Universität Wien

180218 VO-L Cognitive Science - Introduction and Basic Concepts (2025W)

3.00 ECTS (2.00 SWS), SPL 18 - Philosophie

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

Sprache: Englisch

Prüfungstermine

Lehrende

Termine

Mon. 29.09. 13:00-16:00 Introduction meeting (MEi:CogSci students only)
Thu. 02.10. 09:00-11:00 General preparation meeting for MEi:CogSci courses (MEi:CogSci students only)

Thu. 02.10. 11:00-13:00 VO Introduction
Mon. 06.10. 09:00-13:00 VO Symbol Systems, Connectionism
Mon. 13.10. 09:00-13:00 VO Connectionism, Dynamical Systems
Mon. 20.10. 09:00-13:00 VO Artificial Neural Networks (by Prof. Igor Farkas from the Comenius University in Bratislava)
Mon. 27.10. 09:00-13:00 VO 4E Cognition
Mon. 03.11. 09:00-13:00 VO Predictive Processing, Reflection

All lectures are held in lecture hall HS2i, NIG.


Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course introduces cognitive science as an interdisciplinary field that emerged in the mid-20th century from the convergence of philosophy, psychology, neuroscience, computer science, linguistics, and anthropology. Its central aim is to understand cognition in humans, animals, and machines, using a range of conceptual and methodological approaches.

Students will explore the major research paradigms that define the field. These include the symbolic approach, which models cognition as rule-based symbol manipulation; connectionism (or artificial neural networks) which emphasize learning through distributed activation; and dynamical systems theory, which sees cognition as a continuous, time-based process. The course also covers the 4E approaches (embodied, embedded, extended, and enactive cognition) which highlight the role of the body, environment, and social context in shaping mind and behavior. Finally, it introduces Predictive Processing, a contemporary paradigm that conceptualizes the brain as a system of hierarchical prediction and error correction.

Throughout, the course encourages critical reflection on how these paradigms frame our understanding of mind and knowledge, and how interdisciplinary perspectives shape cognitive science as a whole.

The course is delivered in a lecture format, with presentation and explanation of core paradigms, theoretical frameworks, and interdisciplinary perspectives in cognitive science. While the format is primarily instructor-led, lectures include opportunities for clarification, brief discussions, and student questions to support engagement and understanding. Students are expected to consult the assigned literature to deepen their knowledge and to prepare for the written examination.

The following learning outcomes are targeted:
* Identify and distinguish major paradigms in cognitive science
* Explain the core assumptions and conceptual frameworks of each paradigm
* Recognize how different disciplines contribute to and align with different paradigms
* Compare paradigms conceptually, noting similarities, differences, and tensions
* Interpret research in light of specific paradigms and their methodological assumptions
* Reflect critically on the implications of different paradigms for understanding cognition in humans, animals, and machines
* Communicate foundational concepts and paradigm distinctions clearly, both orally and in writing

Art der Leistungskontrolle und erlaubte Hilfsmittel

The course is assessed through a 90-minute written examination. Students are required to answer two out of three open-ended questions. Responses should be written in essay format, with approximately two pages per question.

The use of aids is not permitted during the examination. This includes electronic devices (e.g., laptops, tablets, smartphones) and printed materials (e.g., books, articles, notes).

All course materials will be available on Moodle.

Please make sure to register for the examination ahead of time. No admission without registration.

*** Optional bonus achievements ***
This lecture uses optional bonus achievements to support continuous learning. By successfully completing all bonus achievements, students may be eligible to receive a one-grade improvement. However, completing all bonus achievements does not guarantee a positive overall assessment. (For example, if a student fails the exam, bonus achievements will not be considered.)

Students are permitted to use Microsoft 365 Copilot Chat when working on bonus achievements, to help develop their AI literacy. Microsoft 365 Copilot Chat is based on GPT-4/GPT-5 and includes Enterprise Data Protection. Its use is only allowed if the following conditions are met: (1) Use is explicitly disclosed and (2) the University of Vienna’s guidelines for using Generative AI have been understood and followed.

Students of the University of Vienna have free access to Microsoft 365 Copilot Chat by ordering and activating Microsoft 365 for Students at no cost. See:
* AI in studies and teaching: https://studieren.univie.ac.at/en/studying-exams/ai-in-studies-and-teaching/
* Microsoft 365 for students: https://zid.univie.ac.at/en/software-for-students/user-guides/microsoft-365-students/
* Microsoft 365 Copilot Chat: https://www.microsoft365.com/chat

Mindestanforderungen und Beurteilungsmaßstab

To take the exam it is required that you are registered for the examination date.
To pass the exam it is required that you identify yourself with a valid photo ID.

Assessment criteria (weight):
* Quality of Argument (60%), i.e., clarity, coherence, and depth of the argument; accurate use of concepts; responsiveness to the question
* Interdisciplinary Awareness (15%), i.e., ability to connect perspectives from different disciplines (e.g., philosophy, neuroscience, psychology) relevant to the topic.
* Personal Insight & Reflection (15%), i.e., thoughtful engagement with the material; awareness of one’s own disciplinary background and assumptions.
* Originality & Intellectual Contribution (10%), i.e., independent thinking, creative framing of ideas, or novel connections that go beyond course content.

Points | Grade
93-100 | very good (1)
83-92 | good (2)
73-82 | satisfying (3)
60-72 | sufficient (4)
0-59 | failed (5)

Assessment criteria for optional bonus achievements:
* All-or-Nothing Principle: All bonus achievements must be completed, submitted on time, and done in good faith.

Prüfungsstoff

Bermúdez, J. L. (2023). Cognitive science: An introduction to the science of the mind (4th ed.). Cambridge University Press.
* Chapter 4: Physical Symbol Systems and the Language of Thought
* Chapter 5: Neural Networks and Distributed Information Processing
* Chapter 6: Applying Dynamical Systems Theory to Model the Mind

Clark, A. (2014). Mindware: An introduction to the philosophy of cognitive science (2nd ed.). Oxford University Press.
* Chapter 2: Symbol Systems
* Chapter 4: Connectionism
* Chapter 7: Dynamics
* Chapter 11: Prediction Machines

Gallagher, S. (2023). Embodied and enactive approaches to cognition. Cambridge University Press. https://doi.org/10.1017/9781009209793
* Chapter 3: The First E: Embodiment
* Chapter 4: The Second E: Embedded Cognition
* Chapter 5: The Third E: Extended Cognition
* Chapter 6: The Fourth E: Enactive Cognition

Literatur

Supporting materials (optional):
* Alexander, C. (2025). What is 4E cognitive science? Phenomenology and the Cognitive Sciences, 1–26. https://doi.org/10.1007/s11097-025-10055-w
* Bermúdez, J. L. (2023). Cognitive science: An introduction to the science of the mind (4th ed.). Cambridge University Press. https://tinyurl.com/4zrrbcez
* Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36(3), 181–204. https://doi.org/10.1017/S0140525X12000477
* Friedenberg, J. D., Silverman, G. W., & Spivey, M. J. (2022). Cognitive science: An introduction to the study of mind (4th ed.). SAGE Publications. https://tinyurl.com/3ksa7fbm
* Harré, R. (2002). Cognitive Science: A Philosophical Introduction. SAGE Publications.https://tinyurl.com/2v8y3w5u
* Hohwy, J. (2013). The predictive mind. Oxford University Press. https://tinyurl.com/ytx8nr9f

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 05.11.2025 11:26