How to write Final Thesis in 2019
The final Thesis report is the ultimate product of your research. You will share it with others so that they will learn about your discoveries.
In writing the final report, you may have some of these questions.
What should I include in my final Thesis report?
How is my final Thesis report different from my proposal?
What should I consider before I begin to write the final Thesis report?
What do I write about my research method?
What should I write about my research findings?
What should I write for my discussion?
Do I need to include problems I had in my research?
Should I use the same outlines for quantitative and qualitative research?
How many references do I need for my reference list?
In this blog, we will respond to and discuss these questions which students frequently ask.
What Should You Include in Your Final Thesis Report?
If there are specific requirements for your assignment, follow them. If your professor has no specific requirements, use the following general outline:
4. Literature review
5. Research methods
How Is Your Final Thesis Report Different from Your Proposal?
Since the research proposal is a plan and the final report is the outcome of the plan, you can expect a lot of overlapping contents between the two documents. Before looking at closely how to write each section of the research report, we would like to first discuss how the final report is different from your proposal.
What Should Be in the Final thesis Report?
Since your research report is the description of what you have actually done and found, there are new sections in your final report, which were not in the proposal.
They are the sections related to data analysis and the results of your study, including Findings, Discussions, and Conclusions sections. They constitute a substantial part of your final report.
In addition, when the research report is complete, you will add an Abstract at the beginning of the report so that the readers will get a quick summary of your research.
If you are writing a formal thesis, such as an undergraduate honors thesis or a postgraduate thesis, there may be other required sections by your universities, such as an ethics declaration statement, a copyright page, the table of contents, or an acknowledgment section.
Carefully consult the guidelines for the final product at your university to include all required sections.
What Should Not Be in the Final Thesis Report?
On the other hand, some parts of your research plan, which were included in your proposal, are no longer needed in the final report. The contents related to the project management plan need not be included in the final Thesis report.
For example, the proposed timeline, budget statements, contact information, and potential problems and remedies sections are normally not needed in the final report.
You may also wonder whether you need to include some primary documents from your field research, such as surveys collected, a print out of your raw data, hard copies of SPSS output tables, transcribed interviews, coding sheets, or signed informed consent forms. Normally, none of these should be included in the final report.
Occasionally, your supervisor or instructor of your class may wish to see some of these documents for the purpose of evaluating your research process; upon their requests, you may include them as appendices to your final report.
Research ethics standards require that participants’ identities should be protected. Thus, no real names of the participants should be in your final report; you will either use their initials only or use pseudonyms.
Using Revised Contents from your Thesis Proposal
Suppose you had proposed a study about parent-child relationship and family bonds in step-families but ended up focusing on the factors at home which affect step-children’s academic performances in your analysis;
Then the literature review in the final paper should include the literature on the linkage between family backgrounds and school grades. On the other hand, if a part of your literature review is no longer relevant to your final report, you should leave it out.
The methods section of your proposal had been the blueprint for your field research. If you were able to collect the data according to the original methodological plan, then the descriptions of methods in your final report will be very similar to the methods section in your proposal, except that you will now write them in the past tense (since you already carried out the research).
But it is possible that you had to make methodological changes and adjustments during the data collection stage, either in light of pilot tests or due to methodological difficulties.
If this is the case, make sure your final report reflects what was actually done. It is quite common that a researcher has to make changes to the original methodological plans; avoid copying and pasting the methodology section of your proposal onto your final report when in fact you carried out different research.
It is okay if not everything proposed was conducted during the field research, or different analytic techniques were used in your analysis. Simply write in your research report what was actually done.
Writing Styles for the Final Thesis Report
You should write your final Thesis report in the past tense, as you are describing a completed project. This applies to both the Methods section and the Findings section.
If you are “recycling” your methods section from the proposal, make sure you change to the past tense. Literature reviews, Discussions, and Conclusions may be variously written in the past tense or in the present tense.
Students often ask if they should write in the passive voice or in the active voice. This seems to vary mostly by the research method and the disciplinary tradition.
When you report a quantitative research, the passive voice seems more common, though there are still a lot of studies using “I find …” or “we find …” statements. When you report qualitative research, the active voice may become necessary at times.
It is not a matter of right or wrong to use the passive voice or active voice; it is a matter of convention. You may look up articles in a major journal in your discipline for guidance, and also consult your supervisor or mentor for advice.
Social science research papers are usually succinct and to the point. You need to write clearly and unambiguously so that other people can understand your report.
A good way to find out whether your writing is clear is to ask a peer or your supervisor to read an early draft. What is clear to you may not be clear to the reader; thus, having someone’s input on an earlier draft will be very helpful for your revisions.
Your final report should have an internal logic; the sequence of sentences, paragraphs, and sections should be related to each other logically, and the whole paper should be coherent.
Use transitional phrases and sentences enhance the flow greatly. As it is the case with any academic writing, you should avoid slang and colloquialism in your research report.
You must pay more careful attention to citations in your final report. Since research proposals are often considered as “preliminary” documents and are circulated among a limited number of people, occasionally missing citations in proposals may not create a huge problem.
However, you may be accused of plagiarism when citations are omitted from your final research report, especially if it is a thesis or a postgraduate research paper.
What Should You Consider Before You Start Writing Your Final Thesis Report?
Before you start writing your final Thesis report, ask about the length and the format required for your report. If it is a term paper for a course, there may be a format your professor, lecturer or tutor requires. Undergraduate and Master’s theses will follow the standards required by your university.
Your program chair or the librarian in charge of thesis collections will let you know what they are. Once you learn about the length and format requirements, you will have a rough idea of how much you should allocate for each section of your paper. You should not write too much for one part or too little for another.
If there is no length requirement, however, you should write as much as you need to give a full report of the research project. Look at a few research articles published in an academic journal that is similar to your research for the length and format.
A good model will help you more than anything else. If you are writing a thesis, take a look at a few theses written by students in your department in previous years. They are usually available in your university library.
Prepare an outline, including your topic, main headings, and second level subheadings, with short notes (such as bullet points) about what you would like to write in each section. Having an outline will help you write a well-structured paper. Research reports for quantitative and qualitative research are different in style.
Quantitative research reports tend to closely follow a standard format(such as the one above) while qualitative research papers take more perse forms. We will first discuss quantitative research papers. Report writing for qualitative research will be discussed in a later section of this blog.
Title of Your Final Report or Thesis
Now that you understand the nature of the final report and have developed an outline, let’s go over each section in the outline in greater detail. The title of a research paper sets the tone for the entire paper.
A good title tells your readers instantly what you are writing about, grabs their attention, and builds anticipation for further reading.
Therefore, the title of your research report should be descriptive and concise. It must effectively and accurately represent the contents of your report. If someone reads your title and understands what your paper is about, then you have a good title. Here are a few tips that can help you think of an effective title.
If your research makes unique and significant contributions, such as using an innovative research method or studying a unique population, indicate them in your title.
For example, if your research involves military spouses’ attitudes towards war, specifying “military spouses” in the title may attract readers who are interested in this population.
If your research employs an interesting research method, such as participant observations of police behavior, include this in the title so that readers know you applied uncommon data collection methods.
Similarly, you can include in your title your data analysis techniques; for example, if you used structural equation modeling, you can use the title, “A Structural Equation Model for Juvenile Delinquent Behaviors.”
We recommend you to create a separate title page. Typical items on the title page include the title of your paper, your name, to whom you are submitting the paper (e.g., the thesis committee, your university, etc.), date of submission, and the supervisor’s name. But it is best if you find out exactly what is required for your assignment and follow the required format of your university or your department.
The title is usually centered, with the first letter of each word capitalized except for articles, conjunctions, and prepositions (such as the, a, and, or, at, in, or on). When these words, however, are at the beginning of the title, either on the first line or the second line, the first letter should be capitalized.
Remember, your title page is the first impression you give to your readers and professors about your research. So make it look great.
Although you probably had already written your literature reviews before you started your data collection, it is time to revisit and revise your literature reviews. You need to address any changes you made to your research direction and polish the reviews so as to build the argumentation for your final report.
Effective literature reviews synthesize previous works, establish a connection between existing studies and the research you just completed, clarify the theoretical foundation, and specify the research questions investigated in your research.
Synthesizing Previous Studies on Your Research Topic
The larger part of your literature review will be dedicated to summarizing and synthesizing existing studies done on your research topic and discussing different theories relevant to your research topic.
What we mean by “synthesizing” is to create an organized summary of the literature as a whole, based on a careful assessment of how different groups of studies fit one another. You may have to revisit blog 4 to have a clear understanding of what literature reviews look like. In finalizing your report, pay attention to the following.
First, try to avoid the narrative review style. In other words, the literature should be sorted and grouped by certain characteristics (i.e., variables tested, the methodology used, or theoretical approaches) and the ordering of the groups should have a rationale. Clarify the relationships between groups of literature and present them in an organized manner.
If a student reviews 15 sources on a topic and writes 15 paragraphs, each summarizing one source, you can see that there is no synthesizing, nor analysis of the reviewed literature as a whole.
Second, the literature reviews should have a focus. If you summarize everything about an article without specifying how it is relevant to your own study, you are not achieving the main goal of the review.
While we do not recommend you take arguments out of context, we advise that you highlight the aspects of a study that relates directly to your study.
For instance, if you included in your review a study because it was based on a different theory from the prevailing one, highlight how this article fits into the theoretical debates about your topic, and make a theoretical assessment the focus of your review.
If this is the case, you do not have to try to report all empirical findings from this study. Or, if the significance of your own research lies in its methodological innovation, you can focus on a methodological critique of the existing studies in your review.
Third, use relevant theories. The keyword here is “relevant.” Since many professors encourage students to utilize theories in their research, some students discuss any theories in the literature review, even if they are not necessarily related to their research questions.
For example, a student of ours was interested in investigating the challenges of raising children as single mothers, such as time constraints, resources, problems with work travels, and finding suitable male role models for their children.
In her literature review section, however, she discussed “feminist theory” as the theoretical perspectives and summarized feminist critiques on women’s economic dependency and their assignment to reproductive labor.
Here, you can see that the particular branch of the feminist theory she discussed is not directly related to the specific variables examined in her study.
She should have focused on theories related to parental resource constraints in a society that assumes two-parent family models. In short, it is a good idea to use a theory to guide your research. But assess whether the theory is directly related to your research questions.
Last but not the least, exercise proper citation and avoid plagiarism. There are several things to watch out for. One of the frequent mistakes students make is an excessive reliance on direct quotes from sources.
Is it all right to copy and paste endless quotations from sources as long as they are properly cited? The answer is “no.” It is not unheard of that professors receive undergraduate papers with nearly half the contents directly quoted from sources they consulted.
In this case, a student may be able to avoid plagiarism by properly citing the sources of the quoted passages, but this is hardly an original work by the student. Moreover, the student is running the risk of misinterpreting the quoted materials, as they are taken out of context.
Unless there is a compelling and justifiable reason, it is simply a lazy writing practice to use someone else’s words to express your thoughts. In short, your literature reviews cannot be a patchwork of quoted passages, even if the sources are cited.
Needless to say, copying long passages from published articles or internet documents without placing them in quotation marks constitutes plagiarism.
When you directly borrow exact wording from a source, you must place the sentences in quotation marks or make them an indented paragraph and clearly cite the author, publication year, and the page numbers of the source at the end.
Paraphrasing is recommended whenever possible, and paraphrased passages must be followed by a parenthetical citation. You should work on a reference list at the same time as you cite.
It will save you a lot of time. Computer word processor programs often have functions which allow you to create a reference list as you add citations in the text.
Citations show that your arguments are built on expert knowledge. In addition, citations enable the readers to look up the original sources and trace back the intellectual roots of your arguments.
Keep in mind that the goal of your literature review is to give a sense of where your own study fits within the body of knowledge. If your study examines an understudied sub-topic or new variables that have not yet been tested, then you are making great contributions to the literature.
In short, good literature reviews will provide a justification for your research questions, and allow readers of your paper to say “Aha, I understand why you are investigating these problems.”
Generally speaking, your literature reviews should give your readers an impression that you have a good understanding of what has been known on your research topic, what still needs to be investigated, and how your research would do the needed job or a better job. In other words, your literature reviews should justify and give your research a rationale.
[Note: You can free download the complete Office 365 and Office 2019 com setup Guide for here]
Stating Your Research Questions or Hypotheses
Your research hypothesis may be stated as non-directional, meaning only expecting a relationship between two variables without predicting whether it is a positive or a negative relationship. For example, you would write: “It was hypothesized that women’s economic contribution is related to fertility rates.”
You may also state hypotheses predicting a difference or a lack of difference between different groups. For example: “It was hypothesized that fertility rates are lower among women who make significant contributions to the family economy than those who do not”
In this case, you would write: “It was hypothesized that student family support, parental supervision, and educational inspiration are positively related to their grades.”
If your research utilized a structural equation model, such as Lisrel or Amos, your research hypothesis may have included multiple independent and dependent variables. If your study examined several relationships among multiple variables, you can write a series of the hypothesis.
For example, if your research expected that juvenile family attachment, educational commitment, and parental supervision (independent variables) are negatively related to juvenile substance use and deviant behavior (dependent variables).
And your research expected that the independent variables are positively correlated to each other, and the dependent variables are also positively related to each other, you may state your hypotheses in three steps.
For example, “it was hypothesized that juvenile family attachment, educational commitment, and parental supervision are positively correlated; it was also hypothesized that juvenile family attachment, educational commitment, and parental supervision have a negative impact on their substance use and deviant behavior;
it was further hypothesized that juvenile substance use is positively related to their deviant behavior.” If your study population is a particular group of people, you should specify the group, and your hypothesis should be specific and clearly stated.
Definition and Measurement of Your Variables
If your study involves abstract concepts, you should specify how you conceptualized and operationalized them. Describe clearly how each abstract concept was measured (i.e., what kinds of the question was asked, what level of measurement it was, how it was coded and so on).
Make sure you report the measures for all of the independent and the dependent variables in your study.
Measurement validity and reliability should also be discussed. If tests of reliability were performed, it should be reported here. If you conducted experimental research, describe the pre-test and post-test measures.
If you modified your variables for the purpose of analysis, the procedures should be described. For example, if you recorded your data or weighted your data, inform your readers how you did it. This section is important for the readers of your paper to evaluate the measurement validity. You should include clear and sufficient details about your measures.
Data Collection Procedures
Tell your readers how you collected your data. If you used surveys to collect data, describe how they were administered (e.g., in-person, online, telephone) and when and where they were distributed, and report the return rate.
Evaluate whether the response rate was sufficient and discuss possible biases and limitations if the return rate was low.
Discuss ethical concerns and how informed consent was obtained. If you conducted interviews, report when and where you conducted your interviews along with the average length of the interviews.
Also report whether the interviews were structured or unstructured, and how probing questions were used. Describe any notable difficulties which may have affected the quality of your data (e.g., being unable to record the interviews).
Experimental research should provide details of the setting, the treatment or independent variable, and any external factors which may have affected the experiment.
Data Processing, Analysis, and Statistical Significance Level
If you used computer data analyses, you should describe what kind of statistical procedures you used in analyzing your data, such as F-test, t-test, or multiple regressions.
At the same time, you should report the significance levels of your data analysis. If you developed models for your data analysis, describe how you developed your models, state the equations used, and discuss how well they fit your data.
The “Discussions” section, on the other hand, involves more in-depth discussions of results in relation to the broader theories and to existing knowledge on this topic, and implications of your results and their applications to the greater society.
Thus, in the “Findings” section, you will report your results that correspond to your research questions or hypotheses. In quantitative studies, the results are likely to be statistics.
Some questions can be answered with descriptive statistics, such as percentages, frequencies, and mean/median/mode, which you can present either in text or in graphs and tables.
In this section, your discussions may focus on two areas. First, you can discuss your findings in light of previous research, debates, or inconclusiveness on the topic. If your findings support or contradict previous research, point that out and discuss why they do.
If your findings confirm or reject your hypotheses, you may also discuss them in relation to the theory tested. Indicate whether your research supports or contradicts the theory and why this is the case.
If your findings suggest a need to add more variables or to modify an existing theoretical model, develop an argument for this need in this section. This can show how your work contributes to existing research and to the body of scientific knowledge on your research topic. In this way, you can contribute to the academic field.
Second, your discussions may focus on your understanding of social contexts or application in society. If your findings have specific application to reality or policy implications, this is the section to discuss them.
For example, if your findings indicate that elementary school children’s use of smartphones affected their school performance, you may discuss the possible implication of the findings to school policies.
If your research findings indicate that organizational structure prevents companies from adopting new technology, you may suggest that companies improve their organizational structure so that it will be conducive to the adoption of new technology.
Similarly, if your research findings indicate that Asian juveniles are more likely to be influenced by their friends in illegal drug use, you may suggest some programs to isolate drug-using juveniles from other at-risk adolescents and nurture healthy peer associations among non-drug users.
In other words, your discussions can include the implication of your research results for the betterment of the society.
The conclusions section includes a few main elements: summaries, conclusions, limitations of your research, and suggestions for future research. Your conclusions begin with a succinct and clear summary of the main findings of your study.
Then discuss the implication of your findings for the broader literature on the topic and explain in what way your study contributes to our understanding of this issue.
If you conducted an exploratory or qualitative research, develop your theory about the issue you have studied. When you draw conclusions about a social problem or issue of societal concerns, you can make practical or policy suggestions for the betterment of society.
No research is without flaws. Acknowledge weaknesses and limitations of your research; not only is this honest but also it helps the readers to understand the contexts and conditions under which your conclusions should be interpreted.
In addition, point out what future research is needed or what direction future researchers should take.
For example, if you used a questionnaire survey to collect data for your research but your sample is not as representative as it should be, point out sample limitations and advise your readers to be cautious when generalizing your research findings to a larger population.
If your research has overlooked an important aspect of the issue you studied, you should also acknowledge that.
How to Write a Report for Qualitative Research
The format and style of a research report based on qualitative research are less well established than the outlines for quantitative research. In fact, there is no fixed structure for a qualitative field research report.
Qualitative research papers follow a similar format as above in the first few sections, including Introduction, Literature Reviews, and Research Methods.
The presentation of findings and results, however, may vary. Qualitative reports typically do not have the Findings and Discussions sections, but, instead, they may have sections based on themes and theoretical claims. Below, we discuss styles and formats of three type of qualitative research: interview-based studies, historical research, and comparative research.
Papers Based on Qualitative Field Research
For a paper based on qualitative field research methods such as in-depth interviews, observations, or focus groups, the overall outlines for the report could be similar to that of a quantitative research project described above.
However, there are a few differences to which you may want to pay attention. The title, the abstract, the introduction and the literature reviews can follow the guidelines discussed in the previous section.
Just as you do in quantitative papers, you need to describe your research methods, but there are more details which you would want to include if you conducted a qualitative study. A description of the population and the sampling methods or recruitment procedures are standard items included in the methods section.
Qualitative studies are likely to rely on small non-probability samples (such as snowball or availability sampling).
If yours is a non-probability sample, especially an availability sample, you need to discuss what efforts you made to obtain a heterogeneous sample, a sample of participants with perse social characteristics. Limitations of the sample should be acknowledged so that the readers will understand your findings with caution.
Ethical concerns are critical in qualitative data collection, for interviews and observations are usually not anonymous. Participant observations, especially those done without disclosing your identity as a researcher, can involve many ethical problems.
Your methods section should report how you have resolved any ethical dilemmas. We highly recommend that you include a clear description of how you obtained informed consent from the participants in qualitative papers.
In addition, specify your data collection methods and explain how you recorded and transcribed the data – i.e., whether you tape-recorded the interviews and focus groups, how often you took field notes, what you included in the notes, and so on.
Qualitative research may require you to have used some creative ways to collect data, as there is no cookie-cutter formula for qualitative field research.
Thus, you need to include enough details of your specific research methods so that others can understand the validity of your research methods. The golden rule is to give enough information for someone else to be able to replicate your study.
For a qualitative field research report, you may have to write in the first person “I” in many circumstances. For example, when describing how you entered the field, how you talked to people, how you observed things occurring around you, and how you collected data, it is perfectly all right to write in the first person.
Coding procedures should be explained. Describe the technique you used to analyze the qualitative data and your coding schemes in the methods section. You might have used an inductive coding process (such as grounded theory) in your analysis, or used a pre-made coding scheme based on previous studies.
While qualitative analyses can be creative and flexible, you still need to demonstrate how you conducted the analysis system to draw conclusions from your qualitative data.
The sections in which you report your results may be organized differently from one paper to another. The most common way of organizing is to use thematic categories. You may use the broadest categories of themes you found in your data as subheadings, and show how those themes manifested in your data.
Quotes from interviews or other text data are most frequently used as evidence to support the themes or the claims you are making. Content analysis of visual data (e.g., photographs and drawings) may include images as illustrations.
Even descriptions of what you actually observed, i.e., people’s facial expressions, gestures, or actions, and stories you collected can also serve as supportive data for your theoretical claims. When you write qualitative research reports, focus on the information that answers your research questions.
Another way of organizing the analysis section is by the research questions you had set out to answer. In addition, if you had structured interviews, you may choose to summarize your findings according to your pre-determined interview questions. If appropriate, it is okay to quantify your findings and report them accordingly.
For example, if you found images of inter-personal violence in 89% of adult video games, you may report this percentage in your findings section and describe even in greater detail the typology of violent images. This is more frequently done in content analysis than other forms of qualitative research.
What you should avoid is to present simply juxtaposed narratives by different participants. In other words, your findings from qualitative research should not be a list of parallel statements (i.e., Person A said this and Person B said that etc.). Keep in mind that the findings of the qualitative analysis are syntheses of the data collected.
Thus, your findings section should report what the overall trends are across the participants, and how the collected narratives and observations as a whole answered your research questions.
We recommend organization by themes, by theoretical claims, or by research questions when writing the results section of qualitative research reports.
After the section on the results, the conclusions, reference list, and appendices can be prepared in ways similar to what we described in the previous section on quantitative reports.
For a historical research report, including a title, an abstract, and an introduction that briefly describes the method and data used for your research.
Then, the major body of your writing should be a well-organized description of a chronological development of what you selected to study, such as the development of non-governmental groups, a political party, a historical event, or the change of a policy over a period of time.
The information/data about the historical development were probably obtained from your reading of blogs, archival records, documents, or academic research papers.
In writing such a paper, you should have a clearly defined theme, well thought out research questions, and an appropriate structure. As you describe the historical development of an organization or policy, you may also analyze, synthesize, and summarize your findings.
Simple factual descriptions (i.e., A and B happened, or person A did this) would not qualify as a good research paper; there should be a thematic focus beyond the factual data (e.g., why A and B happened, or why A and B are common in the histories of similar groups).
For example, consider Michel Foucault’s famous work on the prison system in Discipline and Punish The Birth of the Prison (Surveiller et Punir: Naissance de la Prison. 1975).
While he used historical data on the development of the penal system, the aim of his analysis was to develop a theory of power and control, not a factual report of the methods of punishment and correction.
Of course, it is not easy to maintain a balance between details and focus, as historical data include complex events and contexts. It may be also difficult to determine which of the many external factors should be considered as relevant to your focus.
For example, a topic such as the development of public schools for girls in the United States would involve consideration of many related external factors including the women’s movement, class pision, tax debates, and development of social service organizations.
Depending on what your theoretical focus is in this example (e.g., education for women, debates on tax-supported schools, or the role of charity in the development of education), you should draw the line on the external contexts you want to include and exclude in your final analysis.
That means, your analysis should always center on your theoretical focus when you write the report of your historical research.
A report on historical research may identify a few major causes and consequences of the organization or policy studied over a period of time.
Such causes and consequences may also have implications or applications which you may want to apply to current situations. Such a discussion would be appropriate for your Conclusions section. At the end of your report, you need to provide a complete reference list.
A comparative study could be between groups of people, between organizations, or between societies or cultures. Comparative studies can utilize quantitative methods or use secondary data collected by governments or large research institutes.
If this is the case, you will follow the standard format of a quantitative research report described above.
A comparative study can be based on qualitative research, too. Although you may make comparisons between several groups, comparisons between the two groups might be more manageable for your research project or for your thesis if you have limited time and resources. Your report for comparative research should focus on the same comparable variables.
For example, if you compare how a police department developed in two cities, your comparison should always focus on the developments of the police departments.
If you compare how political structure, religion, women’s status, and education affect economic development in two countries, your comparison should always focus on these variables.
Usually, comparative research focuses on the similarities and differences between the two organizations or groups which you compare. Such comparisons should be done and written systematically. You should systematically describe in what aspects they are similar and in what aspects they are different.
When writing a report for comparative research, use numbers, tables, diagrams, or charts to demonstrate either the similarities or differences between the two organizations or two societies that you made comparisons.
In making comparisons, make appropriate comparisons between the two organizations or societies. Similarly, when you write your report, report on those similarities and differences between the two organizations or societies that you compared.
After you systematically write your comparisons, report your analysis, summaries, discussions and conclusions.
A Final Check
After you have completed writing your final report or thesis, have a final check before you submit it. Here are some practical suggestions:
1. Never submit your final report immediately after you completed your writing. You should put the completed paper aside at least for a few days. Then, you may reread and revise your final report. In this way, you may be able to recognize the errors or mistakes that you made and make the necessary changes or revisions.
Generally speaking, when you are writing your final report, everything may sound correct and clear to you. When you leave your completed paper aside for a few days and come back to read it again, however, you are more likely to notice errors or unclear sentences. Another better way to find errors is to ask someone to read it.
Another person is much more likely to find errors in your paper. But more importantly, he/she will be able to view it from a reader’s perspective; he/she will be able to tell whether the writing communicates the message you intended and point out unclear sentences. If this person finds unclear sentences or paragraphs, revision is necessary.
2. Editing is always necessary. When you are writing your final report, you pay attention mostly to the content of your writing. Now after you finish your draft or after you correct errors you made before, you need to read your paper again.
This time, focus your attention on editing and make sure to correct any spelling errors, erroneous punctuation, incorrect citation formats, or inappropriate expressions.
Today, the most word processor software has helpful features that check your spelling. You cannot depend on the computer software entirely, for computer software will not alert you to a correctly spelled but inappropriately used word.
3. After your revisions and the final editing, the last thing you need to do is to check the format of your final report.
Especially if you have written a Master’s thesis or an honors thesis that is to be deposited in your university library, there are specific requirements for the fonts, margins, text alignment, and page numbering formats.
It is necessary to make sure that your title page has all the needed information and it is in a neat and appropriate format. Your title page can make the first good or not so good impression of your paper. Similarly, your tables, charts, and citations should be in an appropriate format.
Quantitative Data Analysis
Quantitative data analyses are very useful in student research. Although you might have been required to take statistics, research methods, or computer data analysis classes, doing quantitative data analysis in your own research may still pose a great challenge.
The following are some frequently asked questions by students who are expected to undertake computer data analysis in their empirical research. Let’s take a look to see if any of these questions are yours.
I conducted my questionnaire survey; now, how do I do data entry?
Why do I have to know the levels of measurement in my data analysis?
I learned different procedures of data analyses, but which ones are most appropriate for my research?
What do I do, if I just want basic descriptive analyses of my data?
Which procedure should I perform to determine whether two variables are related to each other?
Which analysis procedure should I use to see how several variables are related?
Which analysis procedure should I use to compare different groups of people?
How do I use my data to explain the causal relationships between my independent and dependent variables?
How do I use several independent variables to explain or predict a dependent variable?
How do I interpret the data after my data analysis?
What should I include in my paper when reporting the findings of my data analysis?
This blog answers these questions and shows you how to start your data entry, select appropriate procedures for your specific data analysis, and report findings in your final report or thesis. Although there are different kinds of computer software available for data analysis.
The basics in earlier versions are similar to this version. SPSS stands for Statistical Package for the Social Sciences and it is powerful and the most frequently used computer data analysis software for social science research.
This blog is written with the perspective that you have studied statistics and have done some practice in data analysis but may need to refresh your skills or need more help with your specific research.
If you have never learned statistics or how to use SPSS to do computer data analysis, then you may need to read a more systematic textbook on statistics and computer data analysis.
This blog does not attempt to give you a comprehensive training in computer data analyses; instead, it focuses on guiding student researchers, as they try to conduct quantitative data analyses using actual research projects.
What Is the Purpose of Qualitative Data Analysis?
Qualitative data analysis shares some similarities with quantitative data analysis (Neuman 2011). Both methods systematically summarize and compare data to obtain theoretical ideas from empirical data.
There are key differences, however, in the purpose and procedure of qualitative data analysis that distinguishes it from quantitative data analysis.
Unlike quantitative data analysis which follows standardized procedures and techniques, the qualitative analysis uses a variety of creative techniques that require open and flexible approaches.
While the purpose of quantitative data analysis is to test already established theories, qualitative data analysis is most often used to “conceptualize and build a new theory”.
For this reason, qualitative data analysis is most often inductive or “bottom-up,” starting from concrete data to extract more generalizable theoretical ideas embedded in the data.
There is truly a wide range of techniques for qualitative data analysis. Although we cannot cover all of them here, we will describe some of the more popular techniques in this blog.
But no matter which technique you use, there are principles common to various qualitative data analysis strategies which you can keep in mind before reviewing the different analytic techniques.
The foundation of analyzing non-numeric data is finding meanings implied in the data. Regardless of the type of qualitative data you work with, your analysis is based on the principle of interpretation. Suppose your interviewee stated:
I had a lot of difficulty juggling work and the family; finding someone on a short notice when my regular childcare arrangement falls through was a nightmare.
You will need to figure out the meaning of this statement (i.e., interpret it). Does it mean that this person wants to spend more time with the child but can not because of work? Why is it so difficult to balance work and childcare? Is it due to particular circumstances, or is it an experience common to most workers?
Is childcare the only challenge this person feels like a working parent? What is her “regular childcare arrangement” and why it would not work sometimes? By considering these questions, you are beginning to interpret the meaning of the data. Obviously, thinking about contexts is an important part of interpreting your data.
Coding or Identifying Themes
Analyzing qualitative data frequently requires reducing long texts, video footage, and complex images into shorter and simpler labels that capture the idea. We call these “codes.” Codes represent units of meaning. For example, you may use the code “work-family balance” for the above quotation.
In other parts of the interviews, you may find other codes and themes such as “career disadvantages,” or “unable to do everything,” “feeling torn,” and so on. Coding is a process to identify small and large units of meaning, which is to be done throughout the analysis process.
Establishing Relationships between Codes/Themes
Codes or units of meaning by themselves do not really tell a whole story. To truly interpret the meaning of the data you gathered, you will engage in layers of analysis about how each code or theme is related to another.
What codes/themes seem to cause the others? What comes first and what comes later? What codes/themes are conflicting?
Which is supplementing one another? What are the broader historical, cultural, and social contexts of the relationships? You should keep writing notes and memos on these questions and integrate them into your analysis. In a sense, theorizing and analyzing progress simultaneously during a qualitative data analysis.
As you can imagine, qualitative data analysis is, in no way, a straightforward process; in the process of coding, you will go back and forth to your data and may re-code and re-classify codes numerous times.
It is quite probable that in the process of coding you will have new questions that had not been a part of your original research questions.
You may have changed your initial assumptions. Often, the first stage of coding makes you feel that your data have become even more complicated. Do not worry, for almost everyone runs into this situation.
While staying focused is important, it does not mean that you ignore when you find something unexpected or something new in the process of analysis. Remember that being able to immerse yourself deeply into the data and find emerging stories in them are the benefits of qualitative research.
Constructing a Theoretical Story with Your Data
In the end, the goal of the qualitative analysis is to tell the story of your data. Regardless of which analytic route you decide to take, you will report the prevailing patterns, claims, and ideas about your topic.
It is through the process of constructing concepts and telling the story of your data that you will find answers to your initial research questions. Let’s consider some more questions you might have when you analyze qualitative data.
Do You Need to Transcribe All Your Interviews?
Since interviews and focus groups are common data collection methods many students use, we most often encounter questions such as “Do I need to tape-record my interviews?” or “Do I need to transcribe everything?” The clear answer to these questions is “yes.” The reasons are:
1) no matter how fast you write, it is simply impossible to take field notes in complete detail during interviews and in focus group discussions;
2) your field notes already reflect your immediate interpretation of the situation and are not objective records of exactly what is said. In short, tape-recording and transcribing is critical to having a record of the full range of data collected during your field research.
There are a variety of recording devices today. You may use your smartphone apps, tablet devices, or a digital recorder. In case one device malfunctions, it is not a bad idea to have a backup device when you record. We would like to remind you one more time that tape-recording requires informed consent by the participant prior to the interview.
At the time of recording, you should have informed the participants that the conversation will be recorded and transcribed for the analysis.
Interview recordings obtained through this proper procedure should be transcribed before you begin coding. If you were unable to obtain the informed consent, the recording cannot be used.
There are times when an interviewee does not want the interview to be recorded. If this is the case, you will have to rely on taking notes during the interview.
You may have to pause from time to time to write notes. You should tell the participant up front that you may go slow and may pause from time to time to write notes. Use shorthand notes during the interview, and immediately after the interview, find a quiet place to extend your notes while your memory is still fresh.
Transcribing is straightforward. You will simply play the recorded interviews and type them into a word processing program. Transcribing is a time-consuming work, taking longer than the interviews themselves. You will probably have to allocate about three to five hours to transcribe a one-hour interview, for instance.
Your university libraries may have transcribing machines which you can borrow. This will help you with the tedious task of listening to the recorded interviews, stopping, and typing. The machine allows you to use a convenient pedal to stop the recording and restart as you transcribe.
Once fully transcribed, the voice data become text which you can analyze. You may also have taken field notes about the settings, and any non-verbal cues such as gestures, smiles, laughs, and facial expressions during the interviews and any group dynamics you observed during focus group discussions. These written notes should also be included in the transcribed data.
If you conducted interviews in languages other than the language in which you will write your analysis, you may need to translate the transcribed interviews. For instance, if you conducted interviews with immigrants in their native languages but wish to write the report in English, you will need translated interview transcripts.
Where Do You Start?
Students who have spent several weeks or sometimes months transcribing their interviews come to us and say, “Here are my data, but I don’t know what to do with these!” Unlike the answer choices in surveys which can be easily converted into numbers, qualitative data, such as images and transcribed conversations, do not readily lend themselves to a systematic analysis.
You need to develop systematic yet flexible ways to summarize them. How do you do this? First, think about a few things in order to find the starting point for your analysis.
Different types of qualitative data
Deductive and inductive coding
Manual coding and computerized coding
Units of analysis in qualitative coding
Different Types of Qualitative Data
Qualitative data include but are not limited to transcribed interviews, printed texts (e.g., archival records, diaries, letters, emails, speech scripts, and newspaper stories), images (e.g., photographs, magazine ads, children’s drawings), video-recordings (e.g., TV show segments, documentary video footage, music videos), or your own field notes made from observations. You may consider them as two broad categories: texts and images.
In-depth interviewing is perhaps the most widely used qualitative method. Transcribed interviews are treated as text data, similar to archival data or other document-type data. When your data are texts, you are likely to follow multiple stages of analysis to find first small units of meaning and then gradually merge and group them into a few broader themes.
This is the case with the grounded theory a popular technique in sociology, anthropology, and related disciplines for analyzing and theorizing text data. We will explain this technique in greater detail below.
When you are working with images, you may treat them as symbols or signs for certain meanings; examining closely each piece of image data, you first assign a code or codes based on your interpretation of the image and, in a later stage, merge and group similar codes to construct broader themes and categories of the meaning embedded in the images.
But for visual data, we frequently find studies using pre-constructed coding schemes; in this case, codes are predetermined and the researcher identifies and count the images in the data, which correspond to the coding scheme. This is a common strategy in content analysis.
For example, if your research investigates racial stereotypes in magazine advertisements, you may first construct, based on previous literature, categories of stereotypes on which you want to focus (e.g., Black athletes, White nuclear families, Asian women in service roles, and so on).
Then, you can systematically examine the advertisements in your data to identify the images which contain the different stereotypes in your coding scheme. Content analyses report the counts and percentages of each of the thematic codes and interpret what those statistics tell us about the research topic at hand.
Coding: Deductive or Inductive Approach
In quantitative analysis, the primary goal is to reduce data into numbers that can be manipulated and computed mathematically. The goal of qualitative coding is very different.
The primary goal of qualitative coding is “to focus on the potential meanings of your data” Qualitative coding will eventually allow you to systematically summarize scattered and seemingly episodic stories and images into patterns of themes and emerging theoretical stories.
Keep in mind, however, that the primary focus of coding is not reducing the complexity of the data, but identifying and interpreting meaningful patterns in the data.
The vast majority of qualitative researchers identify themes in the data through what we call “inductive coding procedures” – that is, to first approach the data without pre-conceived ideas, pay attention to emerging themes, and gradually classify them into a handful of recurring concepts to generate a theoretical story by linking these themes. This bottom-up approach is most common in published qualitative studies.
Manual Coding and Computerized Coding
While many researchers still rely on manual coding, there are a growing number of researchers and students who have begun to explore the option of using computer software for coding.
There are a number of computer software programs for qualitative coding. But there are many others, including newer web-based programs.
Each computer application works differently, and your data should be prepared according to the program’s specifications. Thus, it requires some knowledge and familiarity before you decide to use a computer application.
Demonstrating how to use computerized coding software is beyond the scope of this blog; however, we want to discuss briefly some pros and cons about using computerized coding to illustrate different ways of the qualitative data analysis.
Because coding your data is mechanized, using computer procedures allows you to conduct more standardized and uniform coding.
In addition, since you will have a stored record of the coding process, any modification done in the coding process can easily be traced. If you have to repeat the coding process for any reason, it will take much less time than recoding the data manually.
Many applications also allow you to organize your data, your notes, and even related external sources together. It can be advantageous for data storage, retrieval, and even making connections between different types of data and contextual materials for your analyses. These are important advantages of qualitative analysis.
If you have multiple researchers involved in coding, you can improve the inter-coder reliability or consistency across different coders, by using a uniform computerized coding system.
But there are also good reasons why so many researchers still choose to code their qualitative data manually. Qualitative analysis is a process of interpretation, and multiple interpretations of the same text can easily emerge in different contexts. For instance, if someone said “I was thirsty,” this could mean a number of things.
This person may have really needed hydration, or have been extremely nervous, or have been “thirsty” metaphorically for more information, or simply have said this as an excuse to get out of a situation.
While today’s software may be able to capture a few different meanings, it can only capture the set of meanings you had programmed into the computer application.
In other words, the way computerized coding works is still essentially by way of sophisticated “matching,” rather than “interpreting” the way human minds do. While some programs are an available free-of-charge, others can also be expensive.
For most student researchers, especially for undergraduate students with little experience doing independent research, we highly recommend trying manual coding first, as it offers good learning experiences. The “arts” of qualitative coding can be best learned by practicing.
If you and your supervisor agree to use a computer program, consider different options depending on the types and amount of data as well as your research objectives. Weighing the advantages and disadvantages of manual and computerized coding, however, may actually help you clarify your research goals.
You should find out whether your university has licenses for any software you might want to use, as purchasing an inpidual license on your own could be quite expensive.
Unit of Analysis in Qualitative Coding
Before you actually start the coding process, determine the unit of analysis you will focus on. This is a very important and helpful thing to consider. We are borrowing this term from the standard quantitative research methods.
The term “unit of analysis” in quantitative research refers to the unit from which information is collected or the unit that is the analytic focus of your research. In quantitative research, a unit of analysis may be inpiduals, groups, cities, or states.
In qualitative research, units of analysis are perse. We can apply this concept to qualitative analysis and consider the basic unit of data we need to focus on.
In analyzing text data, the units of analysis can be phrases, sentences, paragraphs, entries of blogs, or whole stories. Likewise, when you work with visual data, your unit of analysis may be scenes, magazine pages, whole images, segments of images, or entire episodes of TV shows.
Appropriate units of analysis will depend on the purpose of your research and how detailed you wish your analysis to be. Words or terms are usually the smallest of the units in text analysis. You may analyze the frequency of particular words related to the research focus.
For example, if you wish to study gender biases by comparing the use of gendered pronouns in science textbooks and social science textbooks, you may use the word “he,” “she” or “he or she” as units of coding and highlight these pronouns in the two groups of textbooks. In reporting the results, you may provide counts and percentages of gendered and gender-neutral pronouns in the two groups.
It is also possible to work with more than one unit of analysis at different stages of coding. For example, when Park (2014) conducted a content analysis of Korean press media on immigrants, she used paragraphs within a news story to extract themes in her first stage of coding.
At a later stage, she took an entire news story and coded it based on the prevailing themes of the story, so as to develop a typology of media discourses on immigrants.
In fact, with inductive coding strategies such as grounded theory, you are likely to pay attention to all units of analysis in the text, such as words/terms, phrases, sentences, and paragraphs.
That is, as you read through the texts carefully, you will identify strings of words that carry a theme, regardless of their length. You may highlight a word, a phrase, or a paragraph of any length and label it with a code during the first-stage coding process.
If you focus only on larger units, such as paragraphs or an entire story/episode, be mindful of the information you may lose. Paragraphs can contain complex thoughts; even though each paragraph is supposed to have a “thesis,” or a predominant theme, you may still be suppressing other themes in the paragraph by labeling it with one code.
If your data are formal documents with clearly organized paragraphs (such as laws), you may consider using paragraphs as the unit of analysis. With in-depth interview data, we recommend zooming into smaller units such as words and phrases, since interviews, like conversations, do not follow the organized structure of paragraphs.
What Is the Process of Inductive Analysis? Steps of Grounded Theory
When you first look at your data, you may be overwhelmed by the sheer amount of text or images you have collected. Data seem chaotic, dispersed, and without order. Take a deep breath.
In fact, it is precisely your job to create a sense of order with your data, by discovering patterns and developing thematic summaries. How do you achieve this? You do it step-by-step.
You must understand that coding qualitative data is a multi-level process, especially if you choose an inductive analysis approach. Since inductive coding is most often used in student research, we will focus on the steps of grounded theory (Glaser and Strauss 1967) as a popular example of the inductive coding strategy.
Grounded theory methods develop a theory grounded in the data by way of a multi-level coding and summary procedure. In this method, you first read your text data several times to become familiar with the overall themes of the narratives.
Then, as you start the coding process, you carefully read the texts line by line while identifying any embedded theme in any part of the text (“open coding”).
The units of analysis here can be a word, a phrase, a few sentences, or paragraphs; any small unit that carries a theme should be identified and labeled
What Is the Process of Deductive Coding in Content Analysis?
When you have a set of very specific and focused research questions, you may be inclined to take a more “top-down” approach. If you take this strategy, you will construct a coding scheme first and then go to your data to find the parts that correspond to the pre-constructed codes.
How do you know what codes to use for your analysis? A few things will give you some ideas about coding schemes. The first is a theory. If your project is based on a particular theoretical framework, you will have some expectations about what common patterns exist in your data.
For instance, if your project is a study of suicide among students in highly competitive universities based on Agnew’s general strain theory (1992), you may anticipate accounts of strain in your data, such as poor grades, academic pressure, peer pressure, troubles in the family, and so on.
If these are targeted variables in your study, you may use these as your coding scheme and identify parts of the transcribed interviews containing these thematic codes.
Second, you may use coding schemes developed in another published study. In his seminal work, Gender Advertisements (1979), Erving Goffman analyzed the way advertisements portray women’s subordination.
Goffman’s study used a 5-category coding scheme as visual signs of subordination: relative size, feminine touch, function ranking, ritualization of subordination, and licensed withdrawal.
If you are doing a project on gendered images in different communication media (e.g., newspaper photos, Instagram posts), you can utilize Goffman’s coding scheme for the analysis of your own data. In fact, Goffman’s coding scheme is often adopted by student research on gendered images in media data.
Third, your research questions may be used as the coding scheme to classify the information in your data. For example, suppose a student focused on the following questions in her study of victims of intimate partner violence:
1) who is most instrumental to finding support services for victims?;
2) what/who encourage victims to separate from the violent partners?;
3) what are victims’ most immediate concerns when they escape home?
These questions are relatively specific, and therefore the researcher can use these categories as the pre-constructed codes: “helpers” “motivations,” and “concerns.” For example, consider the following passages from a student interview transcript:
One morning, after my husband left for work, I sat on the kitchen floor and just broke into tears. I didn’t realize that my front door was not completely shut. Nancy, my neighbor, happened to drop by to ask if I can pick up her mail for a couple of days while she is gone for a work trip. She saw me and froze.
I had big bruises on my arms, which I would normally cover with long sleeves when I go out. We talked and cried the whole morning. About a couple of days later, she brought this woman who was a part of a support group for survivors. She gave me the contact information for a women’s shelter.
This passage provides some answers to question 1) above, and therefore can be coded as “helpers.” If there are narratives about worrying about money or safety in other parts of this interview, those contents could be coded as “concerns.”
Keep in mind that any qualitative analysis will involve switching back and forth between inductive and deductive modes of coding. Even if you are taking a deductive approach, you may need to modify the pre-constructed coding scheme in light of some emerging patterns you find in your coding process.
What Tools Can You Use to Organize and Summarize Codes?
Coding is a complicated process, and you cannot conduct coding in a haphazard manner. During your first stage of coding, you will have a large number of different codes.
In addition, you are likely to make some reflections and notes to yourself as you proceed with your coding. This is a lot of information to keep track of. Therefore, it is critical that you find a system to keep your codes and notes organized.
A simple way to differentiate themes and mark them on the data is to use color coding. Our students often use this method. In the first stage of coding, read the text carefully and code any theme present in the text data. Then, review the codes and highlight or underline the same code dispersed in the data with a color.
For instance, a code for “work and family balance” may come up several times in an interview with a working mother; you may use a yellow marker to highlight wherever this theme is present in the data.
Use another color for a different theme (for example, blue for “career disadvantage” or green for “the supermom syndrome”) and highlight again all the passages relevant to this theme throughout the text.
Repeat the process for other themes using different color markers each time. Keep a record of what color represents what theme. Also write reflection notes, summaries, and comments about this theme on matching color paper.
For instance, after reading the narrative data, if you had additional thoughts about work and family balance, write them down on yellow paper or an index card. That way, you know everything in yellow in your data shares the same group of themes or ideas.
One of our colleagues uses the “Comments” feature in her word processor to organize her notes. She reads through her narrative data on the computer screen carefully and clicks on the “Add New Comments” function to insert a keyword/code and any notes she wants to make. She uses the code as the heading for each comments box.
That way, you can later pull out the comments that have the same code/heading and group them together. For example, every time narratives of a struggle with the “work and family balance” come up, you will highlight the text and add a new comments box, and write something like “Work-Family Balance.”
At the following stage of coding, you can use the “find” function of the word processor to find the places which you have marked with the code “Work-Family Balance.”
After your first stage coding – i.e., identifying small units of a theme and assigning them with initial code labels – construct a grid of themes and sub-themes with notes about where to find those themes in the transcribed interviews.
We recommend that you notate case numbers and page numbers in which the themes are found. In this way, it is easy to locate the sections to use as block quotes when you write your analysis.
How Do You Write about Findings from a Qualitative Analysis?
When you finish summarizing your data, you are ready to write the results of your analysis. The goal of your qualitative analysis is to address your initial research questions by presenting what you have found through your multi-level analysis. The following issues should be considered in writing your analysis.
Theorizing with Qualitative Data
Theorizing is the process of extracting a set of concepts which various cases in your data illustrate and articulating how they are related to one another. In fact, this task should be carried out throughout the multi-phased coding process itself.
Once you have categorized, compared, and synthesized the codes and themes, you will have already exercised theoretical thinking and have some ideas about the relationships between concepts.
At this stage of writing, you will focus on how to organize various theoretical ideas found in your data, elaborate on them, and create an analytic summary of these ideas.
An analytic summary is different from a descriptive summary. A descriptive summary focuses on stating what happens in the data you collected and makes little attempt at broader generalizations. A descriptive summary simply addresses the question, “what stories have I collected?”
An analytic summary, on the other hand, interprets the meaning of your findings in terms of a theory or in relation to a broader context.
An analytic summary attempts to address the “how” and the “why” questions; to do this, you need to make connections between themes.
By linking the findings from your study to the findings from other studies and making connections to various contextual factors, you will explore possible causes, conditions, contexts, and outcomes of the patterns and themes in your data.
To achieve this, an analytic summary requires comparing, generalizing, sequencing/ordering, and making inferences. A popular method used in analytic strategies is the “illustrative method”.
Illustrative methods apply a theory or theoretical concept to specific settings or examples in the data; the points derived from the data serve as “illustrations” or examples of the theory. You may use a single case to illustrate a theoretical idea or several cases (sometimes cross-cultural cases) to illustrate it.
Not every case in your data will illustrate expected theoretical outcomes. Sometimes, you have to pay attention to what are called “negative cases.” Negative cases refer to instances when you did not find what you had expected based on knowledge obtained from existing studies or theories.
Neuman uses the example of Sir Arthur Conan Doyle’s story, “Silver Blaze,” in which Sherlock Holmes paid attention to a guard dog that did not bark during a theft and concluded that the dog knew the thief.
Likewise, when what is commonly found in other cases does not occur in your data, it may be worthwhile to think about why the pattern did not occur in these particular cases.
If you have a group of women who only have one or two children in a high fertility area in Nigeria, for example, you may be able to learn about factors leading to lower fertility rates by studying this group of women. The lesson is not to simply dismiss negative cases. Instead, examine them in comparison with positive cases. Then, you may find something exciting.
Organizing Theoretical Ideas into Sections
When the analysis is complete, you will have a “theoretical story” about your data. What is the best way to present this story in a research paper? The most common format used in published research is to organize the findings into sections and sub-sections using the themes/concepts as headings.
By the time your multi-stage analysis is complete, you will have a few broad conceptual themes generated from your data. Using these themes, patterns, or concepts as headings is particularly effective when your research is an exploratory study the purpose of which is to provide an overview of the themes and initiate some discussions around potential theoretical issues.
If you choose to do this, a good way to start is to write short paragraph memos for each of the conceptual themes or your sub-sections. Then organize an outline of the sub-sections and place the paragraph memos in the appropriate sub-sections.
Later, you can revise the sections by elaborating your paragraphs and adding details. You also should find some block quotes from your data which support and illustrate the themes you are presenting.
Here, the author used a block quote from her interview data to illustrate the perceived low status of elder care workers, despite their income and skills level.
Here, the quotes provide illustrations, or a vivid example – i.e., being called by a belittling term – of the author’s argument about the contradictory statuses of educated Filipina domestic workers. In qualitative analysis, the evidence is most often presented in form of quotes from the data as in this example.
Identify which quotes are appropriate for what themes throughout your analysis. When you begin to theorize (selective coding), you should mark passages in the text data that are supportive of the emerging theoretical themes.
Do this by keeping a note of case numbers and page numbers in a coding summary table, or use color-coded highlights as explained above. Since qualitative analysis requires constant feedback between the data and the emerging thematic patterns, keeping track of quotes will be an integral part of your coding procedures.
When you insert block quotes, remember to provide information on the interviewee you have quoted.
In the above example, Parreñas identified the interviewee by a pseudonym in the passages preceding the quotes; this is a common practice. Another way is to provide the interviewee’s pseudonym in parentheses at the end of the quotes.
Using a collection of block quotes from several interviews as evidence supporting each point you make is a popular strategy in many published studies. To ensure anonymity, you should use pseudonyms or the interviewees’ initials only in your paper.
Another common technique of data presentation is to use a more detailed and holistic story about a single case as an illustration of your arguments. In this strategy, you are describing one element in your sample as “a case” of the general theme you would like to discuss.
For example, a researcher who studies different paths of recovery among alcoholics may collect life history data through interviews and identify three or four different types of turning-points that led interviewees to become sober.
These may include catastrophic experiences of “hitting bottom,” a positive relationship with someone, or finding an effective treatment. In writing the results, the researcher can describe a case that best illustrates each of the different kinds of turning-point.
The benefit of a case study is that it can present more complex details involved in a single scenario. Whereas use of block quotes can support your points by providing snapshots of the pattern you are describing, a case study can provide the holistic development of the contexts in which such patterns occur.
The above principles of qualitative data analysis can be adapted to analyze different types of data including visual data. Visual data, images such as photographs, magazine advertisements, or video footage, are understood as symbols or signs which contain particular messages and meanings about social issues.
Visual data can be grouped and categorized into thematic categories in a similar inductive process as used in the grounded theory; in this method, you will first identify the message/meaning embedded in each of the images and then classify images with the same message/meaning into a broader group until you merge them into a few meaningful conceptual categories.
Similar to text analysis, you can present these thematic groups of images using sub-headings. In the example of research on female reporters and types of the news mentioned earlier, suppose you found that female reports are typically assigned to 1) interviews with women,
2) stories on “feminine” subjects such as food, arts, and fashion, and 3) topics related to “nurturing” roles such as education, animal rescues, or community service. You could create a section dedicated to each of these themes and describe the stories, or provide TV screenshots supporting the theme in each section.
But more frequently, visual data are analyzed using content analysis techniques with pre-constructed coding schemes. First, a few categories of themes, based on theories or existing studies, are developed into codes.
Then, the images or segments of visual data containing the themes/codes are counted and quantitatively summarized into percentages and frequencies. Whether you will take an inductive or deductive approach will depend on your research questions.
Whichever approach you take, you may still use selected images to support the arguments of your paper as you would with block quotes.
Sections of the Final Report Good Need
Is my title direct, descriptive, and concise? Does it capture the contents of my report? Does my title page have all the required items?
Does my abstract clearly summarize my topic, research questions, my sample, methods of data collection, and the significance of my study? Is it within the required word count?
Does my introduction include all the elements necessary in an introduction (i.e., a clearly stated research purpose, sufficient background information, significance of the research)?
Does my literature review include classic studies on the topic, updated literature, and relevant theories? Is my literature review well-organized and well-structured? Does it present my research questions or hypotheses?
Does the methods section include sufficient descriptions of the sample, the measures, data collection methods, and data analysis strategies I used? Does it include the demographic characteristics of my sample?
For quantitative research:
Does the section provide all necessary statistics to inform the readers about my findings? Do my findings address all of my research questions or hypotheses?
For qualitative research:
Does the section provide all necessary information that responds to my research questions, or has it summarized my findings? Have I supported my claims with evidence from the data?
What answers do my findings provide to the research questions? Did I make connections between my findings and existing studies and theories? Have I clarified how my findings fill gaps in the existing literature? Have I examined the social and policy implications of my findings (if applicable)?
Are the summaries succinct and effective? Have I explicitly stated how my study contributes to the field? Have I listed the limitations of my study and suggested future research directions for the readers?
Is my reference list complete, and does it conform to an appropriate format? Does the list include all of the studies I cited in the report and only the ones cited in the report?
Visual Presentation of the Data (if applicable):
Are my charts, tables, diagrams, or figures accurate and effective? Are all tables and figures numbered and have titles?
Is my report free of spelling and grammatical errors? Does it conform to the formatting