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THINKING CRITICALLY Throughout your college career textbooks have been your ultimate source of knowledge. In the real world textbooks are compilations of factual information presented to students in language that is easy to understand and generally written by learned scholars who have a mastery of the subject. But, textbook knowledge is never cutting edge knowledge. That is the realm of research. Research represents knowledge in the making, data that has not yet earned the distinction of being factual. Thus, in research you are in the world of hypothetical, theoretical, conceptual, conjectural, and sometimes just plain wishful thinking. This puts you on guard as to what to believe and not believe. This is where you need critical thinking. Critical thinking is deciding what is true or false based on the strength of evidence. It’s weighing one opinion against others and deciding which conclusions are correct or fall short. In many respects critical thinking has parallels to the legal profession where a jury must decide if the case against the defendant merits a guilty or non-guilty verdict. The prosecutor presents the case by stating, “we intend to prove that a crime has been committed. We further will prove beyond a reasonable doubt that the defendant was the perpetrator of the crime, that the defendant had a motive to commit the crime and is connected to the weapon that was used in committing the crime”. What follows is a series of testimonies constituting evidence from witnesses or professional experts that supports the prosecution’s theory of the crime. The case rises or falls on the strength of the evidence. Now, put the above scenario in a research situation. Researchers are obligated to communicate findings. When you write a research paper or speak before an audience you are presenting evidence that supports a theory. You begin by stating a hypothesis which basically serves to give, in your opinion, the best explanation of the theory under study. You never “prove” a hypothesis in research. Instead you present evidence that “supports” or “rejects” the hypothesis. That, of course, is a daunting task and could mean acceptance of your paper, or if you are speaking, a bewildering skepticism on the part of your audience. So, how does critical thinking enter into the game of research? First you must know the difference between strong and weak evidence. The two are often confused. Strong evidence is obtained when the design of the experiment features adequate controls, addresses alternative possibilities and eliminates research bias. Weak evidence represents conclusions drawn on the basis of a weak experimental design that rest on specific events observed without attention to contingencies. For example, suppose someone hypothesized that vitamin A acted as a transcription factor for genes that regulate retina development. To support the hypothesis, the investigator provides a table showing a rise in a retinal gene when the vitamin was added to retinal cells in a culture medium. Extending the hypothesis the investigator concludes that vitamin A caused a direct “induction” by binding to the gene that coded for retinal proteins. On the surface one could say that the investigator is correct. But, stop and think. What does a rise in the gene represent and does it mean a direct binding on the retinal gene promoter? Could the data be interpreted differently? What happens, for example, if the vitamin stimulated the synthesis of another factor which in turn acted on the promoter for the retinal gene? This event could also explain the observation and if such happened, then the effect was not direct. Suddenly that firm hypothesis is wilting down to “circumstantial” evidence for support. Circumstantial evidence is just what it says, weak evidence that depends basically on the way the experiment was performed. How does an investigator decipher truth from fiction? Essentially, how does one distinguish hard evidence from soft evidence? This is a major problem when one is dealing with the unknown. The wise scientist is a skeptic who only accepts facts when they are supported by logical deductions (or inductions) of the data. He/she is mindful of experimental design, the adequacy of controls, and the statistical evaluations used. The wise researcher rejects positive conclusions drawn from negative evidence and knows how to distinguish causative effects from associative effects, the former perhaps the strongest ploy to getting at the truth. These are illustrated in the following example. Suppose coins placed on a table flew into the air when the table was struck with your hand. In racing to judgment one may conclude that the coins are all related to one another because all acted in unison. This is assuming cause/effect based on similarity of behavior. The strong evidence is the blow to the table caused all the coins to move as one, i.e., cause-effect. The weak evidence is the movement of one coin initiated the movement of the others. Which is correct? You decide. Note that weak supporting evidence can lead one to conclude an associative relationship is cause/effect. When you try to “prove” a theory you tend to look for links that may not exist. If one wants to prove a theory, one need only design experiments whose outcome will rule in the theory’s favor. It is always good to maintain the mindset of a “doubting Thomas” lest you want a reputation as an investigator who does not critically appraise the data observed. Below are some terms that are used commonly in research. Your task will be to know the meaning of each term and be able to apply your understanding when you present your paper before the class. 1. In vitro, literally Latin for “in glass”. Studying biological phenomenon in a test tube or some such isolated environment. 2. In vivo, literally Latin for “in life”. Depicting the internal biological environment untouched or unaltered. 3. In situ, literally Latin for “at this site”. A way of describing a location in the system where events are occurring. 4. Ex vivo, literally Latin for “out of life”. A term rarely used but meant to represent a hybrid state between “in vitro” and “in vivo”. For example, studying biological phenomena in a cell culture emulates an intact biological environment but is carried out in Petri dishes or culture flasks. Another example is a perfusion of some organ that has been removed from its biological surroundings. 5. Deductive reasoning: Reaching a conclusion based on eliminating incorrect or weak evidence 6. Inductive reasoning: Reaching a conclusion based on infusing new understandings and alternative explanations. 7. Model system: An isolated system assembled to emulate the living system and used to study a cause-effect relationship. 8. Biomarker: An internal bio-component whose change in response to a factor reflects the action of that factor. Biomarkers are convenient tools that can be linked quantitatively to the phenomenon under study. For example, a biomarker of insulin action is a lowering of blood sugar; the greater the dose of insulin, the stronger the depression of blood sugar. 9. Bioavailability: In nutrition, a term used to denote the amount of a nutrient taken in the diet that contributes to a post or pre metabolic event. 10. Hypothesis: An explanation based on evidence representing the most recent and best understanding of the phenomena under study and subject to change. It can be argued that rejecting a hypothesis, particularly a strong hypothesis, is a means of getting closer to the truth. 11. Working hypothesis: A roadmap that guides research efforts, sets the direction, and prioritizes research experiments. 12. Inference: A logical deduction to reach a conclusion. In research to infer something is to avoid stating it as factual. 13. Significant: In research significant implies a statistical analysis would show a difference is caused by an apposing variable and not a random occurrence.