Once you have done some research and have some results, it is time to present these to the outside world. This might be as an abstract, a poster, a data-blitz talk, a full talk, a journal article, a grant proposal … it doesn’t matter, the principle of good scientific presentation is always the same, and that is to follow the zoom-in/zoom-out rule:
(1) The broad question your research is addressing
(2) The specific hypothesis behind your experiment
(3) The prediction(s) made by the hypothesis
(4) An explanation of your experiment and how it is tests for these predictions
(5) Whether the results do or don’t conform to the prediction(s)
(6) Whether the hypothesis is therefore supported
(6) Implications for the broad question your research is addressing
When students first start presenting, they often assume that everyone else in the entire scientific world is more knowledgeable than they are and don’t need to be told the basic background. It feels like this:
In fact, the reality is more like this:
So you need to make it easy on your audience, who will mostly be grappling with unfamiliar concepts as they try to wade through all your material (and it does unfortunately feel like wading, sometimes through treacle).
Question: Your audience may not know much about your research area so it is important to start with some broad background – what is the general question behind your research? Is it “How is memory formed”? “How do we navigate?” “How do we recognise objects”? etc
Hypothesis: You then need to isolate a part of your broad question in the form of a specific hypothesis. A hypothesis starts with a body of knowledge, and addresses a gap in it. Scientists think they know what ought to go in that gap but they aren’t sure – that guess is the hypothesis. Note that a hypothesis is usually not the same as a prediction. A hypothesis might be something like “Memory is formed by changes in connection strength between neurons”. It is relatively general, but less general than the overarching question.
Prediction: Research is about testing hypotheses and to do this the slightly vague hypothesis needs to be concretized in the form of a specific prediction. If my hypothesis is true, then x should happen. If memory is formed by changes in connection strength then blocking these changes should impair memory. It is possible to make many predictions from a hypothesis – the ones you want are (a) testable, and (b) bi-directional. By that, I mean that if the prediction occurs then the hypothesis is supported BUT ALSO if it doesn’t occur then the hypothesis is refuted. Many proposals I see satisfy the first of those but not the second – If the prediction occurs, great, but if it doesn’t then we aren’t any further forward. Hopefully this didn’t happen to you.
Experiment: Then you need to describe your experiment, with the methodology, and explain how it is testing for the prediction.
Results: Do they or don’t they conform to the prediction?
Conclusion about the hypothesis: Is the hypothesis therefore supported or refuted?
Consequence for the big question: Often forgotten, but very important
This all seems rather simple and obvious but it is amazing how many of these steps are often omitted. It is helpful to the reader or listener to have these made very explicit, as headings on your poster, or bold font, or outlined, or in separate paragraphs, or in some other way made visually distinct, to save them mental effort and help them concentrate on your actual results.
Here’s the take-home message: