Discussion Example

[Achill Baldwin]

Inthis blog, we look at how to write the discussion section of a research paper. We will go through plenty of discussion examples and understand how to construct a great discussion section for your research paper.

The discussion section is one of the most important sections of your research paper. This is where you interpret your results, highlight your contributions, and explain the value of your work to your readers. This is one of the challenging parts to write because the author must clearly explain the significance of their results and tie everything back to the research questions.

It is a good idea to start your discussion section with the summary of your work. The best way to do this will be to restate your research question, and then reminding your readers about your methods, and finally providing an overall summary of your results.

The next step is to compare your results to the literature. You have to explain clearly how your findings compare with similar findings made by other researchers. Here is a discussion example where authors are providing details of papers in the literature that both support and oppose their findings.

Our analysis predicts that climate change will have a significant impact on wheat yield. This finding undermines one of the central pieces of evidence in some previous simulation studies [1-3] that suggest a negative effect of climate change on wheat yield, but the result is entirely consistent with the predictions of other research [4-5] that suggests the overall change in climate could result in increases in wheat yield.

The next step is to explain to your readers how your findings will benefit society and the research community. You have to clearly explain the value of your work to your readers. Here is a discussion example where authors explain the implications of their research.

The results contribute insights with regard to the management of wildfire events using artificial intelligence. One could easily argue that the obvious practical implication of this study is that it proposes utilizing cloud-based machine vision to detect wildfires in real-time, even before the first responders receive emergency calls.

In this paper, the authors are saying that their findings indicate that Artificial intelligence can be used to effectively manage wildfire events. Then, they are talking about the practical implications of their study. They are saying that their work has proven that machine learning can be used to detect wildfires in real-time. This is a great practical application and can save thousands of lives. As you can see, after reading this passage, you can immediately understand the value and significance of the work.

Study design and small sample size are important limitations. This could have led to an overestimation of the effect. Future research should reconfirm these findings by conducting larger-scale studies.

Here is a discussion example where the author talks about study limitations. The authors are saying that the main limitations of the study are the small sample size and weak study design. Then they explain how this might have affected their results. They are saying that it is possible that they are overestimating the actual effect they are measuring. Then finally they are telling the readers that more studies with larger sample sizes should be conducted to reconfirm the findings.

It is important to remember not to end your paper with limitations. Finish your paper on a positive note by telling your readers about the benefits of your research and possible future directions. Here is a discussion example where the author talks about future work.

Our study highlights useful insights about the potential of biomass as a renewable energy source. Future research can extend this research in several ways, including research on how to tackle challenges that hinder the sustainability of renewable energy sources towards climate change mitigation, such as market failures, lack of information and access to raw materials.

The authors are starting the final paragraph of the discussion section by highlighting the benefit of their work which is the use of biomass as a renewable source of energy. Then they talk about future research. They are saying that future research can focus on how to improve the sustainability of biomass production. This is a very good example of how to finish the discussion section of your paper on a positive note.

Sometimes you will have negative or unexpected results in your paper. You have to talk about it in your discussion section. A lot of students find it difficult to write this part. The best way to handle this situation is not to look at results as either positive or negative. A result is a result, and you will always have something important and interesting to say about your findings. Just spend some time investigating what might have caused this result and tell your readers about it.

You must talk about the limitations of your work in the discussion section of the paper. One of the important qualities that the scientific community expects from a researcher is honesty and admitting when they have made a mistake. The important trick you have to learn while presenting your limitations is to present them in a constructive way rather than being too negative about them. You must try to use positive language even when you are talking about major limitations of your work.

When you choose to publish with PLOS, your research makes an impact. Make your work accessible to all, without restrictions, and accelerate scientific discovery with options like preprints and published peer review that make your work more Open.

Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts.

While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results!

I recently saw a great LinkedIn post from Morten Nielsen on a 3D printed 'black box' tool to practically teach to complete DoE novices and it got me thinking about what examples work best to teach DoE. I'm sure a lot of us have been through the paper helicopter example in our time, which is a great (and more importantly, fun!) example and pairs nicely with the Prediction Profiler tool - but it uses mainly categorical factors and can take a long time for novices to perform.

My 'go to' experiential DOE learning tools were the paper helicopters and some version of the 'Statapult'. Back in my day of training Eastman Kodak Company Six Sigma Black Belts we used a custom designed and fabricated statapult that had a combination of discrete numeric (eg. number of rubber bands), continuous ( eg. arm length), and categorical factors (eg. ball type, like foam, solid plastic, plastic with holes). The team had to design their own measurement system. People did things like build a sand filled landing pit (think long jump pit) or two people estimating landing point along a tape measure, average the observations. The statapult was a great tool because it so much emulated real life in the lab or production. People got confused, it broke, nuisance variables galore, you name it it happened. One participant moaned about all the operational issues...another on their team told them something like, '...this is what happens in real life...learning how deal with these issues is half of what we're learning here...not just statistics'.

Another, more specialized choice was in our Measurement Systems Analysis module. At the end of the module we had teams set up a typical MSA study...which is still a designed experiment, just with special characteristics like nesting, crossing, replication, operators, devices, and on and on plus specialized analysis methods...which we focused on Wheeler's EMP approach. The teams were given a response...which was the 'length in inches of a plastic straw'. They were given multiple devices to assess length. Things like a plastic ruler, calipers, a micrometer, etc. Then told to define a measurement system and analyze the results using Wheeler's method. But we threw a few monkey wrenches at them. There were 4 or 5 straws that were the 'parts'. One straw had a beveled edge...so there was always lots of conversation about how to actually measure length...when one end of the straw has two distinct end points. One straw was too long to fit in the jaws of the caliper. One 'device' was delineated in metric...so they had to do a conversion to inches. This module was always lots of fun to watch the participants work through all the issues.

In my classes, I have the participants run several hands-on experiments (they start with basic (tablet dissolution rate) to complex (optimizing the flight of a balsa airplane) requiring multiple iterations). These are both educational and entertaining. I also require students to apply the methodology to their work environment. They must design multiple experiments on projects they are working on (not necessarily run them). In addition, I have them run an experiment on something they enjoy personally. I give them Bill Hunter's "101 DOE Ideas" paper and "DOE It Yourself Fun science projects compiled by Mark J. Anderson, Principal, Stat-Ease, Inc.

3a8082e126