Communication system designers minimize noise with self-correcting codes that add redundant information to the signal, increasing the probability of error detection, and recovery of the uncorrupted data. Evolutionary biologists claim that knowledge transmitted between generations of biological organisms have mechanisms that create probability traps for errors. Designers of online systems are starting to mimic these systems.
Devices like cell-phones and modems express information as sequences of codes such that noise generated errors can be detected and corrected. For instance, Modems detect errors by checksum, which is the sum of the digits in a given message modulo some number. If the received message produces a checksum different from the produced by the transmitted one, the system recognizes that it is dealing with erroneous data. A simple method of performing a checksum is to add a parity bit to a 7 bit code, such that the total number of 1s is even; if the receiver gets a message with a byte that does not meet this requirement, an error is present. There are more sophisticated methods of performing the checksum, but the example given here is adequate enough to show that error detection and correction is not only possible, but widely used.
In a learning environment, error detection is quite common in the teacher-student relationship. Ancient Greeks invented a clever method of error detection called dialectics. Plato’s dialogs (Plato, 1925) show how it works. One of the most common dialectic tricks is the reduction ad absurdum, where the student tries to derive an absurd outcome from what he has learned. In case of success, the knowledge is flagged as corrupted. Another common error detecting method among the Ancient Greeks was to check knowledge against known facts.
Once fully developed, Logics also provided a method to scrutinize information for errors; Aristotle and other philosophers classified and analyzed fallacies, in order to filter out wrong arguments. An introductory text on fallacies is (Tindale, 2007). A fallacy is an argument that is demonstrably flawed in its form, which renders it invalid as a whole. Modern logicians classify fallacies as material, verbal, and logical. In his Sophistic Refutations (Aristotle, 1987) Aristotle lists the following types of material fallacies, among others:
• Generalization that disregards exceptions. E. g. Telling lies is a mean act; the mother that tells her child that is suffering from leukemia that he/she will get better is telling a lie; therefore she is mean.
• Argumentum ad hominem: Instead of examining the contents of the information, one worries about the ideology, or moral standing of the author. E.g. Herrnstein and Murray argue that the cognitive elite is becoming separated from those with average intelligence. But it must be false, since these political scientists are the authors of The Bell Curve (Herrnstein & Murray, 1996), a racist book. Some times, the argumentum ad hominem refers to the moral standing of people that have little or nothing to do with the authors of the refuted argument. I have seen arguments against vegetarianism based on the fact that Hitler was a vegetarian.
• Petitio Principii or circular argument: Demonstrates a conclusion by means of premises that assume that conclusion.
• Non Sequitur: Incorrectly assumes one thing is the cause of another.
• Post hoc ergo propter hoc: Believing that temporal succession implies a causal relationship.
There are two important facts about fallacies. The first one is that most people who commit fallacies are unaware that their argument is faulty (Cohen, 1982), but since the patterns of many common fallacies are easily perceived, the student can use them to detect flaws on distance education lessons. The second fact about fallacies is that they often hinder knowledge transmission; the student may not understand a correct fact because the lesson has a fallacious pattern; a fallacious pattern which one often finds in tutorials is the circular argument (Circulus in Probando).
Verbal fallacies are the most common mistakes in lessons and tutorials, and they are easily detected by a trained student. Below the reader will find a listing of some verbal fallacies.
Key Terms in this Chapter
Formal System: A language plus a set of transformation rules, which one can use to model external phenomena.
Error Detection: Ability to detect the presence of errors caused by noise or other shortcomings.
Feedback: Process of sharing concerns with the intention of improving performance.
Modulo: Mathematical operation that finds the remainder of an integer division.
Message: Object of communication; the word stands for both the information and its form.
Error Correction: Ability to construct error-free information or instruction.
Instruction: Information that contains commands and explanations on how to behave or to complete a task.
Error: Difference between actual behavior or measurement and expectations.
Information: Data that one gathers, processes, and transmits in order to add knowledge to a receiver.