Course introducing Cognitive Science
Title: Mind, Computers and Human Behavior [Changed to Introduction to Cognitive
Science]
Overview
Our ideas of how the mind works underlie many facets of our lives, including how we
learn, speak and reason. How do we really think? And how can we describe the way we
think? Those are the questions that cognitive science seeks to answer.
This course introduces cognitive science, an interdisciplinary field that draws upon
aspects of cognitive psychology, philosophy, linguistics, anthropology, education,
neuroscience and artificial intelligence. Its unifying goal is to construct and evaluate
process-oriented theories of how people think and reason. Researchers in cognitive
science typically work under the assumption that processes of human thinking can be
understood in computational terms.
Students will read articles describing cognitive models and discuss how well the model
accounts for human behavior. When possible, the articles will be chosen from journals
such as Cognitive Science. For projects, students will experiment with computer
programs that purport to be models or simulations of some aspect of human cognition. In
some cases, the goal will be to modify these programs and then re-evaluate them as a new
scientific theory. Students will discuss to what extent these models constitute an
explanation for how people think as well as debate whether certain models serve as viable
scientific theories.
Learning Outcomes
At the end of the course, students will be able to
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Work with formal representations to solve problems.
Run working models under a variety of conditions.
Apply a variety of models that instantiate contrasting theories.
Write articles that describe an experimental procedure, its results and what can be
concluded from the experiment.
Present theories and models and explain how well they account for human
behavior.
Explain how physical brain mechanisms may implement cognitive functions.
Reflect on their own thinking and articulate their strategies for solving problems.
Examples of Models and Areas of Inquiry
The choice of models and human abilities will vary with the instructor’s interest and
expertise. However, the instructor should try to use a variety of models that perform tasks
in different areas. Here are some examples:
 Visual information processing: perceptual illusions and the use of specialpurpose, modular models for explaining them. Speech perception: identifying
evidence for and against modular mechanisms.
 Language: using rule-based systems to simulate verb conjugation, sentence
parsing or word pronunciation.
 Categorization: using artificial neurons to learn to classify objects.
 Human memory: what people remember from a list and how cognitive models
explain which items people remember.
 Elementary scholastic skills: a rule-based system that performs subtraction
problems. Rules can be deleted to show common problems observed with
elementary school children.
 Puzzles: running computer programs that solve popular puzzles such as the
Towers of Hanoi or the 8-Tile puzzle.
In all cases, the projects should involve working computer programs that students can
experiment with. Ideally, students should be able to modify some aspect of the model’s
behavior and further evaluate the model’s fit to human behavior.
Example Readings
Newell, A. (1973). You can’t play 20 questions with nature and win. In W. G. Chase
(Ed.), Visual Information Processing (pp. 283-308). New York: Academic Press.
Polk, T and Seifert, C. (Eds.). (2002). Cognitive Modeling. MIT Press.
Bechtel and Graham (Eds.). (1999). A Companion to Cognitive Science. Blackwell
Publishers.
Bransford et al (Eds). (2000). How People Learn: Brain, Mind, Experience, and School.
National Research Council.
Fodor, J. A. (1983). The Modularity of Mind. Cambridge, MA: MIT Press.
McGurk & McDonald. (1976). Hearing lips and seeing voices. Nature, 264:746-748.
Samuel, A. G. (1981). Phonemic restoration: Insights from a new methodology. Journal
of Experimental Psychology: General, 110(4), 474-494.