be based on some planning, possibly even an agenda or at least a list of the images that you need. Your modus operandi, i.e. the way in which you will seek for and collect images, might well be haphazard, hoping that you will have some luck in finding what you are looking for. In this case you might have a hypothesis, problem statement or problem question although collecting images might trigger an issue to conduct research on.

An unstructured observation would be where you do not quite know what kind of images you are looking for. In this instance you will probably work in an unsystematic manner, relying on coming across useful images by chance. You might, for example, happen to have your video camera with you when something happens that you can use in your research. In this case you might not even have decided to embark on research yet. The image or images that you come across might trigger in your mind the need for research. Therefore, you will only now formulate a hypothesis, problem statement or problem question.

Summary

All data collection techniques involve some observation.

Observation relies on what you become aware of through the senses.

As an observer you will mostly remain detached from the target for your research.

It is, however, also possible to observe an event while participating in the activity.

You can act as an observer to make high or low inference observations.

In high inference observation you will need to make judgements or inferences based on your observations.

In low inference observation you will record your observations of specific behaviour without judgement.

You must always report all observations relevant to your research as accurately and impartially as possible.

Observation always takes place in a specific context, or scenario.

Scenarios for observation can be:

1.         Direct observation versus indirect observation.

2.         Structured, semi-structured and unstructured observation.

3.         Participant observation versus non-participant observation.

4.         Overt observation versus covert observation.

5.         Self-observation versus observation of others.

Direct observation is observation that takes place during fieldwork.

Indirect observation takes place in unnatural, artificial settings.

Direct observation coupled with indirect observation provide ‘permanent’ evidence of an event, facts, action or phenomenon.

Structured observation is deliberately decided on and planned.

Some planning is needed for semi-structured observation.

You might, however, identify and select images haphazardly as and when you come across them.

An unstructured observation is where you do not plan the observations.

You will observe events and phenomena that you come across by chance.

Close

I will discuss participant observation versus non-participant observation; overt observation versus covert observation and self-observation versus observation of others in the second part of my articles on observation.

Enjoy your studies.

Thank you.

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ARTICLE 80: Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods: Interviewing Part 4 of 4 Parts: Conducting Interviews and Group Discussions

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Written by Dr. Hannes Nel

This article applies to one-to-one interviews as well as focus groups, which are just another variation of the interview.

I discuss several practical hints on how to conduct an interview.

Most of the hints deal with simple, perhaps even obvious issues.

However, your interview can easily fail if you don’t pay attention to the minor details.

Appearance is important when doing an interview. It is best for you, as the interviewer, to dress according to existing norms or in a fashion similar to the respondents, and not in a way that may lead the respondent to think that you represent a particular point of view, value system or institution. You need to be friendly, relaxed, and pleasant. Show an interest in the welfare of the respondent. Spend a few minutes with small talk to establish a proper relationship. To provide honest answers to questions, the respondent should feel comfortable in your presence. Appropriate appearance and demeanour provide a basis for establishing a comfortable relationship and rapport with the respondent.

Of course, you and the respondent should introduce yourselves if it is the first time that you are meeting. Before asking specific questions, you should briefly explain the purpose and scope of the interview. You should also explain to the respondent what you plan to use the information for. In practice you would already explain the purpose of the interview to the respondent when you approach him or her to ask for an interview. You should also give the respondent an opportunity to ask questions and to raise any concerns that she or he might have. The respondent should be allowed to question the purpose, scope and uses of the interview or discussion.

It is necessary to prepare an interview schedule as well as your interview questions, and then to address the questions in the words indicated on the interview schedule. Do your best not to rephrase questions, because this can spoil the consistency of your data collection process – it might not be possible to realistically compare information obtained with differently phrased questions posed to different respondents. Even so, you need to be ready to provide alternative explanations of questions if the respondent does not understand and asks for an explanation.

Conduct the interview in a professional and courteous manner and show sensitivity to issues of race, class and gender. Read questions without error or stumbling, in a natural, unforced manner. To accomplish this, you need to prepare thoroughly in advance and to practise asking the questions aloud so that you will be familiar with the questions.

It is important to take notes as the respondent answers your questions. This can be done by making an electronic voice recording of the interview, even though some people feel uncomfortable “talking to a machine”. Written notes can also be effective, although it can break your concentration and it is difficult to write everything at the speed that some people talk. Recording the answers electronically is generally most useful with open-ended questions, and such questions should be asked using clear language. Open-ended main questions can be supplemented with secondary questions which probe the respondent’s responses.

Probing for further clarification of an answer is a skill that, if misused, can lead to incomplete or inaccurate responses. You should allow sufficient time for the respondent to answer your questions without interrupting or cutting responses short. Probes should be neutral so as not to affect the nature of the response. You can write probes next to your main questions while doing the interview or in advance, so that you will have enough time to plan the probes well.

It is important to strictly manage the time spent on the interview. You might invoke negative responses to your questions if you make an appointment for thirty minutes and then keep on asking questions after an hour. On the other hand, spending too little time and rushing through the interview might lead to you not obtaining the data that you are looking for, so you will waste time rather than to save time. It might be necessary to remind the respondent of the purpose and scope of the interview from time to time just to make sure that she or he does not digress too much, thereby wasting time on irrelevant topics.

An interview should be prepared and conducted in such a manner that the flow of valid and reliable information is maximised while distortions of what the interviewee knows are kept to the minimum. The challenge in interviewing lies in excavating information as efficiently as possible, without contaminating it. To achieve this, you should formulate reliable questions and provide an atmosphere conducive to open communication. The following are some of the most popular interviewing techniques:

  1. Interviews may take place face to face or at a distance, e.g. over the telephone or by email.
  2. Interviews may take place at the interviewee’s or interviewer’s home or place of work, in the street or on some other ‘neutral’ ground.
  3. At one extreme, the interview may be tightly structured, with a set of questions requiring specific answers or it may be open-ended, taking the form of a discussion. In the latter case, the purpose of the interviewer may be simply to facilitate the subject’s talking at length. Semi-structured interviews lie between these two positions.
  4. Different forms of questioning may be practiced during the interview. In addition to survey questioning, you can also have classroom, courtroom and clinical questioning, as well as personal interviews, criminal interrogation and journalistic interviewing.
  5. Prompts, such as photographs, can be useful for stimulating discussion.
  6. Interviews may involve just two individuals – you, as the researcher, and the interviewee, or they may be group events (often referred to as focus groups), involving more than one subject and/or more than one interviewer.
  7. The interviewee may, or may not, be given advance warning of the topics or subjects to gather any necessary information.
  8. The interview may be recorded in a variety of ways. It may be electronically copied, or the interviewer may take notes, or one person may take notes while someone else asks the questions.
  9. Interviews may be followed up in a variety of ways. A transcript could be sent to the interviewee for comment. Further questions might subsequently be sent to the interviewee in writing. A whole series of interviews could be held over a period, building upon each other, or exploring changing views and experiences.

After asking and having all your questions answered, you should thank the respondent and allow time for him or her to make comments or suggestions regarding the topic of the questions or the interview in general. It is important to end the interview on a positive note. Sum the interview up for the participant to confirm or amend conclusions.

Finally, you need to go through the interview recordings and/or notes as soon as possible, while they are still fresh in your memory. You need to process and analyse the responses so that you will be able to report the outcomes of the interview accurately to the relevant person.

Summary

You should do the following when conducting an interview:

  1. Dress in a non-intimidating manner.
  2. Adopt a friendly, relaxed and pleasant attitude.
  3. Introduce yourself.
  4. Explain the purpose of the interview.
  5. Tell the respondent what you will use the data for.
  6. Allow the respondent to introduce him- or herself and to ask questions.
  7. Prepare well for the interview.
  8. Conduct the interview in a professional and courteous manner.
  9. Take notes during the interview.
  10. Strictly manage the time for the interview.
  11. End the interview on a positive note and thank the respondent.
  12. Work through your notes as soon as possible after the interview.

You can achieve flexibility in your interview through the following:

  1. The interview can take place face-to-face or online.
  2. The venue for the face-to-face interview can be your home, office or any other suitable and safe place.
  3. The interview can be structured, semi-structured or unstructured.
  4. You can use different forms of questions.
  5. You can use prompts to stimulate discussion.
  6. Interviews can involve one respondent or a group of respondents.
  7. The interview can be recorded in a variety of ways.
  8. Interviews can be followed up in a variety of ways.

Close

There are three issues that are critically important for the success of an interview.

They are a positive attitude, proper preparation and professional execution.

If you pay attention to these three issues, you should succeed in gathering the data that you need for your research.

Good luck with your studies.

Thank you.

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