Cognitive Science is an interdisciplinary field of inquiry that is concerned with the acquisition, representation, and use of knowledge by individual minds, brains, and machines, as well as groups, institutions, and other social entities. Because the fundamental purpose of the university, as a social institution, is the preservation, generation, and transmission of knowledge, cognitive science speaks to the heart of the university's mission. By engaging faculty from Psychology, Philosophy, Linguistics, Computer Science, Neuroscience, and Anthropology, Sociology, and other social sciences in common purpose, Cognitive Science constitutes a microcosm of the university as a whole. Through the efforts of its faculty, UC Berkeley is one of relatively few institutions to offer an undergraduate major in this field. And in terms of the scope of our approach to the field, Berkeley's program is almost unique.

Cognitive science majors students are expected to approach problems of knowledge using the tools of several different disciplines: philosophy, psychology, linguistics, computer science, neuroscience, and various social sciences. This expectation is reflected in a demanding curriculum that moves from a broad introductory survey course (CogSci 1), to surveys of cognitive psychology and cognitive linguistics (CogSci 100 and 101, respectively), to a six-course distribution requirement covering the philosophy of mind, cognitive psychology, linguistics, computational modeling and artificial intelligence, neuroscience, and various social sciences. After fulfilling their distribution requirement, students have the opportunity to concentrate further study in one of these six fields, and to complete an honors thesis.

The structure of "Cognitive Science", as an interdisciplinary field of inquiry, is represented by the "Cognitive Hexagon" devised by a committee convened by the Sloan Foundation, which supported the field in its early years, -- with each of its vertices representing one of its constituent fields: Philosophy, Psychology, Linguistics, Neuroscience, Artificial Intelligence, and Anthropology. At Berkeley, we have broadened "Anthropology" to include a wider array of social sciences, such as Sociology and Economics; and broadened "Artificial Intelligence" to include a number of different approaches to the computational modeling of cognitive processes. On many campuses that host a cognitive science major, it is little more than a proxy for cognitive psychology, with perhaps a little computer science and neuroscience thrown in. By contrast, Berkeley's program is truly interdisciplinary. Even where cognitive science is implemented as an interdisciplinary major, most programs do not include a substantive social-science element; Berkeley's is one of the very few that requires all majors to make contact with each point on the cognitive hexagon.

The Undergraduate Student Learning Initiative divides program-level goals into two categories: discipline-specific goals that are unique to the Cognitive Science major, and universal goals that (we hope) are achieved by every liberal-arts graduate.

Discipline-Specific Goals. By the end of their undergraduate careers, Cognitive Science majors are expected to understand and critically evaluate:

• research and theory in cognitive psychology, including perception, attention, learning, memory, reasoning, problem-solving, judgment, and decision-making;
• research and theory in cognitive linguistics, with special attention to the relation between language and thought;
• various approaches to artificial intelligence, and the computational modeling of cognitive processes;
• the biological bases of cognitive functions, as uncovered by cognitive neuroscience;
• classic and contemporary work on the philosophy of mind, including the mind-body problem, mental causation, freedom of the will, and the nature of consciousness;
• the sociocultural context of individual cognition, including the social construction and organization of knowledge, cultural differences in cognition, the history of information, etc.

Universal Goals. We also expect that they will have acquired the following skills for lifelong learning and effective citizenship:

• formulating a well-organized argument supported by evidence;
• effectively written, spoken, and graphical communication;
• problem-solving in cognitive science and its constituent fields;
• applying critical thinking skills in new and complex situations;
• using probability and statistics in reasoning;
• understanding the social implications of theory and research in cognitive science for responsible professional, civic, and ethical behavior.

All of the program's discipline-specific goals are achieved as the student moves through the upper division of the curriculum, through the two required Core Courses (CogSci 100 and 101) and the six courses of the Distribution Requirement. Each of the courses also addresses one or more universal learning goals. The following chart shows how both sets of goals are addressed in the curriculum.

¹All Cognitive Science majors are introduced to Cognitive Psychology through CogSci 100, "Basic Issues in Cognition", which is also cross-listed as Psychology 120. In addition, they may satisfy the distribution requirement in cognitive psychology through any of a number of courses, including CogSci 102 ("Scientific Approaches to Consciousness"), CogSci 124 ("Psycholinguistics"), CogSci 126 ('Perception"), Psych 122 ("Human learning and Memory"), Psych 123 ("Concepts and Categories"), Psych 143 ("Language Acquisition"), and Psych 164 ("Social Cognition"). For the purposes of this report, CogSci 126, "Perception", serves as a representative of all these courses.

²All Cognitive Science majors are introduced to Cognitive Linguistics through CogSci 101, "The Mind and Language", which is also cross-listed as Linguistics 105. In addition, all CogSci majors are required to satisfy the distribution requirement in Linguistics through Linguistics 100, "Introduction to Linguistic Science".

³All Cognitive Science majors are introduced to artificial intelligence and Computational Modeling through one of two courses: CogSci 131 ("Computational Modeling of Cognition"), or CompSci 188 ("Introduction to Artificial Intelligence").

⁴Cognitive Science majors may satisfy the distribution requirement in Philosophy of Mind through any of a number of courses, including Phil 100 ("Philosophical Methods"), Phil 122 ("Philosophy of Knowledge"), Phil 133 ("Philosophy of Language"), Phil 135 ("Philosophy of Meaning"), and Phil 136 ("Philosophy of Perception"). For the purposes of this report, Phil 132, "Philosophy of Mind", serves as a representative of all these courses.

⁵Cognitive Science majors may satisfy the distribution requirement in Society, Culture, and Cognition through any of a number of courses, including CogSci 104 ("the Mind, Language, and Politics"), Anth 166 ("Language in Society"), Econ 119 ("Psychology and Economics"), Educ 140 ("Literacy: individual and Societal Development"), Ling 150 ("Sociolinguistics"), Psych 107 ("Buddhist Psychology"), Psych 164 ("Social Cognition"), Psych 166 ("Cultural Psychology"), and Soc 150 ("Social Psychology"). For the purposes of this report, CogSci 103 ("History of Information") serves as a representative of all these courses.

⁶The use of probability and statistics in reasoning is also covered by one of the lower-division requirements, Math 55 or CompSci 70 ("Discrete Mathematics").

 

The following paragraphs provide more detail about each of the courses in the Curriculum Map, including the methods by which they evaluate the discipline-specific and universal program-level goals.

Typical instructors: Carla Hudson-Kam, Tania Lombrozo, William Prinzmetal

At the completion of this course students should:

• Understand and be able to critically evaluate research and theory in cognitive psychology, including perception, attention, learning, memory, thinking, reasoning, problem-solving, judgment, and decision-making. In particular, students should understand the relationship between empirical data and theoretical claims, and be able to generate and evaluate arguments. This is assessed by requiring students to participate in experiments, respond to exam questions concerning the relationship between theory and evidence, and with written assignments that require students to generate and evaluate arguments.
• Understand the basic methods of cognitive psychology, including their strengths and limitations. This goal is assessed by having students complete writing assignments that require the critical evaluation of evidence, and with exam questions concerning the interpretation of data generated from various methods.
• Have some exposure to the primary empirical literature from peer-reviewed journals in cognitive psychology, including a basic understanding of how this literature can be searched and cited. This goal is assessed on written assignments that require students to consult and cite primary sources from the peer-reviewed empirical literature.
• Understand that the basic cognitive processes covered in the course govern their own behavior and are relevant to everyday life. This goal is assessed with exam questions that require students to apply principles learned from the course to interpret and make predictions about everyday scenarios.
• Appreciate the complexity and subtlety of human cognition, and in particular the fact that many of the processes we take for granted require sophisticated underlying computation. This goal is assessed on both exam question and written assignments concerning these underlying computations.
• Appreciate that cognitive psychology is one of several disciplines that contribute to the study of the mind, and that these disciplines are mutually informative. This goal is assessed with exam questions that require the integration of multiple kinds of data.

Typical Instructors: Alice Gaby, George Lakoff, Eve Sweetser

At the completion of this course, students should:

• Understand and critically evaluate research and theory in cognitive linguistics, including:
  • o linguistic categorization, prototypes, and category theory
  • o basic cognitive mechanisms such as image-schemas, frames, metaphor, metonymy, mental spaces
  • o embodiment and the neural basis for these cognitive structures and their linguistic correlates
  • o a repertory of culture-specific frame and metaphor analyses (for example, metaphors of self, action, time, emotions) - and some cross-cultural comparative context for these structures.
  • o applications to areas such as political thought, mathematical thought, philosophy, literature, education, etc.
  • o basic issues in the neo-Whorfian debate
  • o the typology of meaning relationships
  • o pragmatics
  • o language processing
  • o language acquisition
• Be able to evaluate the appropriateness of different kinds of data and different methodologies to particular problems. This goal is also assessed through the homework assignments.
• Formulate a well-organized argument supported by evidence. This goal is assessed through a series of approximately 6 written homework assignments.
• Communicate effectively in written, spoken, and/or graphical form. This goal is also assessed through the homework assignments.
• Students should have the ability to solve problems in the discipline. This goal is also assessed through the homework assignments.
• Students should understand the professional responsibilities of scholars of the discipline. In all homework assignments, students are required to give the names of other students they collaborated with, citing them throughout wherever appropriate.

These goals are primarily assessed through a series of approximately six written homework assignments which either present students with a novel dataset and require them to present an analysis employing a relevant theory (e.g. constructing a polysemy network, or mental spaces diagram) or present students with a research question and require them to gather primary data in order to answer the question. In addition, there are also in-class quizzes (usually in multiple-choice format) designed to evaluate the students' comprehension and internalization of key concepts, studies, and methodological principles covered in class. Finally, there is a final project or take-home exam in which students have the opportunity to demonstrate their mastery of the skills they have developed over the course of the semester and a more sophisticated understanding of the existing literature in this area.

Typical Instructors: Stephen Palmer, William Prinzmetal

The goal for this course is for students to understand and critically evaluate the scientific understanding of sensation and perception from an interdisciplinary perspective that includes psychology, neuroscience, computer science, and philosophy.  Material to be covered includes theories of perception, methods of measurement, phenomena of perception, physiological mechanisms, and evolutionary constraints in one or more sensory modalities.  More general goals include the following: constructing a well-organized written argument supported by evidence, understanding the scientific method of theory construction and hypothesis testing, analyzing complex mental processes into an interconnected structure of simpler processes, and appreciating the mutual constraints arising from sensory information, phenomenal experience, computational models, neural mechanisms, and evolutionary development.

Typical Instructor: Richard Ivry

In this course, students will become familiar with the interdisciplinary approach embraced by cognitive neuroscience for investigating the relationship of the mind and brain. A major goal for the students is to understand and appreciate the diverse methodologies employed in the field. These include, but are not limited to, behavioral studies with healthy and neurologically impaired individuals and physiological methods used to measure brain function at various scales and in various species (single cell to whole brain). Students should come to appreciate how cognitive neuroscientists apply these methods in a bi-directional manner, asking how mental functions are instantiated in neural networks and how neural data can be used to inform and test our models of our mental function. Students will develop skills in reading original research articles, with a particular emphasis on identifying independent and dependent variables. The section discussions and exams will emphasize these critical skills, in part by asking students to design and critique experiments related to the course material.

Typical Instructors: Jose Carmena, Tom Griffiths

The general goal of this course is to provide advanced students in cognitive science and computer science with the skills to develop computational models of human cognition. Computational modeling is one of the central methods in cognitive science research, and can help to provide insight into how people solve the challenging problems posed by everyday life, as well as how to bring computers closer to human performance for some of these problems. The course will explore three ways in which researchers have attempted to formalize cognition -- symbolic approaches, neural networks, and probability and statistics -- considering the strengths and weaknesses of each. At the conclusion of this course, students should have the ability to solve problems in the three different approaches to formalizing cognition covered in the course, through a series of six problem sets which involve some programming in Matlab. Students are be able to collaborate when solving problems, but each student must write his or her own code, write the document containing his or her answers independently, and list the people he or she worked with on his or her problem set. There is also a take-home final exam.

Typical Instructors: Daniel Klein, Jitendra Malik, Stuart Russell, Robert Wilensky

The goal of this course is to understand and apply computational methods to the core problems of artificial intelligence: reasoning, decision making, learning, and perception. CS188 provides an introduction to the full range of topics studied in artificial intelligence, with emphasis on the core aspects of intelligent systems: problem solving, reasoning, decision making, learning, and perception, including the mathematical foundations of these activities.  Topics include search, planning, logical modeling and inference, probabilistic modeling and inference, utility-based decision making, statistical learning, natural language processing, vision, and robotics.  The course supports the cognitive science curriculum by (1) teaching foundational modeling techniques, (2) examining algorithms which produce complex behavior associated with cognition in humans, and (3) giving students experience in implementing such techniques and algorithms in engineered systems.

Typical Instructors: Susanne Gahl, Andrew Garrett

The learning goals for Ling 100 include familiarity with the goals and key concepts of the scientific study of language and speech, including the

• study of phonetics, phonology, morphology, syntax, semantics, and
• pragmatics; the ability to analyze phonological, morphological, and
• syntactic structure in a wide range of languages; and an acquaintance with
• a range of important linguistic phenomena drawn from a variety of
• languages, including languages unrelated to English.

Typical Instructor: John Searle

The overall objective of this course is to understand and critically evaluate classical and contemporary issues in the philosophy of mind, including the mind-body problem, mental causation, freedom of the will, the nature of intentionality, the nature of consciousness, the structure of human action and the relation of cognition and volition. As I teach the course, I regard it as, in a sense, giving the philosophical foundations of cognitive science. To this end, I examine various alternative conceptions of the nature of cognitive science including Strong Artificial Intelligence, cognitivism, connectionism and my own view, which I call Biological Naturalism. Students are expected to learn to think for themselves about these issues. They are also expected to learn how to construct rigorous, concise arguments, and criticize the arguments of others. The methods of evaluating the achievement of these goals is as follows. There are four required papers, and the papers are graded not only on the students' ability to repeat material that they have already heard in class or the readings, but to construct original works of philosophical analysis. There is an essay final examination where the student is expected both to integrate the material learned in the course together with critical assessment of that material. Among other things, the students are expected to learn to write clearly and concisely and both the essays and the final examination serve this purpose. In addition to the lectures, the students are also expected to attend discussion sections where they are expected to be able to express themselves clearly and rigorously.

Typical Instructors: Paul Duguid, Geoffrey Nunberg

This course seeks to help students set the notion of knowledge, construed as information, in historical context.  We look not only at the technology of communication, but also at social forms that have given shape and meaning to what we now think of as information.  Topics covered include the nature of information and information-processing; the development of writing systems and their effects on cognition and social organization; the transition from manuscript to print culture; the role of early newspapers and the coffeehouse as vehicles for the transmission of information; reference books, museums, and libraries as "authoritative" sources of information; journalistic objectivity; the information economy; point-to-point communication; broadcasting and the rise of mass communication; intellectual property and the "ownership" of information; advertising and the "branding" of information; the Internet, Web 2.0, and information literacy. As a result of the course, students should understand the importance of and application of critical thinking skills to new and complex situations that are conceived of in terms of information. Assessment consists of three short midterm exams and a final exam in short-essay format.

Information about the Cognitive Science major is communicated to students and prospective students via the program website at http://ls.berkeley.edu/ugis/cogsci/, as well as in a printed brochure. This Student Learning Initiative report concerning the educational goals of the Cognitive Science major will also be posted to the program website.