There are a lot of approaches, and some I agree with are mentioned in the comments. One additional thing that's important is trying to always assess the qualit

There are a lot of approaches, and some I agree with are mentioned in the comments. One additional thing that's important is trying to always assess the quality of the information you come across, as a first step. Even the smartest person can make bad judgements if they're relying on inaccurate information. Thus, anything like critical thinking about a topic has to start with some kind of test. One thing to look for (and this is a very math-centric way of looking at it) is to look for inconsistencies, i.e. if two pieces of information are claimed to be reliable but they appear mutually exclusive, then there is probably a problem with either one or both pieces. There's a web page listing many similar useful logical tests for the quality of information (and arguments) that's been around for a long time. Going through the list is a good exercise. http://www.nizkor.com/features/fallacies/ http://www.nizkor.com/features/fallacies/ Example: Description of Biased Sample This fallacy is committed when a person draws a conclusion about a population based on a sample that is biased or prejudiced in some manner. It has the following form: Sample S, which is biased, is taken from population P. Conclusion C is drawn about Population P based on S. The person committing the fallacy is misusing the following type of reasoning, which is known variously as Inductive Generalization, Generalization, and Statistical Generalization: X% of all observed A's are B's. Therefore X% of all A's are Bs. The fallacy is committed when the sample of A's is likely to be biased in some manner. A sample is biased or loaded when the method used to take the sample is likely to result in a sample that does not adequately represent the population from which it is drawn.