PHIL10160 Critical Thinking

Academic Year 2024/2025

In his 2005 book *On Bullshit*, the philosopher Harry Frankfurt (1929-2023) writes that:

"One of the most salient features of our culture is that there is so much bullshit. Everyone knows this. Each of us contributes their share. But we tend to take the situation for granted.”

Frankfurt defines 'bullshit' as content that is presented without any regard for the truth, but for some other reason (for example, to persuade or gain attention). Given that definition, Frankfurt's comment applies to our world today even more than it did in 2005. In fact, with the rise of generative AI, we are entering into an era in which the total quantity of bullshit in our environment is likely to increase exponentially. So, it's more important than ever to be able to distinguish the true from the false, the rational from the irrational, and the logical from the illogical.

Both people and AI systems like ChatGPT can produce content, sometimes true, sometimes false (often neither). But producing content is not the same as *reasoning*. Reasoning involves being sensitive to the evidential and logical relations between different claims. And AI systems can't reason: they are not designed to be sensitive to evidential and logical relations. Even if they get things right a lot of the time -- even if they got things right *all* of the time -- it is not because they are *rational*. Unless we want to allow our ability to reason independently -- and therefore, we might think, our human autonomy -- to wither and die, it's more important than ever for each of us to be able to reason well. The future will need people who can think for themselves.

But reasoning is not easy, and reasoning *well* is harder still. The aim of this course is to help you to learn to reason better, and therefore to make better decisions, by learning three main things:

1. Why our natural psychological biases make it hard for us to reason well, and what we can do to mitigate those biases;

2. What reasoning well actually consists in, in other words, what it means to be sensitive to the evidential and logical relations between claims; and

3. How to extract and analyse arguments from what people (or AIs) write or say, in order to assess whether we should accept their conclusions and recommendations.

To be a little more specific, in the module we'll learn about *cognitive biases* and how to mitigate them; what an *argument* is; what makes an argument (logically) good or bad; what makes a claim *evidence* for another claim; how we might fail in our search for evidence; and how to extract an argument from a piece of text, in order to assess whether we should accept it; what the difference is between *opinion* and *knowledge*, and between *lies* and *bullshit*; what the typical forms of *bad argument* are; and finally, about *paradoxes* (such as that generated by the statement ‘This sentence is not true’), which seem to threaten our most basic assumptions about good reasoning.

The module is taught by me, Dr. Daniel Esmonde Deasy (Associate Professor, UCD School of Philosophy), and is delivered in the form of two 50-minute in-person lectures per week of term and seven 50-minute in-person tutorials with a graduate tutor. Lectures will consist primarily in the presentation of material by the lecturer in lectures and via the course-page on Brightspace, and tutorials will involve active discussion of the material and non-graded quizzes. The module is not difficult, but it should reward those who engage with it with valuable skills they can apply throughout their lives.

I welcome students of all kinds to join this module: not just philosophy students, but also students from any other discipline in the university, students at any stage of their UG degree, exchange, Erasmus and study abroad students, students for whom English is not a first language, mature students, Open Learning students, and so on. Critical thinking is for everyone, and the more diverse the cohort the better.

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Curricular information is subject to change

Learning Outcomes:

The main learning outcomes for this module are as follows:

1. Being able to understand and apply key concepts in critical thinking such as 'reason'; 'cognitive bias'; 'argument'; 'inference'; 'premise'; 'conclusion'; 'evidence'; 'inferential strength'; 'valid argument'; 'sound argument'; 'fallacy'; and 'paradox'.
2. Being able to distinguish different types of cognitive biases and apply strategies to mitigate them.
3. Being able to understand what makes an argument inferentially strong (i.e. logically good) or inferentially weak (logically bad).
4. Being able to produce your own examples of inferentially strong and inferentially weak arguments.
5. Being able to extract, analyse, and assess short arguments presented in text.
6. Being able to distinguish different kinds of fallacies (i.e. common forms of bad argument).
7. Being able to distinguish lies, bullshit, and rhetoric.

Indicative Module Content:

The key topics in this course are:

1. Reasoning (good and bad).
2. Cognitive Biases (common patterns of thought that lead to bad reasoning).
3. Fallacies (commonly accepted patterns of bad reasoning).
4. Arguments (what they are; how they are structured).
5. Evidence (what it is; how it works; what makes it strong or weak).
6. Logical validity (a quality of arguments whose conclusions must be true if their premises are true).
7. Inductive strength (a quality of arguments whose conclusions are likely to be true given the truth of their premises).
8. Rhetoric (the art of persuasion).
9. Lies and Bullshit.
10. Paradoxes (arguments that seem to lead to contradictions).

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Tutorial

7

Autonomous Student Learning

94

Total

125

Approaches to Teaching and Learning:
1. TEACHING

Teaching for this module is centred around lectures and tutorials, both of which are essential for learning in this module.

Lectures are scheduled twice a week during term, and last for around 50 minutes. In the lectures, I'll present the week's learning using a nice slideshow presentation. But the slides will be fairly minimalistic, and won't contain too much information: mostly key definitions and key examples. In other words, I'll say much more in the lectures than is on the slides, and it won't be easy to learn the material directly from the slides. (For example, I'll give examples and make clarifications that don't appear on the slides.) There will be lecture notes as well, which go into more detail than the slides, but again, they won't be as useful for learning as actually attending the lectures. For example, in the lectures I'll also take questions from the floor, and ask questions, and use in-class polls and MCQs using UCD's polling app *Poll Everywhere*. It's impossible to capture this sort of dynamic back-and-forth in any other setting, and that's why it's really important to attend as many of the lectures as possible.

Tutorials are small-group seminars led by a graduate student who is an expert in the subject matter. The purpose of tutorials is two-fold: first, to give you a chance to ask questions about and discuss material presented in the lectures and readings in a smaller setting; and second, to develop some of the reasoning skills we are learning about in the lectures by completing non-graded exercises in small groups. Tutorials last for around 50 minutes and take place once a week for seven weeks during term. In the tutorials, the tutor will first present some of the key concepts and examples from the week's learning, and provide you with an opportunity to ask clarificatory questions. Then, they'll divide the whole group into smaller groups and ask them to collaborate on informal (i.e. non-graded) exercises related to the content of the module. For example, groups might be asked to identify the conclusions in short passages containing arguments, or identify which statements provide reasons for another statement. The tutor will provide feedback in the tutorial on each group's work as the tutorial progresses. Since tutorials provide an opportunity to actually practice your skills in reasoning and argument analysis, they are also an essential part of the learning for this module.

2. LEARNING

Learning for this module is centred around the following:

a. The content presented in lectures;
b. The lecture notes;
c. The other required readings shared by the lecturer on the course page;
d. Discussion and debate in the tutorials;
e. The non-graded tutorial exercises;
f. The graded online assessments (see below); and
g. Online and in-person feedback on the graded and non-graded assignments.

In terms of learning, you will be expected to (i) read the assigned readings in advance of the lectures (shared on the course page as PDFs); (ii) attend all of the lectures; (iii) attend and actively participate in the tutorials; and (iv) complete all of the online assessments.

In addition to the obvious things like delivering lectures, organising tutorials, and populating the course-page with readings and slides, I will support your learning by:

a. Making a video for each short quiz at the end of each quiz week, explaining why the answers were what they were;
b. Sharing a practice exam with a separate answer sheet, so you can practice exam-style questions;
c. Answering questions via email, in person after lectures, and in office hours;
d. Providing feedback and guidance on assessments in lectures and via emails. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Exam (In-person): A 1-hour in-person MCQ exam in the UCD Exam Period. n/a Other No

60

Quizzes/Short Exercises: Six short online MCQs during term. n/a Other No

30

Participation in Learning Activities: Participation in tutorial exercises. n/a Pass/Fail Grade Scale No

10


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Group/class feedback, post-assessment
• Online automated feedback
• Self-assessment activities

How will my Feedback be Delivered?

1. The short online MCQs will generate automated feedback at the end of the 24-hour assessment period. 2. There will be weekly group feedback videos on the short online MCQs. 3. You will receive individual and group feedback in tutorials on informal assignments and exercises. 4. There will be a set of practice MCQs with an answer sheet that you can use to test yourself and check your results.

• Bowell, T. & G. Kemp (2015) Critical Thinking: A Concise Guide (4th Edition). Routledge.
• Galef, J. (2021). The Scout Mindset: See Things Clearly and Make Smart Decisions. Portfolio Penguin.