Teaching
Awards
Outstanding Graduate Student Instructor University of Michigan
Rackham Graduate School, University of Michigan 2006/07
Competitive teaching award given to twenty students across the university by the Rackham School of Graduate Studies. link
Outstanding Graduate Student Instructor Dept. Psychology
Department of Psychology, University of Michigan 2005/06 and 2006/07
One of three students recognized by the Department of Psychology for outstanding teaching.
Workshops
International MBA Program, IE Business School
2010 Decision Making Skills (4 hour workshop; 4 sessions of 50 students).
Guest Lecturing
Department of Psychology, University of Michigan
Invited lectures of 1.5 hours for the course Introduction to Cognitive Psychology. Class size: ~200 students.
Podcasts of lectures available by request
2008 Judgment & Decision Making.
2008 Deductive Reasoning.
2007 Visual Imagery I: Visual Memory, Spatial Memory, Heuristics.
2007 Top-Down Perception: Expectations, Context Effects, & Interactive Activation.
2007 Language I: Structure and Meaning.
2007 Long Term Memory: Semantic Networks.
2007 Language: Structure, Meaning, Localization in the Brain.
2006 Language: Structure, Meaning, Localization in the Brain.
2006 Judgment and Decision Making.
Teaching
Served as a Graduate Student Instructor for ten terms and approximately 600 undergraduate students. Responsibilities included planning and teaching weekly sections, one-on-one meeting with students in office hours, informal mentoring, and running exam reviews sessions, and assigning grades.
Teaching evaluations, student comments, and references available by request.
Introduction to Cognitive Psychology (Psych 240)
Fall 2008, Winter 2007, Winter 2006, Winter 2005, Fall 2004. With Thad Polk, Bill Gehring, Cindy Lustig.
Mean Instructor Rating: 4.91 out of 5.00
Responsibilities: 3 sections, 75 students
The topics covered include various aspects of the psychology of human perception, attention, memory, thinking (including problem solving and reasoning), and consciousness. The material includes data and theory about the relationship between cognition and brain function. The course emphasizes not only the content material represented by these topics, but also the process by which researchers develop theories and collect evidence about relevant issues. Readings are drawn from a textbook and several primary sources. The course includes lectures, discussion, demonstrations, in-class experiments, and practice on problem-solving exercises.
Introduction to Psychopathology (Psych 270)
Winter 2009, Fall 2006, with Joe Gone
Mean Instructor Rating: 4.88 out of 5.00
Responsibilities: 2 sections, 60 students
This survey course introduces students to key issues in the contemporary scientific investigation of psychopathology (or mental illness). Topics reviewed include: efforts to systematically describe and understand psychological distress; the challenge of developing a useful system for classifying kinds of psychopathology; the process of empirical validation of purported disorders; and the problem of conceptualizing psychological distress across cultures. In addition, students become familiar with the role and significance of the Diagnostic and Statistical Manual of Mental Disorders, including several prevalent DSM-IV disorders and their diagnostic criteria. This course consists of both lectures and discussion sections that elucidate and extend material treated in the textbook.
Introduction to to Human Neuropsychology (Psych 345)
Fall 2005, with Jeffrey Hutsler
Mean Instructor Rating: 4.93 out of 5.00
Responsibilities: 2 sections, 70 students
Human neuropsychology seeks to understand human cognition and brain organization. It utilizes similar methods as cognitive psychology to analyze behavior in brain-damaged patient groups as well as normal subjects. This course gives an overview of human brain organization through the use of case studies and experimental research in patient populations. Topics covered include visual function, language, memory, and executive functions.
Introduction to to Artificial Intelligence (EECS 492)
Winter 2004 with Satinder Baveja; Fall 2003 with Michael Wellman
Mean Instructor Rating: 4.48 out of 5.00
Responsibilities: 2 sections, 60 students
The purpose of this course is to introduce the student to the major ideas and techniques of Artificial Intelligence, as well as to develop an appreciation for the engineering issues underlying the design of intelligent computational agents. The successful student finishes the course with specific modeling and analytical skills (e.g., search, logic, probability), knowledge of many of the most important knowledge representation, reasoning, and machine learning schemes, and a general understanding of AI principles and practice. The course serves to prepare the student for further study of AI, as well as to inform any work involving the design of computer programs for substantial application domains.
Undergraduate Mentoring
Tracy Ederer, UM Psychology Program 2008/09
Honors Thesis: “Revealing individual differences in decision-making behavior”.
Kristin Pearson (w/ Thad Polk), UM Brain, Behavior & Cognitive Science Program 2006/07
Honors Thesis: “Individual differences in verbal working memory”.
Zachary Guren (w/ Thad Polk), UM Psychology Program 2006/07
Honors Thesis: “Testing the validity of a fixed history method for the Iowa Gambling Task”.
Sally Hollister (w/ Thad Polk), UM Brain, Behavior & Cognitive Science Program 2005/06
Honors Thesis: “Articulatory versus acoustic coding in verbal working memory”.
Service & Training in Teaching
IE University
Facilitator, Student-Faculty Tertulia on history, psychology & politics of money 2010
Center for Research on Learning and Teaching, University of Michigan
Facilitator, Training for New Graduate Student Instructors 2009
Participant, New Graduate Student Instructor Training, Department of Psychology 2004
Participant, New Graduate Student Instructor Training, College of Engineering 2003
