Research and Critical Thinking
Length: 1132 words (3.2 double-spaced pages)
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Research and critical thinking is such a crucial entity in the world of every single science and our every day lives. While a biologist is testing the effects of carbon monoxide on the environment, a little girl is pointing in the sky counting how many colors there are in a rainbow. Both of these scenarios involve research and critical thinking but are extremely different. There are no guidelines for the little girl but there are many that the biologist has to follow. The same goes for psychological research.
Psychological research is almost exactly the same as scientific research. First you must make a hypothesis, experiment, collect data, and based off of the data you make conclusions as to whether or not your hypothesis was confirmed. The difference between psychological research and some other sciences is in what’s considered data and how that data is gathered and processed. Because psychology deals greatly with the mind and sometimes focuses on things that are not measurable, research has been restricted to things that are observable and therefore can be traced. To do research that successfully gives birth to credible data there are certain elements that must be followed as closely as possible. First your hypothesis must be researched and generalized. Secondly, before starting an experiment one must have a dependent variable, a control variable, and an independent variable. Third the data must be collected and translated properly.
In the case of the researcher who studied college students he has completely abused all the elements of research. He has done almost everything wrong in his research, therefore making his research highly un-credible and almost bogus. Starting with the first step in the scientific method, which is forming a hypothesis, I have reason to believe that after reading this researchers hypothesis he hasn’t a clue how to properly conduct it. Comparing the four year college students to the two year college students is not the problem; it is the structure of the hypothesis. Instead of saying students at a four year colleges are more intelligent than students at two year colleges, the hypothesis should be if students who attend four year colleges and students who attend two year colleges take the same IQ test, than the students who attend the four year college will score higher than the students who attend the two year college. It is much more descriptive without being to constricting.
At the beginning of the hypothesis it is better to be more descriptive than in the end. For instance if the hypothesis were to state that the four year students would score six points higher than the two year students. However both groups scored eight points higher. Even though they scored higher it would still disprove the entire hypothesis.
The next step is the experiment. The way the researcher went about experimenting makes him an even bigger idiot. This is the area that was the most incorrect. First the researcher only tested ten students from each college. With the difference in gender, race, age, education levels, and so many other factors there should be a much larger sample representing each whole. Also he chose the ten people from each college differently. In the four year college he used the first ten volunteers. At the second college he grabbed ten students he found sitting in a T.V. lounge following their last class on a Friday. For one thing if he just found these students how did he know they were students? Just because he found them in a T.V. lounge does not prove that they are. If he randomly just found these ten students how did he know they had returned from their last class that day. I believe he didn’t so therefore it wasn’t random. Another problem with his selection of test subjects is that what if the first ten students who volunteered at the four year college were all female above the age of 25 with a 4.0 grading average while the ten he chose off the couch at the two year college were all males under the age of 25 with a 2.0 grading average? It would make the entire experiment unfair and the data almost fixed. When performing an experiment you must try to get as close as possible to having only one differing variable, that would be the dependent variable. This researcher has so many different variables I don’t think he’s doing the same experiment. In order to do this experiment correctly the choosing of the test subjects should have been done with much more precision. To even out the issue of race, gender, and age the number of people being tested should have been a much bigger group with diversity. It should have also included a spread of race and age, and as equal a ratio of males to females as possible. Background checks should have been done on all the test subjects to see their completed education levels. All the participants should have had as similar G.P.A as possible. I would even go as far as to make sure that all the participants had completed a high school diploma without a G.E.D. Lastly, I do not see the point in having them fill out an essay on philosophy, from what I understand this is a general knowledge test and not a test on philosophy. If the researcher adds the philosophy essay then he should’ve gone through trouble of checking how many students had ever taken a philosophy course. More importantly philosophy and ABC’s are not the same type of intelligence. You can use a computer to score an IQ test while you would have to rely on the mind of a human to judge a philosophy essay. Unless there were factual questions like “When was Socrates born?” I don’t see how handing out a philosophy essay does the experiment any good.
Finally, the way the researcher used his data in my opinion was not professional. He should have used a correlation instead. I say this because even if the experiment was perfect there is still much that is unknown that could have influenced the results, even something as minor as a head cold. The results should have been presented in a graph of sorts representing either a positive correlation, negative correlation, or no correlation at all.
In conclusion when it comes to the seriousness of scientific research much is to be done and followed in order for your data to be as close to the truth as possible. To avoid looking like a complete idiot as the researcher did. Also to make sure the hypothesis is professional and researchable; the experiment is done with the utmost precision and care, and last of all that almost nothing is definite and can always be disproved.