The famous red thread – 5 tips for structuring the thesis

Stringency in content and clear lines of argumentation are the be-all and end-all of scientific work – and often the greatest challenge. Particularly with complex topics, there is a danger of losing track of the big picture. Therefore, it is all the more important to approach the thesis in a structured way and to master it step by step.

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These 5 tips help to draw a red thread through the thesis – and to stick to it consistently:

1. Building the basic structure in terms of content and methodology

Many students first think of the topic “structure” in terms of what is already known from their school days as the “law of writing”. Introduction – main part – conclusion. Unfortunately, this rough structuring is of little use in mere theory. Of course, every work has its beginning and its end, and in the middle there are so many exciting things that the result is particularly insightful. So far, so good. However, in order for the beginning-middle-end principle to become a solid timetable for a thesis, you have to know how to fill it with life in a meaningful way.

One might think that introduction and conclusion are predominantly decorative accessories that only span the frame around the place where the actual magic happens. In fact, however, it is precisely the introduction that is the place in the Bachelor’s, Doctoral or Master’s thesis where the red thread originates. The introduction does what the startup scene calls a “pitch”. The pitch is about convincing an idea as quickly as possible in order to attract the interest of investors. In terms of scientific work, this means: to give potential readers as little space as possible to explain with well-founded facts why they absolutely must continue reading at this point. Anyone who sees the introduction as a pitch, however, not only creates clarity for the later reader, but also defines a kind of roadmap for himself, which can then be worked through consistently. With the help of a few questions, the basic structure of each thesis can be built in three steps.

What and why?

At the beginning of the thesis there is always a more or less broadly defined set of topics that is in some way relevant for our society as a whole or for a part of it. The first question should therefore always be, regardless of the subject and type of work: What exactly am I dealing with and what special significance does this topic have? This is immediately followed by a description of the problem arising from the topic. Why is it important that I take a closer look at this topic? Has it received little or no attention in the scientific context so far? Has it only been considered under certain (insufficient) aspects? Or has it only been examined with certain (inadequate) methods?

What’s the point?

After identifying the gaps in research so far, it is important to find out why it is worth closing this gap. “Why?” is possibly the most important question on the way to the red thread. Because it also includes: “Why should I continue to write here? It may sound strange, but it is enormously important to understand for yourself the overarching scientific added value that you can provide in order not to get lost in details during the writing process that do not contribute to solving the original research problem.

How’s that?

After all, the “how” is a question about the framework in which the scientific debate takes place. Which partial questions do I have to answer in order to obtain results on my central research question? And: On the basis of which methodology do I actually manage this? The “How?” rounds off the scientific pitch by defining the content and methodological timetable for answering the overarching question.

Once you have answered all these questions for yourself, the red thread is actually already complete. Now it is important not to lose sight of this, but to work step by step through the specially defined roadmap.

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2. Using the power of visualization techniques

As the term roadmap implies, scientific work can be imagined as a road with several miles. Why should we do this exactly like that? It has long been accepted that our brain can better process and absorb information if we remember it visually. It has therefore become common practice both in science and in business life to visualise complex facts in diagrams and infographics. It would be downright careless not to make use of this method in scientific work. Whether in the form of a mind map, a flow chart or an alternative form: It is best to start with the overriding research question and then visualize all the partial questions that are important for answering it. For example, different colors, shapes, sizes and lines can be used to visualize priorities or relationships between individual subquestions. Visualization techniques help to classify the vast amount of information from literature research thematically better. This creates clarity in the mind and avoids the risk of losing the red thread. You should therefore make sure that the visualized roadmap is within visible reach during the entire processing time – whether on the desk, on the pinboard or on the screen.

3. Select research results – the quick check

 

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It is of enormous importance to consistently prioritise and select research results, because many students lose track at this point. First of all, they deal with everything that fits thematically into their field of research and find all sorts of interesting results that do not necessarily concern their concrete research question. It might make sense to address questions that go beyond one’s own work within the framework of a summary of the outlook. However, it is much more important to spend your time on results that actually help you achieve your research goal.

Therefore, the Roadmap is also a checklist. With the help of the roadmap, every newly found source should be subjected to a quick check.

The Quick Check Question:

“Does the source add value to answer one or more questions on my roadmap?”

No matter how interesting what you read may seem – if it is not directly related to your own questions, the source should be discarded so as not to get lost in irrelevant facts that cost time and energy and endanger the red thread of your work.

4. Document and categorize research results at an early stage

If the Quickcheck is positive, it is important to document the research results not only immediately, but also systematically. Uncoordinated scribbling on notepads and sticky notes leads at best to chaos of notes and thus has the same effect as “simply reading without notes”: after the tenth source at the latest, nobody knows what information was actually read (or written down) where. With the help of the roadmap, however, each research result can be assigned to at least one partial question. In addition, further criteria for the categorisation of scientific findings can be defined. The best strategy is to create a keyword list. For example: A research thesis should be refuted or refuted on the basis of controversial scientific perspectives. A research result can then, for example, be tagged with “Pro” or “Kontra” – depending on whether it supports the thesis or provides an opposing position. A keyword system facilitates the later retrieval of notes that belong together in terms of content and thus ensures that one keeps track of one’s collection of notes.

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The systematic keywording of notes has another advantageous effect: it makes it possible to repeatedly go into a kind of bird’s eye view during the writing process in order to view notes in their overall context. There’s no question about it: a detailed examination of individual literature sources is indispensable for scientific work. And yet the real added value of a thesis does not lie in the reproduction of already existing research approaches. It only becomes really exciting when connections between these are found and space is created for one’s own conclusions. By working step-by-step through different keyword categories and checking the notes stored in each category for similarities or differences, one creates the basis for new (one’s own) findings in a structured way.

The idea behind such a keyword system is not new. Many scientists today work according to the so-called card index method, which goes back to the famous German social theorist Niklas Luhmann. Luhmann’s internationally renowned classic works on systems theory were created with the help of a wooden file box, into which he sorted his thoughts and ideas in the form of handwritten notes. By linking notes with related contents via a system of numbers and letters, new insights were revealed to him again and again, which led to the continuous growth of his note box.

A well-organized collection of notes is therefore not only the starting point for a structured and stringent thesis, but can also serve as a kind of innovation helper. Of course, today no one has to fight their way through wooden index boxes or handwritten keyword lists. Instead, scientific work can be supported by numerous digital tools.

5. Working with the right tools

Mind mapping tools such as Mindmeister or Xmind are ideal for fast visualizations. Luhmann’s note box method is now also paperless. Digital slip boxes such as Auratikum contain integrated functions for the systematic archiving and structuring of notes and thoughts. The red thread is not created by leafing through heaps of paper, but conveniently by drag & drop. Tools such as these now offer all the prerequisites for the successful structuring of scientific work.

Conclusion

The structuring of the thesis is a mammoth task – no question about it. With the right approach, however, one does not even get into the situation of getting bogged down. This begins with the early creation of a timetable to deal with a clearly defined question of content and ends with a consistently structured collection of notes. Visualization techniques as well as digital structuring tools save unnecessary chaos of notes and head and thus effectively ensure that the thesis becomes a round thing. You only have to make use of it.

About the author

Saskia Pauly is studying Management & Marketing with a focus on market research in the cooperation program of the FAU Erlangen-Nuremberg and the EM Strasbourg Business School. From her own experience, she knows that the only way to structured scientific work is to cope with paper chaos. As a team member of Auratikum, the digital card index app for students and doctoral candidates, she has been working on the future of (digital) scientific work since 2017.

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