Quantitative Reasoning at Yale

Yale College Yale University 11 Graduate and Professional Schools 5300 Undergraduates from all 50 states and >70 countries Middle 50% SAT scores % of students receiving need-based financial aid

Yale College Distribution Requirements (late 1970s through class of 2008) Three courses in each of four distributional groups Group I – languages and literature Group II – other humanities Group III – social sciences Group IV – math, science, engineering (at least two courses must be in natural sciences)

Committee on Yale College Education Richard Brodhead, Chair formed in Fall, 2001 report published April, faculty, students and recent alumni Recommendations included enhancement of education in sciences and institution of new distribution requirements, including a quantitative reasoning requirement.

New Distribution Requirements Class of 2009 and beyond Skills Requirement 2 courses in writing 2 courses in quantitative reasoning 1-3 courses in foreign language Area Requirement 2 courses in humanities 2 courses in social sciences 2 courses in natural sciences

Faculty QR Council Paul Hudak, Computer Science, Chair Joseph Chang, Statistics Michael Frame, Mathematics Donald Green, Political Science Roger Howe, Mathematics Roman Kuc, Electrical Engineering Benjamin Polak, Economics William Segraves, Yale College R. Shankar, Physics Steven Stearns, Ecology and Evolutionary Biology Teresa Treat, Psychology Kurt Zilm, Chemistry Steven Zucker, Computer Science

Key Questions What is QR? What courses should count as QR courses? Core vs. Applied QR

Key Questions What is QR? What courses should count as QR courses? Math (and applications) Stats (and applications) Comp Sci? Philosophy?

A course may be used to satisfy the quantitative reasoning requirement if it meets the following criteria: A primary aim of the course is to develop quantitative reasoning or its application. Quantitative reasoning includes mathematics, statistics, algorithms, and formal symbolic logic. Calculation, quantification, and measurement can supplement but cannot replace quantitative reasoning and problem solving. A substantial proportion (generally a majority) of course exercises, such as problem sets, should be designed to develop and strengthen quantitative reasoning skills through regular practice. Examinations or assigned projects should similarly be primarily quantitative in nature and should require students to demonstrate their quantitative reasoning skills.

QR Courses without Prerequisites (32) Various courses for majors and non-majors in calculus, statistics, comp sci, engineering and physical sciences, and others including: Applied Math – The Pleasures of Counting Architecture – Introduction to Structures Comp Sci - Visualization: Data, Pixels and Ideas Great Ideas in Computer Science Economics - Introductory Microeconomics (3 versions) Environmental Studies/G&G – Atmosphere, Ocean and Environmental Change Math - Fractal Geometry (plus freshman seminar) Music – Math, Music and Mind Operations Research – Introduction to Management Science: Probabilistic Models Philosophy – First Order Logic Psychology – Statistics

Council Review - Implications Political Departmental Interests Individual Faculty Concerns Logistical Review of new and existing courses Tracking of distributional designations

Variations on QR Requirements Place-out permitted Students place out on the basis of test scores or take test to place out of requirement What to provide for students who don’t place out All students required to take QR courses How to meet needs of diverse student population How to place students

Assessment of QR Preparation Placement Questionnaire Length - needs to be short Breadth- test full range of QR areas Is it more valuable than SAT? Iatrogenic effects

Placement and Advising Individual Advising Web-based tools

Outcomes Assessment Enrollment in QR Courses Evaluation of Individual Courses Skills assessment What skills should we expect to see change? Omnibus QR exit assessment? Attitudes assessment

Tutoring Support STARS Program Residential College Tutors (grad students, walk-in) Science and QR Tutors (assigned, mostly undergrad) Course-Based Peer Tutors

Support for Teaching Training for Teaching Fellows and Faculty Assistance with Course Development and Implementation of New Teaching Methods

Challenges in QR Education Anxiety Negative Experiences Stereotype Threat

* Schmader, T., & Johns, M. (2003). Converging evidence that stereotype threat reduces working memory capacity. Journal of Personality and Social Psychology, 85,

Communicate the message that you think everyone has the potential to succeed in quantitative courses Communicate that all individuals are welcomed, supported, and valued whatever their background and experiences Remind students of malleability of quantitative skill Facilitate specific, external, unstable attributions for quantitative difficulties Minimize activation of stereotypes and presence of stereotypic expectations

Faculty Buy-In Support for career Logistical support Pedagogical support Valuing teaching