Sometimes writing a dissertation on vast a topic provides tons of facts. For students, it often becomes difficult to decide what they should include. In such topics, the presentation of data in the literature reviews as well as results analysis sections needs data summarization. Especially in the graduate dissertation, logical data presentation is of utmost importance. Hence, this article will discuss the best guidelines for data summarization in the dissertation.
Guidelines for Data Summarization in Literature Review
The literature review is a section to present the findings of past studies related to your topic. It gives an overview of the present knowledge. It allows researchers to pick the relevant theories. Further, it aims to identify any gap in the past research. The literature review writing is a process that consists of three steps:
- Critical evaluation
In the dissertation, the students must follow these data summarization guidelines at each step.
Summarization During Research
In the dissertation, the first step in every section of dissertation writing is research. In LR, the Keywords are of significant importance. We obtain keywords by the summarization of the topic. Most of the time, the key terms in a topic become the keywords. After that, the next step is to search for each keyword. But, what a student should do when the list of search results goes beyond their imagination? This is the point when they need to follow the data summarization techniques.
- The first step for data summarization in the LR is to customize the years of publication. The students can narrow down their search results by choosing articles from last 5-10 years. The research older than ten years decreases the authenticity. So, after narrowing down the results using the data filter, you have completed the first step of data summarization.
- The second step to summarize the scholarly sources for an LR is eligibility criteria. For making the eligibility criteria, the students make two lists. The first list should be the inclusion criteria list. In contrast, the other will be the exclusion criteria list.
Inclusion Criteria List:
The inclusion list contains factors on which you decide what source you will consider useful. This decision may base on the following things:
- The information in the abstract
- The credible sources of information
- Number of relevant hints
- Title of the research paper
- Methodology of the paper
- The final presentation of the results
Exclusion Criteria list:
Like, in the exclusion criteria list, you should consider the factors you decide what source you will consider useless. This decision is also based on the things mentioned above. Hence, the eligibility list of the sources is the most important in LR data summarization.
Data Summarization During The Critical Evaluation
The next phase in data summarization is the presentation of logical or concise critical evaluation. The dissertation writing guidelines suggest that each paragraph must contain 150-200 words. So, for data summarization, you must structure your Literature review using relevant theories and tell the reader how these theories relate to your Literature review.
Hence, first, you need to write a concise topic sentence. Then, you should give at least two pieces of evidence for the topic sentences. Right after the evidence is the best place for the critical evaluation. The critical evaluation is the researchers own interpretation he has gained during education. Afterwards, the last few lines explain the crux of the whole paragraph. Hence, on average, each sentence must contain 20-25 words. So, presenting a scholar’s work in this way is the best way of using it in a dissertation. Like in LR, the result analysis section of the dissertation also demands data summarization.
Guidelines For The Summarization In The Result Analysis Section Of The Dissertation
The result analysis section is the second most important part that needs data summarization. Some vast studies contain several variables. In this case, the students also need to summarize the result section.
- The merging technique is the best way to summarize the data with several variables. In the merging technique, the researchers merge closely related variables.
- Another helpful technique is to identify the relationship between dependent and independent variables.
The data summarization is an important aspect of the dissertation and carries a lot of weightage. To ace your dissertations, you should try to master the art of it.