Basics of Scientific Research. Константин Алтунин

always that everything is the result of a change, and get used to thinking that there is nothing Nature loves so well as to change existing forms and to make new ones like them."

      – Meditations. iv. 36. – Marcus Aurelius

      Observation in philosophical terms is a process of filtering sensory information through the thought process. Input is received via hearing, sight, smell, taste or touch and then analyzed through either rational or irrational thought. You can see a parent beat his child; you observe that such an action is either good or bad.

      Deductions about what behaviors are good or bad may be based in no way on preferences about building relationships, or study of the consequences resulting from the observed behavior. With the passage of time, impressions stored in the consciousness about many related observations, together with the resulting relationships and consequences, permit the individual to build a construct about the moral implications of behavior.

      Experiment

      Experiment is an orderly procedure carried out with the goal of verifying, refuting or establishing the validity of a hypothesis. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in their goal and scale, but always rely on repeatable procedure and logical analysis of the results. There are also existing natural experimental studies.

      A child may carry out basic experiments to understand gravity, while teams of scientists may take years of systematic research to advance the understanding of a phenomenon. Experiments and other types of hands-on activities are very important to student learning in a science classroom. Experiments can raise test scores and help a student become more engaged and interested in the material they are learning, especially when used over time. Experiments can vary from personal and informal natural comparisons (e.g. tasting a range of chocolates to find a favorite one), to highly controlled (e.g. tests requiring complex apparatus overseen by many scientists that hope to discover information about subatomic particles). Uses of experiments vary considerably between the natural and human sciences.

      Experiments typically include control, which are designed to minimize the effects of variables other than the single independent variable. This increases the reliability of the results, often through a comparison between control measurements and other ones.

      Scientific controls are a part of the scientific method. Ideally, all variables in an experiment will be controlled (accounted for by the control measurements) and none will be uncontrolled. In such an experiment, if all the controls work as expected, it is possible to conclude that the experiment is working as intended and that the results of the experiment are due to the effect of the variable being tested.

      Designs of Experiment

      The types of Experimental Designs usually include a Completely Randomized Design, a Randomized Block Design and a Matched Pairs Design [6].

      In a Completely Randomized Design each experimental unit is randomly assigned to a random group to receive a different treatment, each unit in the same group receives the same treatment, and at the end of experiment you will compare the results from each treatment (Fig. 2, Fig. 3). Let’s show up how a Completely Randomized Design would be used in the following example:

      A researcher wants to conduct an experiment to determine which environment is best suited for studying – a library, in one’s own room or outside. A total of 30 university students volunteer to participate in the experiment. So we have three treatments such as the library, in one’s own room or outside. Since we have three treatments we will have three groups receiving the treatments, and since there are 30 university students, these 30 subjects will be randomly assigned to the three groups to receive the treatments.

      

      Fig. 2. Completely Randomized Design

      And at the end of the experiment we will compare results from each treatment.

      

      Fig. 3. Completely Randomized Design

      Let’s see that a researcher believes that gender has an effect on the results. In a case like this we would use a Randomized Block Design that doesn’t immediately randomly assign the experiment units to receive treatments, we, first, assign people into a block based on the characteristic that’s expected to influence the response to its treatments. And this example where gender would be a blocking variable, so first we separate the experimental units based on gender, one block will be for females and one block will be for males. There are 18 females and 12 males (Fig. 4).