1. Critical Thinking part 2
Dialogue Education
Update 4
Next Slide: Kahoot
Critical Thinking part 2
THIS CD HAS BEEN PRODUCED FOR TEACHERS TO USE IN THE CLASSROOM. IT IS A CONDITION OF THE USE OF THIS CD THAT IT BE USED ONLY BY THE PEOPLE FROM SCHOOLS THAT HAVE PURCHASED THE CD ROM FROM DIALOGUE EDUCATION. (THIS DOES NOT PROHIBIT ITS USE ON A SCHOOL’S INTRANET)

2. Kahoot- Critical Thinking
Next Slide: Contents

3. Contents Page 4 - Video Presentation Monty Python’s Argument Sketch
Page 5 - What is Reasoning?
Page 6 - Deductive reasoning
Page 7 to 8 - Inductive reasoning
Page 10 to Deductive versus Inductive reasoning
Page 19 - Community of Inquiry - Problems with inductive reasoning.
Page 21 - Bibliography
Next Slide: YOUTUBE Video Monty Python’s Argument sketch

4. YOUTUBE Video Monty Python’s Argument sketch
Click on the image to the left. You will need to be connected to the internet to view this presentation.
Enlarge to full screen
Next Slide: Reasoning is the cognitive process of looking for ....

5. Reasoning
Reasoning is the cognitive process of looking for reasons for beliefs, conclusions, actions or feelings.
Reasoning is the cognitive process of looking for reasons for beliefs, conclusions, actions or feelings. Humans have the ability to engage in reasoning about their own reasoning using introspection. Different forms of such reflection on reasoning occur in different fields. Although reasoning was once thought to be a uniquely human capability, other animals also engage in reasoning.
Next Slide: In philosophy, the study of reasoning typically

6. Reasoning
In philosophy, the study of reasoning typically focuses on what makes reasoning efficient or inefficient, appropriate or inappropriate, good or bad.
In philosophy, the study of reasoning typically focuses on what makes reasoning efficient or inefficient, appropriate or inappropriate, good or bad. Philosophers do this by either examining the form or structure of the reasoning within arguments, or by considering the broader methods used to reach particular goals of reasoning. Psychologists and cognitive scientists, in contrast, tend to study how people reason, which cognitive and neural processes are engaged, how cultural factors affect the inferences people draw.
Next Slide: Deductive reasoning Deductive arguments are intended to have reasoning that is valid.

7. Reasoning Deductive reasoning
Deductive arguments are intended to have reasoning that is valid. One classic example of deductive reasoning is that found in the following:
Premise 1: All humans are mortal.
Premise 2: Socrates is a human.
Conclusion: Socrates is mortal.
The reasoning in this argument is valid, because there is no way in which the premises, 1 and 2, could be true and the conclusion, 3, be false.
Deductive reasoning
Deductive arguments are intended to have reasoning that is valid. Reasoning in an argument is valid if the argument's conclusion must be true when the premises (the reasons given to support that conclusion) are true. One classic example of deductive reasoning is that found in the following:
Premise 1: All humans are mortal.
Premise 2: Socrates is a human.
Conclusion: Socrates is mortal.
The reasoning in this argument is valid, because there is no way in which the premises, 1 and 2, could be true and the conclusion, 3, be false.
Next Slide: Inductive Reasoning Inductive reasoning contrasts strongly with deductive reasoning.

8. Reasoning Inductive Reasoning
Inductive reasoning contrasts strongly with deductive reasoning. Even in the best, or strongest, cases of inductive reasoning, the truth of the premises does not guarantee the truth of the conclusion. Instead, the conclusion of an inductive argument follows with some degree of probability.
Next Slide: A classical example of inductive reasoning comes from the empiricist David Hume:

9. Reasoning
A classical example of inductive reasoning comes from the empiricist David Hume:
Premise: The sun has risen in the east every morning up until now.
Conclusion: The sun will also rise in the east tomorrow.
Relatedly, the conclusion of an inductive argument contains more information than is already contained in the premises. Thus, this method of reasoning is ampliative.
Next Slide: Deductive vs. INDUCTIVE “nondeductive” arguments

10. Deductive vs. INDUCTIVE “nondeductive” arguments
A deductive argument is one that contains a deductive inferential claim.
A Inductive (nondeductive) argument is one that contains a nondeductive inferential claim.
Next Slide: Deductive vs. Inductive (nondeductive) inferential claims

11. Deductive vs. Inductive (nondeductive) inferential claims
A deductive inferential claim is the claim, made by the arguer, that the truth of the conclusion follows with the force of absolute logical necessity from the assumed truth of the premises.
An Inductive (nondeductive) inferential claim
Next Slide: is the claim, made by the arguer, that the truth

12. . . . is the claim, made by the arguer, that the truth of the conclusion follows with some significant degree of probability from the assumed truth of the premises.
Next Slide: Deductive inferential claims are either “valid” or “invalid.”

13. Deductive inferential claims are either “valid” or “invalid.”
Inductive inferential claims are either “strong” or “weak.”
Next Slide: A deductive inferential claim (or argument) is valid

14. A deductive inferential claim (or argument) is valid
when the truth of its conclusion follows necessarily from the assumed truth of its premises.
Next Slide: A deductive inferential claim (or argument) is invalid
1. If Polly is a cat, then Polly is an animal.
2. Polly is a cat.
3. Polly is an animal.
is valid.

15. A deductive inferential claim (or argument) is invalid
when the truth of its conclusion DOES NOT follow necessarily from the assumed truth of its premises.
Next Slide: An Inductive (nondeductive) inferential claim (or argument) is strong…
1. If Polly is a cat, then Polly is an animal.
2. Polly is an animal.
3. Polly is a cat.
is invalid.

16. An Inductive (nondeductive) inferential claim (or argument) is strong
when the truth of its conclusion follows with some significant degree of probability from the assumed truth of its premises.
Next Slide: Millions of crows have been observed…..

17. is strong. 1. Millions of crows have been observed.
2. All of them have been black.
3. All crows are black (probably).
Next Slide: Community of Inquiry Discussion
is strong.

18. An Inductive (nondeductive) inferential claim (or argument) is weak
when the truth of its conclusion DOES NOT follow with any significant degree of probability from the assumed truth of its premises.
Next Slide: Community of Inquiry Discussion

19. 1. The great majority of college professors are politically liberal.
2. Patricia Quinn is a college
professor.
3. Patricia Quinn is (probably)
politically liberal.
Next Slide: Community of Inquiry Discussion
is weak.

20. Community of Inquiry Discussion
CLICK ON THIS LINK FOR THE STIMULUS FOR A DISCUSSION ON INDUCTION. (You might like to print this material out and distribute it to the class.)
Next Slide: Bibliography

21. Bibliography
Copeland, Jack Artificial Intelligence:a philosophical introduction. Oxford: Blackwell.
Furley, David 'Rationality among the Greeks and Romans'. In The Gale Group, Dictionary of the history of ideas. University of Virginia Library.
Jeffrey, Richard Formal logic: its scope and limits, (3rd ed.). New York: McGraw-Hill.
Kirwin, Christopher 'Reasoning'. In Ted Honderich (ed.), The Oxford Companion to Philosophy. Oxford: Oxford University Press.
Manktelow, K.I Reasoning and Thinking (Cognitive Psychology: Modular Course.). Hove, Sussex:Psychology Press
McCarty, L. Thorne 'Reflections on TAXMAN: An Experiment on Artificial Intelligence and Legal Reasoning'. Harvard Law Review. Vol. 90, No. 5.
Scriven, Michael Reasoning. New York: McGraw-Hill. ISBN