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Cognitive Science of Science (fakultet)

Informacje ogólne

Kod przedmiotu: 0500-KS1-2CSS Kod Erasmus / ISCED: 14.952 / (brak danych)
Nazwa przedmiotu: Cognitive Science of Science (fakultet)
Jednostka: Wydział Historyczno-Socjologiczny
Grupy: 3L stac. studia I stopnia kognitywistyka - przedm. fakultatywne
Punkty ECTS i inne: 3.00
zobacz reguły punktacji
Język prowadzenia: angielski
Rodzaj przedmiotu:

fakultatywne

Założenia (opisowo):

Good listening comprehension skills in English

Intermediate speaking skillls in English


Tryb prowadzenia przedmiotu:

w sali

Skrócony opis:

The aim of this course is to give students an overview of research in the cognitive science of science - a multi- and inter-disciplinary field that investigates various mechanisms underlying scientific activity. The disciplines studying different aspects of science include philosophy of science, correlational psychology, cognitive psychology, sociology, anthropology, artificial intelligence, and neuroscience. Each of them has its own repertoire of approaches that are sometimes difficult to reconcile with one another. Because it would be impossible to provide a comprehensive description of all relevant literature, the lectures focus on selected topics and attempt to shed light on them from a wide range of theoretical perspectives.

Pełny opis:

Profile: general academic

Type of studies: full-time

Type of subject: elective

Discipline: cognitive science

4th term

Prerequisites: good knowledge of English (at least B2)

No. of hours: 30

Teaching methods: lectures with PowerPoint presentations, in-class discussions, optional student presentations

3 ECTS points:

attendence - 30 hours (1 ECTS)

preparation for class - 30 hours (1 ECTS)

preparation for final exam - 20 hours (1 ECTS)

Quantitative indicators: no. of hours requiring direct involvement of the teacher: 30 (1 ECTS), practical (none)

Literatura:

Selected literature:

Atmanspacher, H.; Maasen, S. (eds.) (2016), Reproducibility: Principles, Problems, Practices, and Prospects, Wiley: Hoboken, NJ.

Bird, A. (2019), Understanding the Replication Crisis as a Base Rate Fallacy, British Journal for the Philosophy of Science.

Button, K.S., Ioannidis, J.P.A., Mokrysz, C., Nosek, B. ..., (2013), Power Failure: Why Small Sample Size Undermines the Reliability of Neuroscience, Nature Reviews Neuroscience 14(877): 365-376.

Chavalarias, D. & Ioannidis, J.P.A. (2009), Science Mapping Analysis Characterizes 235 Biases in Biomedical Research, Journal of Clinical Epidemiology 63: 1205-1215.

Craver, C. (2005), Beyond Reduction: Mechanism, Multifield Integration and the Unity of Neuroscience, Studies in History and Philosophy of Biological and Biomedical Sciences 36: 373–395.

Cronbach, L.J. (1957), The two disciplines of scientific psychology, American Psychologist, 12(11), 671-684.

Darden, L.; Maull, N. (1977), Interfield Theories, Philosophy of Science (44) 1: 43–64.

Fanelli, D. (2009), How Many Scientists Fabricate or Falsify Research? A Systematic Review and Meta-Analysis of Survey Data, PLoS ONE 4(5): e5738, doi:10.1371/journal.pone.0005738

Giere R. (2006), Scientific Perspectivism, Chicago: University of Chicago Press.

Machamer, P.; Darden, L.; Craver, C. (2000), Thinking about Mechanisms, Philosophy of Science (67) 1: 1–25.

Ioannidis, J.P.A. (2005), Why Most Published Research Findings are False, PLoS Med 2(8): e124.

Kraft, P., Zeggini, E., Ioannidis, J.P.A. (2009), Replication in genome-wide association studies, Statistical Science 24(4): 561-573.

Magnani, L., Nersessian, N.J., Thagard, P. (eds.) (1999), Model-Based Reasoning in Scientific Discovery, Springer: New York.

Merton R.K. (1968), The Matthew effect in science: The reward and communication systems of science are considered, Science, 159, 56–63.

Merton R.K. (1988), The Matthew effect in science II: Cumulative advantage and the symbolism of intellectual property, Isis, 79, 606–623.

Miłkowski, M., Hensel, W.M. & Hohol, M. (2018), Replicability or Reproducibility? On the Replication Crisis in Computational Neuroscience and Sharing Only Relevant Detail, Journal of Computational Neuroscience 45(3): 163-172.

Nosek, B.A., Ebersole, C.R., DeHaven, A.C., Mellor, D.A. (2018), The Preregistration Revolution, PNAS 115(11): 2600-2606.

Patel, C.J., Burford, B., Ioannidis, J.P. (2015), Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations, Journal of clinical epidemiology 68(9), 1046–1058.

Redner S. (2004), Citation statistics for more than a century of Physical Review, https://arxiv.org/pdf/physics/0407137.pdf

Sawyer R.K. (2012), Explaining Creativity: The Science of Human Innovation, Oxford: Oxford University Press.

Sawyer R.K. (2011) The Cognitive Neuroscience of Creativity: A Critical Review, Creativity Research Journal, 23 (2), 137-154.

Simonton, D.K. (2014), The Wiley Handbook of Genius, London: Wiley.

Stodden, V., Seiler, J., & Ma, Z. (2018), An Empirical Analysis of Journal Policy Effectiveness for Computational Reproducibility, Proceedings of the National Academy of Sciences, 115(11), 2584-2589.

Thagard, P. (1992), Conceptual Revolutions, Princeton: Princeton UP.

Thagard, P. (2012), The Cognitive Science of Science: Explanation, Discovery and Conceptual Change, Cambridge, MA: The MIT Press.

Zytkow, J. & Simon, H. (1986), A Theory of Historical Discovery: The Construction of Componential Models, Machine Learning, 1: 107-136.

Metody i kryteria oceniania:

Final exam in the form of a written multiple-choice test

Zajęcia w cyklu "Rok akademicki 2019/20" (zakończony)

Okres: 2019-10-01 - 2020-06-30
Wybrany podział planu:


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Typ zajęć: Wykład, 30 godzin więcej informacji
Koordynatorzy: Witold Hensel
Prowadzący grup: Witold Hensel
Lista studentów: (nie masz dostępu)
Zaliczenie: Zaliczenie na ocenę
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet w Białymstoku.