It can be hard to match what we learned about the scientific method in school with the scientific literature being published. There are a variety of reasons for this, but generally it is an issue of what is practical (especially within the time frames that sources of funding expect results).
Because the classic description of the scientific method is a bit idealized, I’ll attempt to summarize the process in a way closer to reality:
- Identify opportunities to expand knowledge. A scientist puts together an idea based on what is already known and creative ideas on how to make improvements (observation and maybe hypothesizing). The new research could help fill gaps in knowledge or attempt to improve methods. These new questions are often guided by the problems that society needs to solve.
- Design a systematic means to collect and analyze data that will accomplish defined goals. The scientist designs a research plan that will expand knowledge, but because modern science is often chipping away at complicated issues, there may not be a formal hypothesis tested.
If a hypothesis is not tested, is the research still scientific? Yes. Maybe we should call this activity scientific exploration in contrast to scientific experimentation, but both activities are needed to expand the body of scientific knowledge. The key is how the data is collected and analyzed. In both cases, reliable (precise) measurements must be taken.
- Do the research (experiment and assess data). In real life, things rarely go as planned. To keep the research scientific, one needs to keep track of the surprises that come up and any adaptations that were done to the work in response to them.
- Document. This is a critical and sometimes tricky step. Nobody has time to read a detailed log on everything that happened throughout the research project. The work has to be synthesized, but in a way that is transparent enough for others to evaluate and potentially build on the work.
In the practical world of doing scientific work, it is often necessary to find projects that make incremental progress towards a bigger scientific question. Therefore, useful projects could be primarily about the collection of data or simply the improvement of a method. In this context, a critical challenge to scientific work is making valid comparisons between studies. This need for comparisons makes the use of standardized measurements and analysis methods very important.
Although, the scientific method may not be clearly visible in modern research studies, the logic principles behind it are still essential to scientific research. The causes of phenomenon (whether it be a bug in a software program or the distribution of soil properties around the world) are determined by a systematic process to eliminate alternative causes. Only when all of the alternative possibilities are eliminated can conclusions be drawn. When single studies cannot complete this task alone, they advance science more cautiously by only proposing what the results suggest and being careful to not extend conclusions beyond what is supported by available data.