Download THINKING CRITICALLY

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.