Lectures
This course includes the following eleven lectures. They are all available as videos on Canvas to watch whenever you want. Their place in the schedule is a suggestion of when you might view it. The exception is the lecture “Algorithmic reasoning and its limitations” which is given as a campus lecture.
- Introduction and scientific knowledge (26 minutes)
- Scientific inferences (59 minutes)
- Observation and measurement (76 minutes)
- Experiments (49 minutes)
- Models (62 minutes)
- Statistics (62 minutes)
- Explanations and causes (81 minutes)
- Qualitative methods (93 minutes)
- Algorithmic reasoning and its limitations
- Research Ethics (103 minutes)
- Anticipating Risk in Science and Engineering (85 minutes)
From the second lecture onward, there is an associated quiz of 15 questions. If you complete the quiz with at least 14 points, you will get 0,5 bonus points for the exam. You can attempt to complete the quiz as many times as you like until it closes. This quiz closes at the end of the week where the lecture is scheduled (Sunday, 23:59, of each week). (The exception is “Algorithmic reasoning and its limitations”, which has its own deadline, see Canvas.) This is to incentivise studying throughout the course, rather than only at the end. Bonus points collected during this period are valid for the exam and the re-exam belonging to this period.
In addition to these, there are two “flipped classroom” sessions. In these sessions, the lecturer answers your questions. In this period, they are given only as discussion forum interaction on Canvas. You need to have asked the question before the dates specified for the flipped classroom on Canvas, but you do not need to be present on any lecture nor do you have to watch any video. You can read the answers in the discussion forum at any time after the session.
Seminars, 1,5 credits
The course includes a mandatory seminar series comprised of four seminars. Each seminar covers selected course contents from the video lectures and course readings, and following the first seminar, each subsequent seminar connects to the previous seminars.
Seminars are intended as a collaborative learning activity where you practice critically discussing course contents and practice applying course contents to cases, with instruction and support from teaching staff. The overall topics covered during the seminar series are as follows:
- Definitions, operationalizations and hypotheses (course week 3)
- Designing a scientific study (course week 4)
- Interpretation, analysis and evidence (course week 6)
- Risk and research ethics (course week 7).
Since completion of the seminar series yields course credits, the seminars feature mandatory activities: (1) preparing and passing a seminar quiz, and (2) actively participating on the seminar. Missing activities result in seminar incompletion and thus no seminar course credits.
Before each seminar, you read the assigned readings (reading instructions available on Canvas). Before attending each seminar, you must also pass a mandatory seminar preparation quiz (See section on Schedule and see Canvas for deadlines). There is no limit on number of quiz attempts up until the quiz deadline. You must complete the quiz with a passing score of 14 points before the deadline (indicated in Canvas as “Passed”).
The preparation quizzes are intended to ensure that all participants come prepared to the seminar for a more rewarding seminar learning experience. If you attend the seminar without completing the preparation quiz beforehand, you will not be marked as attending.
On the seminar, you will be working together with other students on exercises as per instructed by the teacher. The exercises are formulated in such a way as to promote critical reflection and discussion, as well as to practice application of course concepts to case scenarios.*(not for AK2030 online - they have their own seminar-like assignments)
You are expected to engage actively with the course contents and work on the exercises during the seminar. Passive attendance on the seminar will be marked as not attending. Active participation on the seminar does not mean that you are expected to demonstrate full proficiency of course contents. Rather, it means that you are expected to have properly engaged with the relevant course material beforehand and made an honest attempt at understanding it. Arisen questions and reflections can be addressed on the seminar.
For information on what to do if you have not completed a preparation quiz or actively attended on a seminar, see the section on Examination and completion.
Note that the TimeEdit course schedule shows multiple seminar slots for every seminar week. The different slots correspond to different seminar groups. You will join one seminar group upon course start and your group takes only one seminar per seminar week. Instructions on how to join a seminar group as well as seminar group schedule will be available on Canvas after course start and before the start of the seminar series.*(not for AK2030 online)
Seminar contents and reading instructions
All course readings can be found on Canvas.
Seminar 1 – Definitions, operationalizations and hypotheses
Texts:
- Grüne-Yanoff, Till – Justified Method Choice, chapters 1, 2, 3, 13
- Optional reading: Hansson, Sven Ove – Art of Doing Science: sections 2.2-2.8, 3.1-3.2, 5.0-5.1, and 5.8
Topics relevant for the seminar:
- Stipulative and lexical definitions
- Narrowness and broadness (as applied to definitions)
- Vagueness
- Hypotheses (and their quality criteria)
- Direct, aided and indirect observation
- Operationalization
- Accuracy and precision (as qualities of observations and measurements)
- Measurement error (random and systematic error)
- Convergent validity and divergent validity
Seminar 2 – Designing a scientific study
Texts:
- Grüne-Yanoff, Till – Justified Method Choice, chapters 4, 5.
- Optional reading: Hansson, Sven Ove – Art of Doing Science: sections 3.7, 4.2-4, and 5.1-3.
Topics relevant for the seminar:
- Experiment, observational studies and model studies
- Mill’s method of difference
- Internal validity and external validity
- Experimental control
- Constancy, elimination and effect separation
- Randomization
- Control group and treatment group
- Observer influence
- Confirmation bias
- Blinding
- Epistemic virtues of models (Parameter precision, Similarity, Robustness, Simplicity, Tractability, Transparency)
- Analogies (positive, negative, neutral)
Seminar 3: Interpretation, analysis and evidence
Texts:
- Grüne-Yanoff, Till – Justified Method Choice: chapters 2, 6, 7.
- Optional reading: Hansson, Sven Ove – Art of Doing Science: sections 1.6-7, 3.7, 3.9, 5.3-5, 5.7, 7, 8 and the box on p. 24.
Topics relevant for the seminar:
- Repeatability, reproducibility and replicability
- Statistical evaluation
- Statistical significance
- Correlation and causality
- Explanatory virtues (Accuracy [of explanations], Non-sensitivity, Precision in the explanans, Precision of the explanandum, Cognitive salience)
- Duhem-Quine thesis
- Ad-hoc hypothesis
- Falsificationism (Popper)
- Inductive and deductive inferences
Seminar 4: Risk and research ethics
Texts:
- Grüne-Yanoff, Till – Justified Method Choice, chapters 11, 12.
- “On Being a Scientist: Responsible Conduct in Research”, National academy of Sciences.
- Ahlin, Jesper, “Ethical Thinking”.
- Optional reading: Hansson, Sven Ove - Art of Doing Science: Section 9.
Topics relevant for the seminar:
- Gift authorship and ghost authorship
- Scientific misconduct (falsification, fabrication and plagiarism)
- Informed consent
- Deontology, consequentialism and virtue ethics
- Precautionary principle
- Decision making (under certainty/risk/ignorance/deep uncertainty)
Project, 3 credits
In this part you will discuss the relationship between mathematics and reality. The part will consist of four lectures and one final assignment, graded pass, fail or revise. More information can be found on Canvas.