One of the first tasks a scientist or curious person must undertake before experimentation is the formulation and positing of a scientific question. A scientific question is an extremely narrow question about reality which can be answered directly and specifically by data. Scientists pose scientific questions about obscure aspects of reality with the intent of discovering the answer via experimentation. After experimentation, the results of the experiment are compared with their most current explanation of reality, which will then be adjusted if necessary. In the laboratory, the original scientific question will likely take many complicated experiments and deep attention paid before it is answered.
For everyone else, the scientific question and experimental response is much more rudimentary: if you have ever wondered what the weather was like and then stepped outside to see for yourself, you have asked a very simple and broad scientific question and followed up with an equally simple experiment. Experiments render data, which is used to adjust the hypothesis, the working model that explains reality: upon stepping outside, you may realize that it is cold, which supports your conception of the current time being winter.
Of course, a truly scientific hypothesis will seek to explain the ultimate cause as well as the proximate cause, but we’ll get into what that means later. For now, let’s investigate the concept of the hypothesis a little bit more so that we can understand the role of the scientific question a bit better.
Informally, we all carry countless hypotheses around in our head, though we don’t call them that and almost never consider them as models of reality that are informed by experimentation because of how natural the scientific process is to us. The hypotheses we are most familiar with are not even mentioned explicitly, though we rely on them deeply; our internal model of the world states that if we drop something, it will fall.
This simple hypothesis was likely formed early on in childhood, and was found to be correct over the course of many impromptu experiments where items were dropped and then were observed to fall. When our hypotheses are proven wrong by experimentation, our response is surprise, followed by a revision of the hypothesis in a way that accounts for the exception. Science at its most abstract is the continual revision of hypotheses after encountering surprising data points.
If we drop a tennis ball onto a hard floor, it will fall– then bounce back upward, gently violating our hypothesis that things will fall when dropped. Broadly speaking, our model of reality is still correct: the tennis ball does indeed fall when dropped, but we failed to account for the ball bouncing back upward, so we have to revise our hypothesis to explain the bounce. Once we have dropped the tennis ball a few more times to ensure that the first time was not a fluke, we may then adjust our hypothesis to include the possibility that some items, such as tennis balls, will bounce back up before falling again.
Of course, this hypothesis adjustment regarding tennis balls is quite naive, as it assigns the property of bouncing to certain objects rather than to a generalized phenomena of object motion and collision. The ultimate objective of the scientific process is to resolve vague hypotheses into perfect models of the world which can account for every possible state of affairs.
Hypotheses are vague and broad when first formed. Violations of the broad statements allow for clarification of the hypothesis and add detail to the model. As experiments continue to fill in the details of the hypothesis, our knowledge of reality deepens. Once our understanding of reality reaches a high enough level, we can propose matured hypotheses that can actually predict the way that reality will behave under certain conditions– this is one of the holy grails of scientific inquiry. Importantly, a prediction about the state of reality is just another type of scientific question. There is a critical caveat which I have not yet discussed, however.
Hypotheses must be testable by experimentation in order to be scientific. We will also say that hypotheses must be falsifiable. If the hypothesis states that the tennis ball bounces because of magic, it is not scientific or scientifically useful because there is no conceivable experiment which will tell us that “magic” is not the cause. We cannot interrogate more detail out of the concept of “magic” because it is immutable and mysterious by default.
Rather than filling in holes in our understanding of why tennis balls bounce, introducing the concept of magic as an explanation merely forces us to re-state the original question, “how does a tennis ball bouncing work?” In other words, introducing the concept of “magic” does not help us to add details which explain the phenomena of tennis balls bouncing, and ends up returning us to a search for more details. In general, hypotheses are better served by only introducing new concepts or terminology when necessary to label the relation of previously established data points to each other. The same could be said for the coining of a new term.
Now that we are on the same page regarding the purpose of scientific questions– adding detail to hypotheses by testing their statements– we can get into the guts of actually posing them. It’s okay if the scientific question is broad at first, so long as increasing levels of understanding allow for more specific inquiry. The best way to practice asking a basic scientific question is to imagine a physical phenomenon that fascinates you, then ask how it works and why. Answering the scientific question “why” is usually performed by catching up with previously performed research. Answering “how” will likely involve the same, although it may encounter the limit of human knowledge and require new experimentation to know definitively. I am fascinated by my dog’s penchant for heavily shedding hair. Why does my dog shed so much hair, and how does she know when to shed?
There are actually a number of scientific questions here, and we must isolate them from each other and identify the most abstract question we have first. We look for the most abstract question first in order to give a sort of conceptual location for our inquiry; once we know what the largest headline of our topic is, we know where on the paper we can try to squint and resolve the fine print. In actual practice, finding the most abstract question directs us to the proper body of already performed research.
Our most abstract question will always start with “why”. Answering “why” will always require a more comprehensive understanding of general instances that govern the phenomena in question, whereas “what” or “how” typically refers to an understanding that is limited to a fewer instances. So, our most abstract question here is, “Why does my dog shed so much?”
A complete scientific explanation of why the dog sheds will include a subsection which describes how the dog knows when to shed. Generally speaking, asking “why” brings you to the larger and more comprehensively established hypothesis, whereas asking “how” brings you to the more narrow, less detailed, and more mechanistic hypothesis. Answering new questions of “why” in a scientific fashion will require answering many questions of “how” and synthesizing the results. When our previously held understanding of why is completely up-ended by some new explanation of how, we call it a scientific revolution.
At this point in human history, for every question we can have about the physical world, there is already a general hypothesis which our scientific questions will fall under. This is why it is important to orient our more specific scientific questions of “how” properly; we don’t want to be looking for our answer in the wrong place. In this case, we can say that dogs shed in order to regulate their temperature.
Temperature regulation is an already established general hypothesis which falls under the even more general hypothesis of homeostasis. So, when we ask how does the dog know when to shed, we understand that whatever the mechanistic details may be, the result of the sum of these details will be homeostasis of the dog via regulated temperature.
Understanding the integration between scientific whys and hows is a core concept in asking a good scientific question. Now that we have clarified the general “why” by catching up with previously established research, let’s think about our question of “how” for a moment. What level of detail are we looking for? Do we want to know about the hair shedding of dogs at the molecular level, the population level, or something in between? Once we decide, we should clarify our question accordingly to ensure that we conduct the proper experiment or look for the proper information.
When we clarify our scientific question, we need to phrase it in a way such that the information we are asking for is specific. A good way of doing this is simply rephrasing the question to ask for detailed information. Instead of asking, “how does the dog know when to shed”, ask, “what is the mechanism that causes dogs to shed at some times and not others.”
Asking for the mechanism means that you are asking for a detailed factual account. Indicating that you are interested in the aspect of the mechanism that makes dogs shed at some times but not other times clarifies the exact aspect of the mechanism of shedding that you are interested in. Asking “what is” can be the more precise way of asking “how.”
The question of the mechanism of shedding timing would be resolved even further into even more specific questions of sub-mechanisms if we were in the laboratory. Typically, scientific questions beget more scientific questions as details are uncovered by experiments which attempt to answer the original question.
As it turns out, we know from previous research that dog shedding periods are regulated by day length, which influences melatonin levels, which influences the hair growth cycle. Keen observers will note that there are many unstated scientific questions which filled in the details where I simplified using the word “influences”.
Now that you have an example of how to work through a proper scientific question from hypothesis to request for details, try it out for yourself. Asking a chain of scientific questions and researching the answers is one of the best ways to develop a sense of wonder for the complexity of our universe!
I hope you enjoyed this article, I’ve wanted to get these thoughts onto paper for quite a long time, and I assume I’ll revisit various portions of this piece later on because of how critical it is. If you want more content like this, check out my Twitter @cryoshon and my Patreon!
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