Philosophy of Science: Understanding Scientific Reasoning
|School||School of Computing and Academic Studies|
|Minimum Passing Grade||50%|
|Start Date||September 07, 2021|
|End Date||December 17, 2021|
|Pre-requisites||BCIT ENGL 1177, or 6 credits BCIT Communication at 1100-level or above, or 3 credits of a university/college first-year social science or humanities course.|
Acknowledgement of Territories
The British Columbia Institute of Technology acknowledges that our campuses are located on the unceded traditional territories of the Coast Salish Nations of Sḵwx̱wú7mesh (Squamish), səl̓ilwətaɁɬ (Tsleil-Waututh), and xwməθkwəy̓əm (Musqueam).
|Instructor to provide|
|Office Hours||Instructor to provide|
Develops simple, yet powerful methods for understanding and evaluating a wide variety of scientific and pseudo scientific material. Introduces some of the great thinkers and theories of the past, both winners and losers. Reflects on what makes scientific reasoning so effective, and uses these reflections to evaluate some contemporary criticisms of the place of science in society.
Course Learning Outcomes/Competencies
Upon successful completion, the student will be able to:
- Distinguish theoretical models from real-world objects of study.
- Abstract brief descriptions of theoretical models from popular or semi-technical science reports.
- Recognize the empirical predictions of such models.
- Note whether these predictions are actually fulfilled in observation or experiment (negative or positive evidence).
- Judge whether there are other plausible models that can (also) explain the facts.
- Judge whether to accept, reject or suspend judgement on whether the proposed model accurately represents the world.
- Judge whether the proposed model is credible, but needs further development or testing; or judge that the proposed model is implausible, and (currently, at least) not worth pursuing.
- See how historically eminent scientific models triumphed over then-plausible contemporary views.
- The students will have read through James Watson's classic, The Double Helix, as well as the brief historical episodes discussed in the texts.
- The students will also have been provided with further details regarding the historical episodes discussed in the text. Such nuances can help reveal how and when theory evaluations are tied to theoretical traditions.
- See that 'marginal science' models are generally not worth accepting or pursuing because (i) they make vague or multiple predictions; (ii) their predictive 'successes' are also explained by more plausible models; or (iii) they are deeply inconsistent with well-established theories.
- Recognize and intelligently engage with some alternative philosophies of science.
- Distinguish sample and statistical models from the larger population they are designed to represent.
- Understand statistical proportions, distributions, correlations and variables.
- Understand basic mathematical probability models (addition, multiplication rules, conditional probabilities, the structure of random sampling, and standard deviation).
- Quickly compute margins of error from sample sizes.
- Recognize the connection between margin of error and confidence level.
- Construct simple statistical models of reported proportions, distributions and correlations.
- Recognize and evaluate samples according to how well they approximate random sampling.
- Distinguish statistical significance from 'significance.'
- Judge whether a proposed statistical model should be accepted, rejected or treated as unsupported.
- Distinguish causation from correlation.
- Distinguish deterministic from probabilistic models of causation.
- Distinguish causal models for individuals from those for populations.
- Understand causal 'effectiveness.'
- Understand the role of control and experimental groups in establishing causal hypotheses.
- Understand the theoretical superiority of Randomized Experimental Designs for supporting causal hypotheses.
- See when Prospective and Retrospective causal models are required, and when they can support a causal hypothesis.
- Understand controlling for other variables, matching control and experimental groups, and constructing control groups (in Retrospective studies).
- (If time permits.) Understand the elements of decision-making models (options, states of the world, outcomes and values).
- Distinguish ranked from measured values.
- Recognize when a situation calls for decision making with certainty, uncertainty, or risk.
- Grasp better, worse and satisfactory options and correlated strategies.
- Combine probabilities and values, in terms of expected values in situations involving known risks.
Philosophy of Science: A Very Short Introduction, 2nd ed. by Samir Okasha (available as an ebook or as a printbook)
All other readings/videos/websites will be provided.
By the end of this course you will be able to:
Perform conceptual analysis;
Express your view in the form of a philosophical argument;
Define science from a philosophical point of view;
Describe some classical problems in philosophy of science;
Identify new approaches that are being taken by philosophers to address these problems;
Describe how developments in neuroscience and recognition of the importance of neuroplasticity support a shift in our understanding of science;
Describe how individual and social values influence science;
Explain how science has been misused to support the concept of race.
Weekly Quiz (25%)
Each week there will be a 10-question T/F quiz based on the assigned material for the week to test your recollection of key ideas in the material. After module 1, the quiz will also include two questions from previous quizzes. Each quiz will be worth a maximum of 10 marks and your best ten quiz grades will count towards your final grade. The quiz will close at midnight on Sunday each week.
Weekly discussion (25%)
Each week, starting in week 2, I will post an open-ended discussion question on the topic of the week that invites a response from you. You may either respond to my question or to the response of another student. Your response should be at least 300 words. Each response will be worth a maximum of 10 marks. Your best ten responses will count towards your final grade. The discussion will close at midnight on Tuesday in the week after the discussion started.
Self reflection (15%)
At the end of weeks 5, 10 and 14 you are expected to submit a passage of self reflection of at least 300 words. If you are not familiar with self reflection as a learning activity, the UK Open University has a short module on it here.
Final Exam (35%)
The final exam will be held on Thursday December 16. It will consist of two equally rated sections; one will be a set of 25 questions randomly selected from the weekly quizzes and the other will require you to write at least 500 words on a course-related topic, which you will be given in advance of the exam.
Safety equipment or protective clothing
Course Schedule and Assignments
Topics and readings
Week 1 2021-09-06
Week 2 2021-09-11`
1. Self assessment
Week 3 2021-09-18
Week 4 2021-09-25
1. What is science? An overview
Week 5 2021-10-02
1. Models in science
Week 6 2021-10-09
Week 7 2021-10-16
Week 8 2021-10-23
Week 9 2021-10-30
Week 10 2021-11-06
Week 11 2021-11-13
1. The evolved brain
Week 12 2021-11-20
1. Change in science
Week 13 2021-11-24
1. Values in science
Week 14 2021-12-04
1. Challenges to science
Week 15 2021-12-13
Final Exam 2021-12-16
The topics studied in the course are given in the section Course Schedule and Assignments. The first three weeks are introductory and are intended to give you the basic philosophical tools required to think and talk about current and historical ideas (mainly current) of what science is and how it is done in a philosophical way. A consistent theme throughout the course is Realism, which is the view that the world is exactly the way we perceive it to be, and each week it is challenged.
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Guidelines for School of Computing and Academic Studies
Students must successfully complete a course within a maximum of three (3) attempts at the course. Students with two attempts in a single course will be allowed to repeat the course only upon special written permission from the Associate Dean. Students who have not successfully completed a course within three attempts will not be eligible to graduate from their respective program.
I verify that the content of this course outline is current.
Alan Belk, Instructor
August 30, 2021
I verify that this course outline has been reviewed.
Michael Bourke, Faculty
August 30, 2021
I verify that this course outline has been reviewed and complies with BCIT policy.
Patricia Sackville, Associate Dean
August 30, 2021
Note: Should changes be required to the content of this course outline, students will be given reasonable notice.