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Understanding science is important. Not just for engineers and doctors, but for all of us. Knowledge and scientific literacy can give us the knowledge and support to make decisions, stay healthy, remain productive and become successful. There's a chain of communication and transmission that takes scientific discovery from the lab to our everyday lives. Scientists publish articles in academic journals. Exciting or important discoveries make the news and may even be incorporated into law.
Let's start with the definition of communication in science.
Communication in science refers to the transmission of ideas, methods and knowledge to non-experts in an accessible and helpful way.
Communication puts scientists' discoveries out into the world. Good science communication allows the public to understand the discovery and can have many positive effects, such as:
Improving scientific practice by providing new information to make methods safer or more ethical
Promoting thought by encouraging debate and controversy
Education by teaching about new scientific discoveries
Fame, income and career enhancement by encouraging groundbreaking discoveries
Scientific communication can be used to influence law! An example where this has occurred is the Montreal Protocol. In the 1980s, a scientist named Paul J. Crutzen discovered that CFCs (chlorofluorocarbons) damaged the ozone layer. His report brought the dangers of CFCs to the public eye. In 1987, the United Nations produced the Montreal Protocol. This international agreement limited the production and use of CFCs. Since then, the ozone layer has recovered. Crutzen's scientific communication helped to save the planet!
Good scientific communication should be:
Good science communication does not require the audience to have any scientific background or education. It should be clear, accurate, and easy for anybody to understand.
Scientific research and communication need to be unbiased. If it's not, bias can contribute to false conclusions and potentially mislead the public.
Bias is a movement away from the truth at any stage in the experiment. It can happen intentionally or unintentionally.
Scientists should be aware of possible sources of bias in their experiments.
In 1998, a paper was published suggesting that the MMR vaccine (which prevents measles, mumps and rubella) led to children developing autism. This paper had a severe case of selection bias. Only children who already had an autism diagnosis were selected for the study.
Its publication led to an increase in measles rates and negative attitudes towards autism. After twelve years, the paper was withdrawn for bias and dishonesty.
To reduce bias, scientific discoveries are subject to peer review. During this process, editors and reviewers check the work and look for any bias. If the article's bias affects the conclusions, the paper will be rejected for publication.
Scientists use two types of communication to showcase their work to the world and other fellow scientists. These encompass - inward-facing and outward-facing.
Inward-facing communication is any form of communication that takes place between an expert and an expert in their chosen fields. With scientific communication, this would be between scientists from similar or different scientific backgrounds.
Scientific inward-facing communication would include things like publications, grant applications, conferences and presentations.
In contrast, outward-facing communication is directed toward the rest of society. This type of scientific communication is typically when a professional scientist communicates information to a non-expert audience.
Scientific outward-facing communication includes newspaper articles, blog posts, and information on social media.
Whatever communication type, it is essential to tailor the communication style to the audience and their level of understanding and experience. For example, scientific jargon is appropriate for inward-facing communication but unlikely to be understood by non-scientists. Overuse of complicated technical terms may distance scientists from the public.
When scientists make a discovery, they need to write up their results. These results are written in the form of scientific articles, which detail their experimental methods, data and results. Next, scientists aim to publish their articles in an academic journal. There are journals for every subject, from medicine to astrophysics.
Authors must adhere to the journal's guidelines regarding length, format and referencing. The article will also be subject to peer review.
Thousands of articles are published annually, so only those considered groundbreaking or important will reach other forms of media. The article's information or critical messages will be shared in newspapers, television, textbooks, scientific posters, and online via blog posts, videos, podcasts, social media, etc.
Bias can occur when scientific information is presented in the media. The data of scientific discoveries themselves have been peer-reviewed. However, the way the findings are given is often oversimplified or inaccurate. This makes them open to misinterpretation.
A scientist studied Sunnyside Beach. They found that during July, the number of shark attacks and ice cream sales rocketed. The next day, a reporter went on TV and declared that ice cream sales caused shark attacks. There was widespread panic (and dismay for ice cream van owners!). The reporter had misinterpreted the data. What actually happened?
As the weather got warmer, more people bought ice cream and went swimming in the sea, increasing their chances of getting attacked by a shark. Sales of raspberry ripple had nothing to do with sharks!
During your GCSEs, you'll be doing some scientific communication yourself. There are a few useful skills to learn that will help you out.
Not all data can be shown in the same way. Suppose you wanted to show how temperature affects the rate of a reaction. What type of graph is more suitable - a scatter plot or a pie chart?
Knowing how to present your data is a helpful skill in scientific communication.
Bar Charts: these charts display the frequencies of categorical data. The bars are the same width.
Histograms: these charts display classes and frequencies of quantitative data. The bars can be different widths, unlike bar charts.
Pie Charts: these charts display the frequencies of categorical data. The size of the 'slice' determines the frequency.
Scatter Plots: these charts display continuous data with no categorical variables.
To create graphs, you need to be able to convert numbers into different formats.
A scientist surveyed 200 students to discover their favourite science subject. 50 of these 200 students preferred physics. Can you convert this number into a simplified fraction, a percentage and a decimal?
The ability to write and present effectively is essential for good scientific communication.
Make sure your report is clear, logical and well-structured. Check for spelling or grammar mistakes and add visual representations of your data, such as graphs.
Good scientists know how to analyse their data.
You may need to calculate the slope of a straight line graph. To do this, pick two points along the line and note their coordinates. Calculate the difference between the x-coordinates and the y-coordinates.
The x-coordinate (i.e. going across) always goes first.
Once you've worked out the differences, divide the difference in height (y-axis) by distance (x-axis) to find out the angle of the slope.
Maths-based questions will often ask for an appropriate number of significant figures. Significant figures are the first important digits after zero.
0.01498 can be rounded into two significant figures: 0.015.
The mean is the average of a set of numbers. It is calculated by taking the sum and then dividing that by how many numbers there are.
The range is the difference between the smallest and largest numbers in the set.
A doctor asked three friends how many apples they eat in a week. The results were 3, 7, and 8.
Think about what the mean and range would be for this data set.
Mean = (3+7+8)/3 = 18/3 = 6
Range = 8 (largest number in set) - 3 (smallest number in set) = 5
Studying data in a table or a graph can allow you to predict what will happen. Predict how tall this plant will be when it's five weeks old.
|7 days||6 cm|
|14 days||12 cm|
|21 days||18 cm|
|28 days||24 cm|
You'll probably need to describe this trend and draw a graph to represent this data.
You can also use data to make a hypothesis.
A hypothesis is an explanation that leads to a testable prediction.
Your hypothesis for the plant growth could be:
"As the plant gets older, it gets taller. This is because the plant has time to photosynthesise and grow."
Sometimes, you are given two or three hypotheses. It's up to you to figure out which one best explains the data.
To learn more about Hypotheses and Predictions check out our article on it!
Good scientists always evaluate their work to perform a better experiment next time:
Your data should be accurate and precise.
Accuracy is how close a measurement is to the true value.
Precision is how close measurements are to each other.
If an experiment is repeatable, you could do it again and achieve the same results.
Your results may vary slightly due to random errors. These errors are inevitable, but they won't ruin your experiment.
Repeating your measurements and calculating the mean can help to reduce the impact of errors, thus improving the precision of your experiment.
An anomalous result doesn't fit with the rest of your results. If you can work out why it's different to the others (for example, you might have forgotten to calibrate your measuring equipment), you can ignore it when processing your results.
1. Ana-Maria Šimundić, Bias in research, Biochemia Medica, 2013
2. AQA, GCSE Combined Science: Synergy Specification, 2019
3. BBC News, Tasmanian Tiger: Scientists hope to revive marsupial from extinction, 2022
4. CGP, GCSE AQA Combined Science Revision Guide, 2021
5. Courtney Taylor, 7 Graphs Commonly Used in Statistics, ThoughtCo, 2019
6. Diana Bocco, Here's What Stephen Hawking's Net Worth Was When He Died, Grunge, 2022
7. Doncho Donev, Principles and Ethics in Scientific Communication in Biomedicine, Acta Informatica Medica, 2013
8. Dr Steven J. Beckler, Public understanding of science, American Psychological Association, 2008
9. Fiona Godlee, Wakefield’s article linking MMR vaccine and autism was fraudulent, BMJ, 2011
10. Jos Lelieveld, Paul J. Crutzen (1933–2021), Nature, 2021
11. Neil Campbell, Biology: A Global Approach Eleventh Edition, 2018
12. Newcastle University, Science Communication, 2022
13. OPN, Spotlight on SciComm, 2021
14. Philip G. Altbach, Too much academic research is being published, University World News, 2018
15. St Olaf College, Precision Vs. Accuracy, 2022
Communication in science is important to improve scientific practice, promote thought and debate, and educate the public.
Academic journals, textbooks, newspapers and infographics are examples of scientific communication.
Appropriate presentation of data, statistical analysis, using data, evaluation and good writing and presentation skills are key to ensure effective scientific communication.
Science communication should be clear, accurate, simple and understandable.
What is communication in science?
Communication in science refers to the transmission of ideas, methods and knowledge to non-experts in an accessible and useful way.
Which of the following is not a key principle of science communication?
Where do scientists publish their articles?
Scientists publish their articles in academic journals.
What is bias?
Bias is a movement away from the truth at any stage in the experiment process.
Bias is always intentional. True or false?
How do scientists reduce bias?
Scientists peer review each other's articles to check the work and look for bias.
Why are scientific discoveries often misinterpreted in media?
The presentation of discoveries in media is often oversimplified or inaccurate.
Which of the following charts displays the frequency of categorical data?
What are significant figures?
Significant figures are the first important digits after zero.
What is the mean?
The mean is the average of a set of numbers.
What is the range?
The range is the difference between the smallest number and the largest number in a set.
What is a hypothesis?
A hypothesis is an explanation that leads to a testable prediction.
What is an anomalous result?
An anomalous result doesn't fit with the rest of your results
What does precision measure?
Precision measures how close measurements are to each other.
What chart is suitable for displaying continuous data?
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