Categories
Study Hacks

How to Eliminate Self Doubt as a Student (7 Steps)

Finding out how to eliminate self-doubt as a student can be a major challenge.

What if I don’t pass my next exam?

Or, heaven forbid, if I end up with a lousy grade?

Then all my dreams of completing my degree and landing my dream job will go down the drain! There is only one way out: You must focus on how to eliminate self-doubt and fear.

As you read these questions, you can feel your heart racing, and those pesky negative thoughts are exactly what occupy your mind, right?

Whether you find yourself questioning your abilities, drowning in the overwhelming workload of your studies, or constantly comparing yourself to your fellow students, self-doubt can become a real mental burden that chips away at your self-confidence.

But don’t give up just yet!

The silver lining is that self-doubt is actually a normal part of the learning process, and with effective strategies, you can conquer it.

That’s precisely why I’ve put together this article with 7 invaluable tips on how to overcome self-doubt and fear just for you. They’ll help you silence that critical voice in your head and tackle your upcoming study tasks with a renewed sense of enthusiasm. So, let’s dive right in and kick self-doubt to the curb!

Step 1: Recognize and Identify Your Self-Doubts

The initial stride on how to overcome self-doubt and fear is acknowledging its presence and realizing that it’s a completely normal and human experience.

Self-doubts act as a defense mechanism, shielding us from the potential sting of failure. In a healthy dose, they can even be a catalyst for motivation, propelling us to give our best and refine our skills to bolster our self-confidence.

However, when doubts and fears overpower us, they can hinder our performance and become a heavy burden.

The first step on how to overcome self-doubt and fear is to consciously acknowledge and precisely identify its triggers. It’s easy to initially attribute it to a general fear of exams, but it’s crucial to delve deeper within yourself.

  • Which specific exam evokes this unpleasant sensation?
  • What is it about this particular exam that instills fear in you?
  • What specific outcome are you afraid of and why?

By gaining a clearer understanding of your mental barriers, you can directly confront your self-doubts and ultimately fight them.

how to overcome self doubt and fear

Step 2: Your Thoughts Don’t Define Reality

When it comes to assessing our own abilities, we often let our feelings cloud our judgement. It’s crucial to recognize that our emotions don’t always reflect the objective reality of our competence.

To conquer self-doubt and free yourself from feeling inadequate, it’s essential to separate our emotions from the objective evaluation of our abilities.

Take a step back and try to assess yourself on a rational level. Jot down your past achievements and identify your strengths. You might even consider starting a success journal to track your progress.

When self-doubt starts to creep in again, referring to your journal can provide a genuine confidence boost.

However, especially when you’re caught in the throes of self-doubt, recognizing your strengths can be challenging.

In such instances, seeking honest feedback from mentors, professors, or fellow students can be immensely helpful.

Oftentimes, we tend to be our own toughest critics, while others can offer a more objective assessment, offering a clearer perspective of our actual skills.

This enables you to better identify areas that require improvement and differentiate them from minor distractions that you might unnecessarily obsess over.

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Step 3: Create a Worst-Case Scenario to Eliminate Self-Doubt

Hold on a second! I know I’m already caught up in my worries, so why should I bother sketching out a specific worst-case scenario?

Well, here’s the thing.

When you take a moment to consider the absolute worst outcome in this situation, it triggers your mind to start thinking about solutions almost automatically.

And these small steps towards finding a solution are exactly what you need to combat your worries and overwhelming feelings. Besides, is your worst-case scenario, which is highly unlikely to even happen, really so catastrophically awful that there’s no way out?

Let’s say you actually fail the statistics exam. What’s next? You’ll have to retake it! Sure, it’s not the most enjoyable experience, but it’s not the end of the world either. Life goes on.

Visualizing the negative doesn’t make your thoughts even more negative – quite the opposite, in fact.

If you do encounter a setback, you’ll be emotionally better prepared to handle it.

The ancient Stoics like Seneca and Marcus Aurelius understood this well. For them, visualizing the worst-case scenario was an integral part of their daily meditation practice.

Step 4: Develop Your Self-Confidence

When it comes to overcoming self-doubt, a healthy dose of self-confidence is absolutely essential. But let’s be honest, it’s easier said than done, right? How to overcome self-doubt and fear? How can you actually build more self-confidence and conquer your self-doubts?

In this context, you’ve probably come across the concepts of positive thinking and affirmations. And guess what? Scientific research has shown that they work, at least to some extent.

So, it won’t hurt to give yourself some positive pep talks. However, I firmly believe that taking proactive steps will lead to even greater success (and shrink the foundation of your self-doubt, wink).

Let’s revisit the statistics exam, which was like the final boss and a major source of self-doubt for many students during my studies.

If you find yourself tormented by thoughts of potential failure, here’s my tip: Prepare for the exam as thoroughly as possible.

I know it may sound mundane, but trust me, from my own experience, it’s the best way to combat self-doubt. Being well-prepared increases your chances of passing the exam significantly.

But what if you’re completely clueless about dispersion parameters and scale levels? In that case, passing the statistics exam might seem like a distant dream. However, why not tackle exercise 1.5 for your next tutorial? Give it your best shot and then discuss it with your tutor.

The principle is crystal clear: Instead of facing an overwhelming task head-on, break it down into smaller, manageable subtasks.

As you successfully complete these subtasks, your self-confidence will naturally grow, and that nagging inner critic in your head will gradually quiet down.

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Step 5: Reach Out for Support

Do you ever feel like you’re the only one dealing with your worries? Your fellow students seem to be unaffected by crippling self-doubt, and no one dares to talk about this uncomfortable topic.

But here’s the thing: that’s precisely the problem! Many students try to handle their concerns alone or simply push them aside. Unfortunately, that approach doesn’t lead to much progress.

Wouldn’t it be so much easier if you could openly address your fears? By doing so, you can support one another and provide much-needed encouragement.

When self-doubt starts taking over your thoughts and impacting your quality of life, it’s a clear sign that you should seek support.

It’s truly amazing what a difference it can make to realize that you’re not alone in your doubts and that others have gone through similar experiences. Reach out to people you trust in your circle, such as your friends or your family.

They might help you in finding out how to eliminate self-doubt because they have done it themselves.

Additionally, universities and colleges often have resources like psychological counseling services with trusted professionals who can lend a helping hand. Remember: Every worry can be overcome, even if it may not seem that way at first.

Step 6: Embrace Failure as an Opportunity for Growth

Even if you didn’t pass an exam, had a mental block during an oral exam, or had a disastrous presentation in a seminar, it’s important not to define yourself by those failures.

Instead, see them as chances for learning and personal development. Remember, nobody is immune to failure, and even the most successful individuals have faced numerous obstacles on their journey.

Stephen King’s book “Carrie” was rejected by 30 publishers before it finally got published in 1974.

Tim Ferriss’ book “The 4-Hour Workweek” was rejected 25 times.

And even the manuscript for Harry Potter faced rejection 12 times. J.K. Rowling even received feedback like, “You do realize you will never make a fortune out of writing children’s books?”

But they didn’t let those setbacks define them or stop them from pursuing their dreams.

By accepting failure as a normal and necessary part of the learning process, you can free yourself from the fear of making mistakes and self-doubt.

Take the time to analyze and reflect on what went wrong in those challenging situations. Use that reflection to identify areas for improvement and develop an action plan for overcoming similar challenges in the future.

Remember, failure doesn’t have to be the end of the road. It can be a steppingstone towards growth and success. So, don’t be discouraged by setbacks.

Embrace them, learn from them, and use them as opportunities to become a stronger and more resilient individual. Keep pushing forward, keep learning, and keep growing.

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Step 7: Celebrate Your Progress and Every Little Success

And finally, it’s time to celebrate! Take a moment to rejoice in your progress and success, no matter how small they may seem.

Give yourself credit for the efforts you’ve put in, the hard work you’ve invested, and the achievements you’ve attained.

By rewarding yourself for reaching milestones, you’ll give your self-confidence a well-deserved boost and foster a positive mindset.

Remember, finding out how to eliminate self-doubt is a continuous journey, and every step forward is worth celebrating! So, let’s give a big “Whoop Whoop!”

Categories
Research Methods

Case Study Research Methodology (A Beginner’s Guide)

You would like to apply the case study research methodology to you next academic paper or thesis?

Then you should stop everything else right away, because in this article you will get a super fast and effective beginner’s tutorial on how to conduct a case study.

In only 6 easy-to-follow steps you will learn the basics of case study research and how to apply them.

What is the case study research methodology?

Case study research is often used in social sciences. It investigates a current phenomenon that can be observed in our world (as opposed to, for example, historical events or natural laws).

This phenomenon is always anchored in a specific context, which must be taken into account throughout the entire case study. A possible context can be an organization, a country, or even a single person.

The case needs to provide the context in which the phenomenon under investigation can be observed.

In a case study, the researcher has no influence on the events (as opposed to, for example, an experiment in a laboratory). Rather, data is collected in the field or from third parties about that case to analyze the phenomenon and to arrive at theoretical and/or practical conclusions.

Both qualitative approaches (such as interviews and grounded theory) and quantitative methods (such as surveys and statistical tests) can be used in data collection and analysis. The special feature is that the research focuses only on one specific “case”.

Comparative or multiple case studies are special forms of case study research that relate and contrast several cases to each other.

A case study always answers a specific research question, which is best started with “how” or in rare cases also with “why”.

Who should use a case study research methodology?

As mentioned earlier, a case study is a methodology that is popular in the social sciences. Those include economics, psychology, political science, and so on.

Natural sciences and humanities do not fall under this category. However, as interdisciplinary research and teaching are almost everywhere nowadays, it is not impossible that case studies can also be used here. Case studies are therefore a quite common and widely used research methodology.

Critics of this method claim that case studies are too “soft”. This means that they have little explanatory power due to their descriptive research design. This can be countered by collecting unique data and analyzing it empirically, resulting in a “harder” case study.

Moreover, critics would claim that a lack of generalizability is a limitation of case studies. This is true, but only for statistical generalization. Other forms of generalization are possible with case studies but are often not considered.

Differences exist here both between different disciplines and cultural backgrounds. For example, case studies in European management literature must be quite “hard”. In the United States, on the other hand, case studies are often written quite “soft” and rely on the storytelling and interpretative abilities of the authors.

Especially for a dissertation, a case study is a great option. Depending on your data collection possibilities and methodological training, a dissertation can move freely on the spectrum from “soft” to “hard”.

Conducting a Case Study in 6 Steps

Now that you have all the background information, let’s move on to the 6 steps you can follow to write a case study.

I mainly rely on the work of Robert K. Yin and the 2014 version of his book “Case Study Research: Design and Methods”.

You can find the book linked below the video and in any well-organized university library.

Whenever you want to use the case study research methodology in academia, you should refer to at least one source in your methods chapter that has established generally accepted rules for the process. In Yin’s book, you will also find an overview of the most important sources for each research discipline.

Planning your case study #1

First and foremost, you need to decide that you want to conduct a case study. But that’s not enough. You should carefully consider why a case study is preferable to other methods.

  • Why is a literature review, a survey, or an experiment unsuitable?
  • What are the advantages of a case study in your situation?
  • Is a case study even possible with your resources?

You should have an answer to these questions and discuss them with your supervisor. Planning also includes formulating a research question.

To conduct a case study you need a relevant research question. Start with the question word “how” and proceed slowly. There are two possibilities:

  • Case-specific research question (e.g., “How does Volkswagen respond to hate speech on Twitter in the wake of the Dieselgate scandal?”)
  • Generic research question (e.g., “How do large companies respond to hate speech on social media?”)

Both approaches are possible and have their advantages and disadvantages. The research question should always be discussed with your supervisor.

case study research methodology

Setting up the research design #2

Now it’s time to set up your research design. The crucial questions here are:

Which method(s) can be used to answer my research question?

And:

What data do I need for that?

In my example, I could proceed as follows: I construct my case study backwards. I could answer my research question by identifying various strategies in the Twitter replies of the VW Group.

I could do this by collecting a dataset of relevant tweets (e.g., using the hashtag “Dieselgate”) and applying qualitative content analysis.

Can I answer the question differently?

Sure. In theory, I could also interview VW employees and have them answer the question.

Which approach you choose also depends on the possibilities you have to obtain data.

Preparing for data collection #3

Now it’s time to prepare. Just follow these three steps:

Create a literature review

Before you do any research, you have to read. Conduct a thorough literature review that reflects the current state of research.

(And if you are a bit more advanced:)

Is there a theory that can explain your case study?

In this case, establish a theoretical background. You do this by focusing on a theory that helps you understand the phenomenon under investigation. You then discuss your results in relation to this theory.

Identify data sources

Where do I get my data from?

Which interview partners do you need, which social media platforms, which company data? Which archive reports?

Contact the right people

Now all you have to do is get access to the data. Write to interview partners, call archive owners, and so on. Create a table with all your data sources for better overview and keep a diary of your progress.

  • Whom have you already contacted?
  • Who responded positively?
  • Were there any rejections?

This way you can meet your desired timeline and optimize your project management.

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Data collection #4

The fourth step according to Yin is actual data collection. Again, this can look completely different depending on your research design.

If you conduct interviews, I just apply the method as you would normally do. Remember that a case study is a methodology and not a method.

This means that you are flexible in the methods you choose.

At this point, the literature review should be completed and already written up.

Data analysis #5

The most work when conducting a case study awaits you in the analysis. In “hard” case studies, of course, a little more than in “soft” ones. When analyzing your data, follow a few guiding questions.

  • How can your data be described?
  • Do the data have special characteristics?
  • What patterns can be identified here?

Collect your results digitally and make enough backups. Nothing is more annoying than losing days of work. Use software wherever possible, because you are not the first person to conduct such an analysis. Smart software solutions make pretty much every research method easier.

Interpreting the results #6

Finally, you filter the important results from the unimportant ones and present them “from general to specific” in the results section of your manuscript.

These 3 elements are essential for an outstanding case study:

  • Figures (e.g., flowcharts, bar charts, or pie charts)
  • Tables (e.g., with absolute or relative values of your analysis; results of statistical calculations such as frequencies or correlations)
  • Explanatory text between the visual elements that shows the reader which of the results are particularly noteworthy

In another chapter, you discuss the results in relation to:

  • Your specific case
  • General conclusions or implications (to theory)

Note that the results of a case study are not generalizable in a statistical sense. However, other generalizations are possible if your reader is willing to make some judgement calls.

For examples, this means that you should not draw conclusions about all other car manufacturers from VW. However, you can advise the reader to transfer the findings onto a another case if they are willing to accept that this case is similar enough to VW.

Moreover, case studies are great if researchers want to develop new theory. This is why case study research methodology is often combined with techniques from grounded theory.

Categories
Uncategorized

Is Using ChatGPT Plagiarism? (A Surprising Answer)

Is using ChatGPT plagiarism? Since the AI-powered chatbot ChatGPT has shaken up the academic world, this question has been on the minds of many students and teachers.

If you use ChatGPT to create your academic assignments, do you run the risk of being accused of plagiarism and failing your subject?

Today, we will delve into this question in detail so that you know exactly what you can do with ChatGPT and what you should avoid.

The definition of plagiarism

In order for us to form an opinion about texts generated by ChatGPT, we first need to define what plagiarism is.

The University of Oxford, for example, defines it in their University policy as “‘the copying or paraphrasing of other people’s work or ideas into your own work without full acknowledgment.”

This definition can serve as the basis for a classification of AI-generated texts.

Is using ChatGPT plagiarism?

From my point of view, it makes sense to distinguish between 3 forms of using ChatGPT.

#1 Using ChatGPT for grammar and spelling checks

Let’s say you write your own text and use scientific sources that you cite as usual. Now you ask ChatGPT to optimize this text you have written.

The AI program could, for example, check grammar and spelling, find synonyms, or paraphrase the text to make it sound more scientific.

Is this considered plagiarism?

No. You are the intellectual author of the text and have indicated the references on which you base your argument correctly. This is not plagiarism. Grammar-check software or a human editors have existed for ages and do not lead to plagiarism either.

#2 You paraphrase text from another source using ChatGPT

Of course, you could also come up with the idea of having ChatGPT rewrite a text from another source. Now it depends on whether you make the original source visible or not. That was the decisive criterion before ChatGPT and still is.

Case 1: You indicate the original source (indirect quotation)

Paraphrasing is a technique of scientific work and, with correct indication of the original source, is nothing other than an indirect quotation. If you use ChatGPT in this way, you are not committing plagiarism.

However, you should ask yourself to what extent ChatGPT can help you in this case. A meaningful indirect quote is perhaps 1-3 sentences long. Paraphrasing longer text passages and thus several lines of thought in a row makes little sense.

This is because if you copy more than one thought from another source you are leaving the realm of what is considered good academic work.

After all, one criterion for evaluating scientific work is your ability to develop your own lines of thought and unique arguments.

Is using chatgpt plagiarism

Case 2: You do not indicate the original source (plagiarism)

If you have ChatGPT paraphrase text from another source and do not indicate the original author, then of course this is considered plagiarism.

Now we come to the most exciting case.

#3 You use ChatGPT to generate new text

What is so special about ChatGPT is that the program can not only paraphrase but also generate text. If you now present a text created by AI as your own, are you committing plagiarism?

Let us recall the definition of plagiarism. The following questions arise:

  1. Can we consider ChatGPT as “other people”?
  2. Is using ChatGPT intellectual property theft?
  3. Is copyright being violated?

You are welcome to disagree with me in the comments, but I think the answer to the first question is no.

An artificial intelligence is not a person. This is precisely the decisive characteristic of an AI. That is why no intellectual property theft or plagiarism can take place here as it used to be defined.

The answer to the second and third question is not quite clear. After all, ChatGPT also uses sources, e.g. from the internet, but does not indicate them. If you were to do the same work, you would have to indicate these sources in order not to commit plagiarism.

Therefore, it would be advisable to ask ChatGPT about the sources on which the generated text is based, to check them manually and to indicate them when using the generated text.

An even better way would be to limit one’s use of ChatGPT to optimizing language and avoiding the risk of generating text without knowing its sources.

Preliminary conclusion

We have seen that you can use ChatGPT in different ways. How you use ChatGPT determines whether you are plagiarizing or not.

Now comes the big BUT.

When evaluating academic assignments, plagiarism is not the only criterion.

What do I mean by that?

You can use ChatGPT as a tool for your scientific work and not commit plagiarism, but still violate the University policy.

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ChatGPT Plagiarism Scanners

Most Universities have not made up their minds about how to deal with ChatGPT. Some have dabbled around with ChatGPT scanners, which is total non-sense in my opinion.

With the help of mathematical models, these scanners can give examiners a probability of whether a text was generated by an AI.

In addition, Open AI, the company behind ChatGPT itself, now offers a ChatGPT plagiarism scanner that can detect ChatGPT texts.

These scanners can always be circumvented with certain tricks. A development in this direction would therefore be a constant arms race, which the software developers would probably laugh about the most.

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Redefining plagiarism

The University of Oxford, for example made up their mind. They introduced a new plagiarism policy that states the following:

“Plagiarism is presenting work or ideas from another source as your own, with or without consent of the original author, by incorporating it into your work without full acknowledgement. All published and unpublished material, whether in manuscript, printed or electronic form, is covered under this definition, as is the use of material generated wholly or in part through use of artificial intelligence (save when use of Artificial Intelligence – AI for assessment has received prior authorisation e.g. as a reasonable adjustment for a student’s disability).”

Ok, this is as clear as it can get!

But what happened here? The University of Oxford simply changed the definition of plagiarism!

I think a better way would be to keep those things separate. Instead of changing the definition of plagiarism, they could just introduce an AI policy.

Other Universities might disagree with this definition and allow the use of AI. But at this point nobody agrees upon the definition of plagiarism anymore.

Universities could choose a very different path. Banning ChatGPT could be considered counterproductive. How can you prepare students for a world with AI if you ban it from universities?

Things like ChatGPT could still be allowed as a tool, but the exam formats might change. There could be more oral exams or less scientific papers, which then have to be empirical, for example.

What do you think? Is should using ChatGPT be considered plagiarism? Please let me know in the comments.

The Key Take-Away for You

The key take-away concerning your academic assignments is to check the AI policy of your University, because policy and plagiarism are not the same.

Categories
Philosophy of Science

What is a Theory in Research? (simply explained)

“What is a theory in research?”

…my professor asked me in my last oral exam at the university.

Pah! What an outrageous question.

I had apparently answered the questions related to the course material so well that he now wanted to test me.

The annoying thing was, I couldn’t really answer the question well. When are you ever asked that question?

This article will help make sure that you don’t experience the same thing that happened to me.

From now on, you will always have an answer for the question “what is a theory” plus some knowledge about the philosophy of science at your fingertips.

What is a theory in research?

Defining the term “theory” is not so easy. But one thing is clear: anyone who wants to deal with theory from a philosophy of science perspective cannot ignore one man: Karl Popper.

Popper defined theory as “universal statements” used to cast a net to “catch” the world. (Popper, 1959).

So a theory should aim to contribute general statements (universal statements) about phenomena (the world) in order to better explain or understand the world. Specific statements that are only true in a particular situation are therefore not suitable as theory.

A theory often only considers a specific section of reality. This section can then be represented as a so-called model.

The Demarcation Problem

Why was Popper’s work so important? Until Popper’s book “The Logic of Scientific Discovery” was published, it was not really defined when a methodology was considered “scientific” and when it was not.

This is also called the “demarcation problem”, i.e. the dividing line between science and non-science.

At that time, Popper criticized in particular the backward-looking character of many studies. For example, Popper’s contemporary Sigmund Freud looked back in time to explain the present. What Popper disliked was the fact that Freud could always search for evidence that confirmed his theory instead of looking for evidence that refuted it.

Falsification

Albert Einstein, on the other hand, tried to make predictions about the future using theory, which Popper preferred.

what is a theory

However, theory according to Einstein’s approach is much more fragile, as only one event in the future is enough to bring down the entire theory.

But Popper was convinced. He believed that theory must be falsifiable.

The old view was this: if I find a handful of white swans, I can propose the theory that all swans are white.

Popper’s view, however, was this: if I find a single black swan, I can refute the it.

Instead of looking for evidence, we should look for counter-evidence!

The main components of a theory in research

The development of a theory most often involves the observation of real-world phenomena. At least when we conduct science based on the idea of empiricism, which presupposes that knowledge is generated through human experience.

Through a step of interpretation and abstraction, we can convert the phenomena into concepts. On a practical level, we can do this in the qualitative analysis of interview data, to name just one example.

At this level, we can also make assumptions about how these concepts are causally related to each other. This is a very important component of any theory: what is the relationship between the individual components?

Once concepts and their relationships are established, we can in principle speak of a theory.

Now it is a matter of repeatedly testing, expanding, or falsifying it.

To do this, concepts are transformed into constructs that consist of individual variables. This step is important so that it is even determined what can be observed in a study and then ultimately measured. Measurability is achieved by operationalizing variables.

The theoretical relationship between the variables is expressed in hypotheses that can be tested through statistical calculations. Here we are in the realm of quantitative research. For example, an experiment could be carried out to draw conclusions about the relationship between two or more variables.

What is a theory in research? (4 questions)

To order the components of a theory a bit, you can ask questions as Whetten (1989) did:

What?

Which factors, be they concepts, constructs or variables, should be considered at all? Here the principle of parsimony or Ockham’s razor applies, namely: the theory that requires the fewest components to explain the phenomenon is usually the best.

How?

How are the factors connected to each other? You can easily imagine this with the boxes and arrows that are usually used as a graphic element to illustrate a theory in 2D.

Why?

What are the dynamics that the theory tries to model? What are the causal relationships that the theory assumes?

Who, Where, When?

What are the limitations of the theory, and who or what can it not represent if necessary?

Critique of the prevailing understanding of theory

However, this understanding of “what is a theory?” is not the only one.

Although Karl Popper did not consider himself a positivist, the image of theory explained above corresponds to positivist assumptions.

This would mean that we humans can perceive the world as it is with our senses and can therefore make statements about the objective world.

In the natural sciences, these assumptions are not questioned so much because, to put it bluntly, the probability that we live in a matrix and that the laws of nature do not reflect the objective world is rather low.

If scientists were to question the assumption that there is some sort of objective world outside of our minds it would be very hard to conduct research at all.

But in the social sciences, this epistemological standpoint has often been criticized. The reason for this is that the research object here is different, for example human behavior. Over time, sociology, psychology, and now even communication and media studies have increasingly been overlaid with natural scientific principles.

An example of the resulting conflict was the so-called positivism dispute, in which the German Frankfurt School, led by Theodor Adorno, took a counterposition with their “Critical Theory”.

According to critical theory, the subjective character of knowledge acquisition must be taken into account when developing theory.

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Why do we need theory in research?

Alright, we’ve clarified the question “What is a theory?” (hopefully).

To wrap things up, here are a few thoughts on why they are important. After all, couldn’t we simply observe the world and write down our findings without abstracting them into theories?

Well, we might miss out on a lot of potential if we were to discard theory.

#1 Theories help us better understand the world

I always think of theories as glasses. I can put on different glasses and see the world differently. Through one pair of glasses, I see certain aspects of the world more clearly, and through another pair, I get a completely new perspective.

#2 Theories collect our knowledge

Here, you can imagine theories like a Wikipedia article. Someone writes the first draft, which is then checked, developed further, or even criticized by others. The important thing is always that every scientific work somehow tries to make a contribution, sometimes smaller, sometimes larger.

#3 Theories help in practice

Through theories, we can uncover problems and derive actions to change the world for the better.

And that is a wonderful idea, isn’t it?

Categories
Research Methods

Dependent and Independent Variables in Research (made easy)

Have you ever wondered what the distinction between dependent and independent variables is?

Then you’ve stumbled upon digital gold.

In this article, I will explain to you shortly but precisely what the difference between dependent and independent variables is and what function they play in your quantitative research design.

If you’re still interested after that, I will go a bit more in-depth and explain why this designation of variables in the context of survey studies and other methods is often not correct and how to correctly describe them.

Why do you need dependent and independent variables in a quantitative research design?

In a quantitative research design, your goal is to test a theoretical relationship. One of the building blocks of theory constructs that consist of variables.

In order to test a hypothesis in a quantitative research design, you must first determine the variables of that hypothesis and ensure that you can measure them.

As the name suggests, variables can change. They can experience various forms of change, for example, changing human behavior such as the tendency to choose more organic fruit at the supermarket.

Similarly, a variable can vary by location, such as in counties with the highest subsidies on organic fruit. Moreover, a variable can change over time, such as a fruit vendor’s profit per quarter.

Independent variables are the variables that are manipulated or changed in order to observe the effect on the dependent variable. In our example, the independent variable would be the type of fruit (organic vs. non-organic) and the dependent variable would be the number of fruits sold.

Variables in hypotheses

A hypothesis typically includes two variables and their relationship to each other. It’s about how one variable affects the other, i.e. the hypothesis expresses a relationship between cause and effect.

H: Eating a banana immediately after exercise increases muscle regeneration.

In this hypothesis, eating a banana is the cause. This is the independent variable.

Increased muscle regeneration is the expected effect. This is the dependent variable.

dependent and independent variables

Independent Variables

Ok, and why is the first variable now independent?

That’s because this variable can be varied arbitrarily. The variable could also be “drinking a protein shake”. Or: eating two bananas.

In that sense, this variable does not depend on other variables – hence independent variable.

Dependent Variables

The second variable, which represents the effect, is called dependent because the value of this variable depends on the cause.

In reality, however, independent and dependent variables are often not as clear-cut as they may seem. In many real-world situations, multiple variables can be both independent and dependent at the same time, depending on the specific research question and the level of analysis.

For example, in a study looking at the relationship between income and education, income could be considered the independent variable at the individual level, but when looking at the relationship at the societal level, education could be considered the independent variable.

Additionally, it’s important to note that the cause-and-effect relationship between independent and dependent variables can be difficult to establish as it may be influenced by other factors. That is why we need experiments.

Dependent and independent variables in experimental designs

These terms originated in the context of scientific experiments. To test the example hypothesis, you could set up an experimental design that examines a sample of athletes. Under supervision, each participant receives a banana – this is how the independent variable is measured.

Then they can let off steam during the workout and afterwards their muscle regeneration, the dependent variable, is measured.

In this experiment, the independent variable can now be varied, this is also referred to as “manipulation”.

3 example experiments

Example #1

For an experiment, the temperature inside a car is changed. People sitting in the car indicate how they feel at each temperature. Temperature is the independent variable. The dependent variable is the reported well-being of the occupants.

Example #2

You want to investigate how smartphone usage affects heart rate. The independent variable is smartphone usage and the dependent variable is heart rate.

Example #3

You want to find out how time spent working from home affects the work performance of your employees. In this example, the independent variable is time spent working from home and the dependent variable is work performance.

dependent and independent variables shribe

Dependent and independent variables in cross-sectional studies

In an experiment, data is collected at different times. This allows the study director to manipulate the independent variable.

In studies that only collect data from different individuals at a single point in time, this is not the case. This is also referred to as cross-sectional studies. An example of this is an online survey.

Here, variables cannot be manipulated and thus no causal relationships can be tested. The terminology of independent and dependent variables would therefore be incorrect. Nevertheless, everyone knows what is meant when you talk about it, but if you want to be completely correct, you can use

Predictor variable or prognostic variable instead of independent variable and

Response variable instead of dependent variable in speaking or writing.

After all, predictions about variables are also made in cross-sectional studies – only causality is not assumed.

If you’re interested, the difference between causality and correlation has been discussed in another video that you can find linked on the top right.

For experiments, this designation also works. You could therefore theoretically always use the designation predictor variable and response variable – independent and dependent only in the context of experiments (Field, 2015).

Measuring

Of course, the method is of the utmost importance here. For a quantitative study design, as already mentioned, experiments or standardized surveys such as online surveys can be used. But also collecting sensor data or other measurements or collecting documents, texts or social media data can be the basis for a quantitative research design.

Each method now produces data that has different levels of measurement or scale levels. These scale levels, if you will, decide the quality of your variables and what statistical operations are available to you to test your hypothesis.

dependent and independent variables article

Reliability and Validity of measuring variables

It is important to note that in order to make accurate inferences and conclusions, variables must be measured in a reliable and valid manner. Reliability refers to the consistency of measurement, while validity refers to the accuracy of measurement. For example, if you are measuring the number of organic fruits sold in a supermarket, it is important that the counting method is consistent and accurate.

If your variables are metric scaled, i.e. they consist of numerical values (e.g. number of bananas eaten), then the relationship (depending on the data, causal or correlational) between the dependent and independent variable can be calculated using a regression analysis.

Variables for regression analysis

Exactly how to do this is a topic for another video – but at least you now have a small glimpse of what you can do after determining and measuring your variables.

I hope this was helpful and if you want to delve further into this topic, I recommend the textbooks by Andy Field.

Categories
Research Methods

Quantitative and Qualitative Research Methods (simply explained)

Are you trying to wrap your head around empirical research methods? You keep reading about quantitative and qualitative research methods but what is the difference?

Don’t panic, you will get an easy answer to this question over the next few minutes.

In this video you will learn about the 5 crucial differences between quantitative and qualitative research methods. So not only will you be able to distinguish these two approaches in your sleep, but hopefully you’ll get some valuable ideas for choosing the method for your next scientific work.

What is empirical research?

Before we dive into the differences between qualitative and quantitative research methods, we need to clarify what they have in common. They are both part of what is called empirical research. This means, in a very simplified way, the systematic collection of data to gain knowledge.

In a figurative sense, the “experiences”, i.e. the data, are used to derive new knowledge. This always involves some sort of observations in the real world or with real people. For example, social sciences but also the natural sciences are dominated by empirical research.

In contrast, a mathematician or philosopher, who reaches insights only by thinking and logical reasoning, is not considered empirical. That does not mean one is better or more scientific than the other. They are just different ways to gain scientific knowledge.

In philosophy of science, the question about how researchers can gain knowledge in the first place is subject to epistemology. Look up this term if you want to dive deeper into this.

The two paradigms (quantitative and qualitative)

The distinction between quantitative and qualitative research is the result of more than one century of debates between researchers about what science is and how research should be conducted.

quantitative and qualitative research methods

In a nutshell, two positions emerged based on different philosophical assumptions about how the world is made up (in philosophical terms, this is called ontology). The more sciency scientists were convinced that there is an objective reality that is independent from us humans (in philosophical terms, this world view is called realism). This reality can be measured by using numbers and statistics (in philosophical terms, this world view is called positivism). This was the starting point for quantitative research.

As this thinking was dominant in the academic landscape of the early 20th century, emerging disciplines adopted the same principles. For example, psychologists studying the inner workings of the human mind applied the same natural science-based approach.

Later, this natural science approach to social science led to the emergence of other positions that were not at all happy with this type of thinking.

“Wait a minute,” they said, “don’t you think social phenomena are constructed differently by different groups and individuals?”

They had a point.

A stream of research emerged that was not interested in statistically computing the personality traits of teenagers or how the management of an IBM computer worked (the relevant philosophical terms here are constructivism and interpretivism).

One milestone in advancing the qualitative paradigm was Glaser and Strauss’ (1967) Grounded Theory Methodology. It reversed the deductive logic of testing theory to an inductive logic of generating theory. Until this day, the Grounded Theory Methodology is an important part of qualitative research.

The 5 Differences between quantitative and qualitative research

Now, let’s look at 5 different characteristics of both approaches.

#1 Object of study

Quantitative research investigates large samples and assumes more of an outside view

Qualitative research investigates small samples and assumes more of an inside view

#2 Types of data

Quantitative research relies on numerical data (“hard” and replicable)

Quantity as a characteristic means measuring the amount of a certain unit. Quantitative data is therefore available in large quantities in the best case. But not only the quantity is decisive, but also the quantifiability. This means that these data are unambiguous.

If a test person answers question 1 in a questionnaire with the answer option 3, then this data is unambiguous.

A measurement method of a sensor or the number of comments on a Twitter message is also unambiguous. In the language of statistics, different types of data can be categorized as nominal, ordinal, and metric.

And this brings us to the great advantage of quantitative data: You can apply statistical techniques to analyze it.

Qualitative research relies on linguistic data (“soft” and unique)

Qualitative data are always context-dependent, i.e. the basic conditions of your data collection environment must be taken into account during the investigation. This is particularly important in case studies.

The great advantage of qualitative data is that they can be rich. As a researcher you really get underneath the surface level and can attempt to explain “why” things are the way they are.

#3 Analytical Logic

Quantitative research typically measures things and follows a deductive logic

Qualitative research typically interprets things and follows an inductive logic

Deductive logic means using a general (mental) model to form a specific conclusion. (For example, using a theory to derive hypotheses)

Inductive logic means starting from a very specific example or case and forming a general conclusion. (For example, using interview data to generate a theory)

#4 Methods (Examples)

Quantitative research uses methods such as surveys, experiments, or simulations

Qualitative research uses methods such as interviews or observations

#5 Theoretical Contributions

Quantitative research typically contributes to theory by testing propositions or hypotheses

Qualitative research typically contributes to theory by introducing new concepts, models, or mechanisms

How to choose between quantitative and qualitative methods

If you are faced with the challenge of conducting empirical work, then choosing the right research design is one of the most important decisions of all. It all comes down to your research objectives, i.e. answering your research question(s).

Which research method can best achieve this goal?

quantitative and qualitative research methods

This question is the basis of your consideration. I would like to make it clear that scientific work does not have to be empirical. In many disciplines this would not make sense at all.

Moreover, most scientific disciplines welcome both quantitative and qualitative research. In fact, many researchers see great value in combining quantitative and qualitative research methods. This is called “Mixed Methods”.

The next step you can take is grabbing Creswell’s (2014) classic textbook and dig deeper into what you just learned.

Categories
Scientific Writing

How to Write an Abstract for a Research Paper or Thesis (7 Steps)

You would like to write an abstract for your research paper or thesis? But how should you structure the abstract? What should be included in the abstract?

Here you get all the answers.

Why write an abstract?

The purpose of an abstract is to summarize your research paper or thesis in a short paragraph. The abstract serves as a guide for the readers as to what they can expect in the paper. It contains all the important information about the paper, such as the context, the research relevance and method, and also the main results of the paper.

The abstract is a kind of a mini-version of a research paper.

It is important to understand that the abstract is NOT a teaser. Nothing should be hidden from the reader here, and there must not be a cliffhanger at the end. All the most important findings and contributions should be presented concisely. Hence, no artificial tension should be created in the abstract. The reader’s curiosity automatically results from the relevance of the topic.

Especially in research articles, the abstract is one of the most important parts of a text. This is because it allows an interested reader to decide whether the results obtained or the content of the text are relevant to him. And not only the reader. A paper will also be indexed by databases such as Google Scholar based on the abstract. So make sure all important concepts appear in your abstract.

Even if you are a student and have no interest in publishing your paper whatsoever, your professors want you to come as close as possible to actual scientific work. Therefore, they ask you to write an abstract.

How should the abstract look like?

There are no generally accepted standards for an abstract. In research, they result from the requirements of the publisher, at university from the requirements of your supervisor. If you are unsure, ask for the criteria in the next office hour or check the thesis requirements of your department. A typical abstract is between 150 and 200 words.

Although the criteria are not set in stone, there is a common practice of how how to write an abstract. If you follow these 7 steps, there is not much that can go wrong when writing your abstract.

#1 Context

What is the context of your research? (1 sentence) By context, I mean the real world events that frame your scientific work.

I will now give you an example for each step. At the end, we will have a complete abstract that connects all the steps with each other. All you need to do then is to transfer this example onto your own paper and topic. The example is from a paper by Suh et al. (2010).

how to write an abstract

So for the context sentence, one could write the following:

“Retweeting is the key mechanism for information diffusion in Twitter.”

Note that the key concepts are already mentioned: Retweeting, information diffusion, and Twitter.

#2 Relevance

Why is this topic relevant to your research field? (1 sentence)

This is where your argument practically begins. Why should anyone care about this topic? “Anyone” often means the researchers that are the potential audience of your paper or thesis. But your work could also be of societal or practical importance.

So for the relevance sentence, one could write the following:

“It (retweeting) emerged as a simple yet powerful way of disseminating information in the Twitter social network.”

#3 Problem Definition

What is your research problem? (2 sentences) The research problem is often grounded in the scientific debate. What do we know already? What do we not know? And why is that a problem? Why should we conduct research to address this problem?

So for the problem definition, one could write the following:

“Even though a lot of information is shared in Twitter, little is known yet about how and why certain information spreads more widely than others. In this paper, we examine a number of features that might affect retweetability of tweets.”

#4 Method

What method do you use to approach the problem? (1 sentence) The choice of method is linked precisely to the research problem. It is the toolkit you use to explore and address the problem.

So for the method sentence, one could write the following:

“We gathered content and contextual features from 74M tweets and used this data set to identify factors that are significantly associated with retweet rate. We also built a predictive retweet model.”

#5 Main Results

What are the main results of your paper or thesis? (2 sentences) Remember that the abstract is not a teaser but should include everything there is to know about the study. It is a challenge how to write an abstract but you should be able to summarize the essence of your results in two very concise sentences.

So for the main results, one could write the following:

“We found that, amongst content features, URLs and hashtags have strong relationships with retweetability. Amongst contextual features, the number of followers and followees as well as the age of the account seem to affect retweetability, while, interestingly, the number of past tweets does not predict retweetability of a user’s tweet.”

#6 Contributions

How can researchers (or practitioners) benefit from your work? (1-2 sentences) How would dealing with the research problem advance our knowledge? What part of the research literature would it enrich and how? Theoretically? Methodologically?

And how might possible findings help practice, i.e., professional individuals or organizations?

Here you need to sell your paper a little bit to the audience. For the contribution sentences, one could write:

“This research proposes a framework that explains the theoretical relationships between platform features and information diffusion on microblogging platforms. Moreover, this work informs the design of sensemaking and analytics tools for social media streams.”

#7 Keywords

An abstract most often comes with keywords. Name the 3 to 5 core concepts of your paper or thesis. Those could be: microblogging, Twitter, information diffusion, retweeting.

Conclusion

If you stick to this structure, you will automatically have included all the important information in your abstract. In addition, you can easily use your introduction and adopt some of the sentences you have used there. Do not copy and paste them but change the wording and grammar slightly.

Also make sure that the abstract flows. You can use words such as “Therefore”, “hence”, “consequently”, or “moreover” to connect your sentences and create one coherent piece.

It couldn’t be easier, could it? 🙂

Categories
Scientific Writing

How to get over Writer’s block (fast)

Are you looking for a jumpstart that explains how to get over writer’s block?

You’re in luck.

Because in this very place in the endless expanses of the internet, you’ve found it. I’ve got 5 unbeatable tips for you on how to overcome your writer’s block and get a waterfall of words flowing across your keyboard in no time.

You’re guaranteed to get closer to your goal of writing a term paper, bachelor’s thesis, or your next bestselling novel.

How to solve writer’s block (fast)

Do you know this?

There is no time left for procrastination and you finally have to deliver. The deadline for your project is already looming and you’ve freed up all the time you can for your work.

But you can’t find more than the heading “Introduction” and a sinister ticking cursor in your Word document. Although you are actually good at the subject, the ball doesn’t quite want to get rolling.

You’ve already typed the first sentence three times and discarded it again, because it just sounds ridiculous. The longer you look at the empty document, the more invincible the opponent seems: that darn 15-page paper.

So what can you do to solve your writer’s block?

#1 Recognize the true opponent

The first thing to do is to face your greatest adversary. Face to face. In the mirror. Because the biggest opponent is not your scientific work, but yourself!

EVERYTHING is a matter of motivation; of priorities, discipline and perseverance. The biggest mistake you can make is to develop a negative attitude. The subject is stupid, the lecturer sucks and you have to work on the weekend.

Once you have started to allow such thoughts, you enter into a negative spiral. You won’t get out of this thinking anytime soon. Therefore, it is even more important to link your scientific work with positive thoughts.

Is the topic boring? Examine it from an unprecedented perspective.
The lecturer is a jerk? Show him what you’re made of.
Do you have to use your hard-earned free time to write? Make writing your hobby.

Don’t let external conditions spoil your fun. Strengthen your attitude from within.

Make the writing process an event. You can write a term paper on the beach, in a cozy Starbucks, or at home in bed… How awesome is that?

Once you’ve powered up in mentally, it’s time for the next step.

how to get over writers block

#2 Determine your writing type

When it comes to writing, there are two different types.

First, let it be said that both types of writers can get to their goal equally. So there is no one type that is better or worse than the other. However, in case of a total blackout, one of the two is better able to solve his writer’s block.

The perfectionist (type #1)

Personally, I definitely belong to this group of people. When I write a sentence, it has to be perfect right away. I’d rather rewrite it five times instead of just getting on with it and torturing myself with a tedious revision later.

As a result, my writing progress is a little slower. In the end, however, I save the time again because the first draft is usually already good enough for my needs.

In addition, I tend to write very densely. By that I don’t mean that I’m drunk or stoned while writing, but that I need less text for the content. In scientific papers, this often leads to me having too little text available. Then I have to think afterwards about where I could still add meaningful text modules.

The explorer (type #2)

This type embodies exactly the opposite of a perfectionist. Without giving it much thought, the explorer just writes away. The words pour over the pages, so that within the shortest time the complete amount of the required pages is filled.

People who claim to have written 7 pages of their term paper in one day are explorers. They get started and look afterwards to see where this has taken them. For me, it’s impossible to write that much at once. That’s because explorers put their first draft down on paper without regard for typos or other minor weaknesses.

A text written so quickly is often very light on content. By this I mean that the content is conveyed with the help of a larger number of words. At the end of a scientific paper, explorers have not infrequently simply written twice(!) the required number of pages.

So explorers finish their work very quickly, but must allow time to revise the draft and shorten it.

how to get over writers block shribe

Now what?

So how do these types behave when they have writer’s block?

Well, first and foremost, perfectionists have the potential to write great work. So if you deliver the perfect draft in the first pass, that’s exceptionally good.

But if you insist on remaining a perfectionist when you’re experiencing with writer’s block, you’re doomed.

#3 Get rid of your perfectionism

If you don’t produce any text at all, or only very little, you’re facing a problem: the pressure is mounting.

That’s why, when you have writer’s block, it can be useful to remember the virtues of the explorers. Text is still better than no text. Later on, you can still let your perfectionism rule, but during writer’s block, it’s your death sentence.

This is where getting into the writing flow matters. Correcting spelling, grammar, or expression is something you can do once you’ve cracked the magic page number. Be sure to allow time for this, because turning in a sloppy draft is not the point, of course.

As an explorer, however, you make progress piece by piece. You notice how something is happening. The pages in your document become more and more.

This is good for your conscience and takes the pressure off your shoulders. In contrast to perfectionists, who remain on the first page, explorers are the ones who are unleashed.

#4 Keep a diary

A popular exercise for perfectionists who are blocked: Journal writing. Grab your journal, calendar, or open a blank document and start writing. Formulate sentences about how you’re currently sitting in front of your laptop writing.

Look out the window and just type into the keyboard whatever pops into your head. It doesn’t matter if these words make sense or not. The main thing is that you write.

Alternatively, you can think of a little story. Just keep writing. Do this for about 10 minutes and then seamlessly move on to your scientific work. You’ll be amazed, but your fingers are much looser on the trigger than before.

#5 Use your flow experience

If one or a combination of these methods and techniques has led you to get the first sentences down on paper – by all means keep at it. Don’t get carried away and interrupt the flow again.

Instead, grab your keyboard and use it as your surfboard. That way, you can ride the flow wave and move inexorably toward finishing your work.

Here you can take advantage of a principle that is actually known from physics. Once you get the proverbial ball rolling, you need less energy to keep it rolling than it took you to get it started.

Believe me, once you get started, the rest of your work is a breeze. Now stretch your finger muscles and get ready for your writing marathon. Let’s go!

Categories
Scientific Writing

How to Select a Research Topic for a Thesis or Dissertation (3-Step-Guide)

Do you want to select a research topic for your thesis or dissertation, but you don’t really know how and where to start looking?

Then you’ve stumbled upon the perfect article here.

Because in the next few minutes, I’m going to tell you 3 steps I would take if I were looking for a research topic for my thesis, dissertation, or paper.

If you follow these 3 steps, you will not only get rid of your doubts and indecisiveness – no, after this exercise you can already write the email to potential supervisors and submit them a proposal they can’t refuse.

#1 Supervisor Screening

The first suggestion I’d like to make is perhaps a bit unconventional. But if you want to get an outstanding grade AND have fun with your thesis, here’s what I would do if I were you.

Don’t put the potential content of your research at the beginning of your topic identification process, but rather a person.

Why?

Well, think about it. If you find a supervisor with whom you get along great, how does that affect you?

The mentoring conversations are informal and fun. A person with whom you are on the same wavelength is likely to be enthusiastic about the same topics as you are.

The person will offer to help you more and more often if they like you. Hence, the likelihood that you’ll get a bad grade drops precipitously. So, the first step on how to select a research topic is to identify your preferred supervisor. In doing so, you can look at these criteria:

  • How good was your experience with him or her during your studies?
  • What topics does this person advertise on their website?
  • Is this person actively doing research, i.e. can you find recent publications on their website? On which topics?
  • Is this person an experienced professor or research assistant (PhD student, post-doc)?

Your favorite lecturer is not your favorite lecturer because he or she has nice hair. Most of the time, your enthusiasm for their course comes through the topics anyway. Now write down your 3 favorite topics you found while researching this person.

If you are studying at a university, research assistants and post-docs can also supervise your work. Always prefer these people over a professor. For three reasons:

  • They have to do their own research (PhD students) or prove themselves with publications (post-docs).
  • The motivation of this person to use a thesis for their research is much higher
  • A bad thesis serves this person nothing at all; therefore the supervision becomes all the better

Professors who have hung up their research boots don’t care if your thesis is good or bad.

#2 Read, read, read

When it comes to a selecting a research topic, reading is by far the biggest lever you can apply. You can think back and forth as much as you want – it’s all wasted time. Just don’t think about a possible topic at all, but read into the 3 topics from step 1 as much as you can allow yourself.

Slowly approach the topic of your research

Start with light fare to get a gentle introduction: YouTube, popular science articles or documentaries. This usually doesn’t hurt that much and is fun.

Then you dare to tackle the scientific literature. Here, the following principle applies to finding a topic:

For now, topicality is more important than the basics.

If one of your 3 topics is e-learning, then knowing the history and roots of e-learning will not help you in finding a topic. It is more important to know how the topic has been researched in the last 1-3 years and which acute questions arise in this area.

So, when searching for reading material, be sure to use literature databases where you can find journal articles and conference proceedings.

The Special Issue Hack

One trick to select your research topic lies in so-called “special issues”. These are calls for papers from scientific journals that want research on specific topics. Here, smart people (the editors) have thought about what research questions would be really important right now. So they have practically already done the work for you! In addition, you will find in such calls even a small bibliography with reading recommendations. So you get suggestions for topics as if served on a silver platter. Isn’t that practical?

You can find these calls for papers on the websites of the journals. If you don’t know which journals are relevant for your topic, go back to the publication list of your potential supervisor from step 1 and write down the journals in which he or she has already published.

#3 Combination and Inquiry

To avoid choosing the exact same topic that has already been researched by your supervisor, you need to add a little original twist to your research topic. If you didn’t find what you were looking for in the calls for papers, or if people in your discipline tend to only research books, try the following:

Combine the topic you’re most interested in with a current phenomenon, technology, or theory.

The topic you finally choose should not only be interesting, but also relevant. And you achieve relevance by addressing a research problem.

If you now combine your favorite topic with a second component, in most cases the result is such a dynamic topic that a relevant research problem can easily be derived from it. Here are a few examples:

  • E-learning + AI
  • Enterprise + Digital Nomadism
  • School education + Virtual Reality
  • Democracy + Bitcoin
  • Cryptocurrencies + Climate Change
  • E-mobility + 3-D printing
  • Retirement + Social Media

I think you see the pattern. So now think about what research problem arises from such a combination and how you might approach this problem methodologically. Qualitatively? Quantitative? With literature work?

The next step on how to select a research topic would be to derive a research question. For this, you take your chosen topics or some aspects of it and take those as variables. Then you simply ask for the relationship between the two. For example:

How does Virtual Reality affect the Cognitive Load of school children between the ages 12-15?

Additionally, I’ve added a theory to the mix. I explain how and why you should do this in my tutorial on how to develop a research question.

how to select a research topic-shribe

Conclusion

Be prepared for presenting a preliminary research question in your inquiry to your potential supervisor. Present him or her with a topic for your research that fits in with her own research, has an original and current twist, and is fun for both of you.

This way, you’re guaranteed to open doors with your request and lay a fantastic foundation for your research.

Categories
Scientific Writing

How to Write a Conclusion for a Research Paper (or thesis)

Your scientific work is on the home stretch and you just have to write your conclusion? In this article, I’ll give you a guide on how to write a conclusion for your research paper, bachelor thesis, or master thesis that will tip the scales in favor of an outstanding grade.

Writing a conclusion is not an art. Rather, it is a technique that you can learn in just a few steps.

The Conclusion of a Research Paper

Before I present you with an exact guide to writing a conclusion, let’s clarify one more thing: What is a conclusion good for anyway?

Sometimes, instead of ‘conclusion’, the terms résumé or outlook appear in the academic vocabulary. To cut to the chase, a conclusion is meant to be an evaluative summary of your work. It is one of the main pillars of an academic paper and requires a lot of attention. In the conclusion, you are required to present the results of your work and demonstrate to your reader why your work was sensationally good.

Remember, the conclusion of your paper is usually read last. Accordingly, it is the part of the work that will be remembered. Here, you need to be extra careful when writing your conclusion and make use of some tricks on how to write a conclusion for a research paper.

The Outline for a Conclusion

In my opinion, this is best possible outline for your conclusion:

  • A summary of your findings
  • The answer(s) to the research question(s)
  • Added value for science/seminar
  • Added value for practice (if applicable)
  • Limitations
  • Further research

Now let’s dive into an exact guide on how to address each point.

How to write a conclusion for a research paper or thesis shribe example

7 Basic Rules for Writing a Conclusion

A conclusion, just like other parts of a scientific paper, needs a clear structure. Before we go through this structure in detail, you need some background information to prepare you for writing your conclusion.

Identify the Audience of your Work #1

First of all, you should be aware of whom you address (this also applies to the rest of your text). If you are not preparing a research paper for an international conference or journal, the only reader (with the exception of your mum) is your lecturer or professor!

When writing your conclusion, imagine how you will sell your research results to your professor. Accordingly, you should not tell her anything that she already knows and that would bore her. Rather, you can make it your task to convince her of a real added value of your work for her field of research.

If your paper relates to a specific seminar or course, reflect on the results in light of the topics covered during the semester and place them in a meaningful overall context.

Write your Conclusion on a Meta Level #2

Just like the introduction, the conclusion should be approached a bit differently than the main body. Instead of moving on with your content, you should zoom out and “write about writing” in these parts of the paper.

This means that you do not add any new sources or insights in your conclusion except for limitations and recommendations for future research. A conclusion only refers to the findings you have already written down in the main body of your paper, such as in the results and discussion sections.

Summarize your Results #3

Now we come to the actual content of your conclusion. Start with some introductory words and explain what you are going to do in the following. Also explain why you are doing it. For example, you will summarize the main points of the results discussed above, in order to make them explicit with regard to the research question. Also, when writing a conclusion, this step is helpful in placing your findings in the context of the research gap you identified at the beginning.

Do not proceed chronologically in your “summary” so that the reader does not get too bored. Try to restate your findings along the lines of your argument and the idea of your paper.

Close all open Loops #4

One of the most important steps on how to write a conclusion for a research paper is to concisely repeat the answer to the research question you posed at the beginning of your paper. In doing so, you must abstract your results to such an extent that they point purposefully to the problem of your work in just a few sentences. Explain your results in an understandable way and explain how they build on existing literature.

Sell the Added Value of your Results #5

The idea behind research papers always implies creating added value for the scientific community. In a thesis or term paper, this principle can be practiced. Therefore, you should try to carve out a unique contribution, even if it is “just” a paper that only your lecturer will ever read.

The closer you get to the principle and requirements of scientific work, the better your grade will be in the end.

How do you convince a reader of your contributions?

Argue how your work and its results could be useful. For theory, the general state of knowledge, individuals, organizations, or society. It is common to distinguish between added value (=contribution) for theory and knowledge and added value for practice. Practical implications also depend on the field of study. Work in technical fields or business administration often has a higher relevance for practice. In contrast, humanities scholars often work within the boundaries of a scientific debate. If your work can do both, all the better.

How to write a conclusion for a research paper or thesis shribe

Explain Limitations #6

Again, we are at the meta-level, reflecting on our own work. When writing your conclusion, point out any hurdles that stood in the way of your work. For example, did you not have access to certain data? Was your sample small, but justifiable for the scope of a thesis? Did you only look at one set of facts (case study) and lack a means of comparison?

Be honest, but don’t completely pick apart your work, after all, you want to sell it as outstanding. In addition, you should not invent any limitations, but at best have made notes on them during your work. The limitations should be plausible, but not caused by your own fault. A good way to deal with limitations is to refer to further research opportunities.

Make Recommendations for Further Research #7

Finally, you can give a preview of what other areas you would like to explore in further research (even if you never work on this topic again). Suggest which studies, methods, and open questions could be addressed in the future. This not only shows interest, but also demonstrates foresight and competence.

Bonus: Miscellaneous Questions

What length should you aim for when writing the conclusion? As always, the length of the conclusion should be based on the length of the entire paper. About 10 percent of the entire text.

If possible, the above steps should be worked through in the suggested order. Subheadings are rather unusual, but quite possible in a thesis with a very long conclusion.

Now you are left with one very last sentence that you can use to stick in your reader’s mind. Choose a strong statement that will leave a lasting impression.