ࡱ> \^[ %=bjbj 0T4]8$A<s9}}}}}XXX9999999U<>p9XXXXX9}}-9: : : X}}9: X9: : 68}p-x"f79C90s97^g?: g?48g?8$XX: XXXXX99: XXXs9XXXXg?XXXXXXXXX : Revised Quantitative and Mathematical Reasoning Requirements The Committee on the Undergraduate Curriculum moves that the Faculty add new Section II.B.3.d to the Curricular Rules: II.B.3.d. Quantitative and Mathematical Reasoning Requirements as follows: (effective for students matriculating in September 2011 and thereafter) Each student must demonstrate the application of the quantitative skills needed to succeed in their professional and personal lives as well as many social and natural science courses by either a satisfactory score on the diagnostic assessment offered before the start of the freshman year or completing a Q-Sem with a grade of 2.0 or higher during the freshman year Each student must complete, with a grade of 2.0 or higher, before the start of her senior year, one course which makes significant use of at least one of the following: mathematical reasoning and analysis, statistical analysis, quantitative analysis of data or computational modeling. Courses that satisfy this requirement are identified by the sponsoring department or program, subject to review by the Committee on the Undergraduate Curriculum and are designated Q in course catalogs and guides. (3) In addition, the following regulations apply: A student cannot credit the same course to meet both the Q and distribution requirements. Students may use credits transferred from other institutions to satisfy these requirements only with prior approval. Curriculum Committee is responsible for maintaining and updating, after broad consultation with the faculty in affected disciplines, a memorandum of understanding identifying the quantitative skills to be addressed in the Q-Sem. Quantitative and Mathematical Reasoning Requirements Rationale and Explanations Goals for Students Part one of requirement: Quantitative Literacy Goal A. To equip students with the quantitative skills necessary later in their professional and personal lives. Students will be able to understand and critically analyze quantitative information and arguments, and construct arguments based on quantitative information. Part one of requirement: Quantitative Literacy Goal B. To develop the fundamental quantitative literacy skills needed for many social science and natural science courses. With a quantitative literacy base required for all students, courses in the natural and social sciences would spend less time on basic quantitative skills and could proceed with more challenge and rigor. Part two of requirement: Mathematical or Quantitative Work. To enhance student confidence and depth and breadth of understanding through advanced quantitative or mathematical study at the college level. Requirement: Part one: Quantitative Literacy: demonstration of the quantitative literacy skills listed below. The emphasis would be on using these skills in context, not as a mechanical application of an algorithm. Satisfied by a sufficient score on the diagnostic assessment offered before the start of the freshman year, or by passing a quantitative literacy course (Q-Sem) during the freshmen year. Part two: Mathematical or Quantitative Work: Completion of a course that makes significant use of mathematical reasoning/analysis, or of a data overlay course where students use their quantitative skills in a particular disciplinary domain. Having part one of the requirement (quantitative literacy) will allow the criteria for what counts as a course for part two to be more rigorous than is true under the current Q requirement. (see criteria below). Diagnostic assessment Composed of modules, each of which corresponds to one of the areas listed in the quantitative literacy skills list below. Assessment would also include some basic arithmetic and computational skills. Sample assessments would be posted during the summer before freshman year as well as supporting on-line instructional modules for each part of the assessment, allowing students to strengthen weak areas before attempting the test. An opportunity to self-test will also allow students to get a more accurate sense of their skills. Each module would be scored separately, creating a profile of a students strengths and weaknesses across the spectrum of quantitative skills. Such assessment, when coupled with an awareness of the skills necessary for specific courses (listed on the syllabi of these courses in the appropriate section), can help students in natural and social science courses target those areas where their skills need strengthening. Students will participate in the assessment before the fall of the freshmen year. Students may elect to bypass the assessment and register immediately for the quantitative literacy course or for Math 005. Students who do very well on the assessment would be able to place out of the quantitative literacy course. Students who show a weakness in basic arithmetic and computation skills would first be required to complete Math 005 to strengthen these skills (see below). Upon successful completion of Math 005, they would proceed to the Quantitative Literacy course. Students who are below competency level in only one module can choose to develop strength in this area by completing an on-line module or workshop, rather than having to take the whole quantitative literacy course. Workshops in each of these modules may also be offered to students throughout the year (perhaps at a quantitative center akin to our writing center) and on-line as refresher supplements to quantitatively based courses. Creating and scoring the assessment Assessment will be built at Bryn Mawr after extensive consultation with faculty who teach courses requiring quantitative skills The assessment would be sensitive to student performance. For example, students who have significant weakness in basic arithmetic skills might exit the assessment after this section. Students who perform well on challenging problems may not be asked to do simpler ones, but students will be asked to show competency in all skill areas. Successful completion of the assessment requires a threshold score overall and on each module NOTE: This assessment does not replace the Math Departments placement test, which measures pre-calculus and calculus skills. The Quantitative Literacy Course or Q-Sem Teaches the skills on list at the end of this document. Emphasis will be on applying these skills in a context. While there was good agreement as to what these skills should be among many of the faculty in the natural and social science, more work will be needed in the context of developing the course to further operationalize and perhaps prioritize these skills. Each Q-Sem will have a theme that is chosen to create an interesting context in which to apply the quantitative skills that are being learned. Such themes might include: Environmental Sustainability, Personal Finance, Sports. Themes could also be drawn from our traditional departments; however, the learning goals of the course would be focused on the demonstration of quantitative skills in context, rather than on content based knowledge. The course will need to be designed in close consultation with faculty from the natural and social sciences. Care will needed in choosing an instructor who is dynamic, excited about the topics and teaching them, and who is sensitive to the needs of students who are under-prepared and/or uncomfortable with quantitative skills. Benefits of the quantitative literacy course (Q-Sem) Teaches the skills on list below. All students who are interested in the sciences and social sciences will be prepared to be successful in the substantial quantitative aspects of these fields. Emphasizes applications and real world situations, e.g. survey results, medical studies, voting patterns. This applied emphasis will enable students to understand quantitative information and arguments that they will encounter throughout their lives. Supplements in-class instruction with self-paced, computer-assisted instruction Emphasizes creating competencies. Likely benefits students preparing for GREs and MCATs, particularly upcoming revision of the MCAT, which will likely have a more statistical orientation. Faculty will need to become more aware of the quantitative skills that students are expected to gain from the Q-Sem and what skills are more specialized knowledge that faculty will need to incorporate in their classes. In this way, faculty will be better able to tailor instruction to the students abilities. Criteria for courses satisfying Part Two of the requirement: Mathematical or Quantitative Work (This requirement is VERY similar to the one that we have now, BUT bar would be raised from current requirement.) Courses would show at least one of the following: Significant use of statistical analysis Significant quantitative analysis of data Significant use of computational modeling Significant use of mathematical reasoning or analysis QUANTITATIVE LITERACY SKILLS (to be taught in Q-Sem): These skills are those that students will need in their lives beyond Bryn Mawr to be responsible citizens and make smart choices. Thus passing the quantitative literacy course is a graduation requirement (that many students will possess when they arrive). The emphasis in teaching these skills will be to enable students to apply them to real world problems or use them within a content area. These quantitative literacy skills are also those that are frequently the basis of more sophisticated quantitative work in the natural and social sciences. Thus making students quantitatively literate will prepare them to take advantage of our own curriculum as well. NOTE: Each Q-Sem will have a content theme, so that it will be easier for these skills to be taught and learned in a context. Themes that might particularly lend themselves to teaching these skills could be: Environmental Sustainability; Personal Finance; Sports. Themes might also be drawn from traditional disciplines, but the course would be focused on the learning goals surrounding quantitative skills, with the content there to provide a context. Computation Skills - understanding and using exponents and roots; logarithms and inverse logs Basic Probability - understanding frequency distributions: shape of normal (Gaussian) curves; - understanding basic combinations of events and probability (e.g., coin toss) -understanding conditional probability Central Tendency - knowing the definitions of mean, median & mode and their properties - understanding statistical variability and standard deviation - knowing how to compute weighted averages and how these averages differ from a straight average Tables and Graphs - reading tables of data - constructing and understanding x-y plots REVIEW/APPLICATION - constructing and understanding an x-y plot with a straight line fit to the data (i.e., a linear equation of the form y = mx + b) -- REVIEW/APPL. -understanding bar graphs, pie charts -graphing non-linear functions and their slopes. understanding how they differ from linear functions Basic Algebra Working with basic types of equations (e.g., distance = rate x time) - solving for a single variable REVIEW/APPLICATION - solving linear equations backward and forward (e.g., using rate and distance to get time; or calculating mass from volume and density REVIEW/APPL. - rearranging equations to make them apply to the problem at hand (not quite the same thing as solving backwards and forwards) REVIEW/APPL. - converting from one unit of measure to another unit Magnitude of Numbers / Sense of Scale - calculating answers and/or providing estimates as an order of magnitude - understanding the concept of significant figures in terms of the precision of an answer. Interpreting Word Problems - setting up problems from a context - identifying the quantitative question being asked and relevant information - setting up problems that have multiple steps and/or are not solved by using just one standard formula [this is really the goal to be able to use a multitude of these basic skills simultaneously or in the appropriate order to solve a problem that is more complex than a plug and chug] -evaluate/reflect on the answer to the problem as to its reasonableness given the problem/context SKILLS LEARNED IN MATH 005 These skills are basic skills that almost all students would have acquired in high school. They are considered pre-requisite to most of the skills covered in the quantitative literacy course. Students who fail to demonstrate these skills during the assessment would begin with Math 005 to gain these skills as well as others. Arithmetic and Computation Skills - computing using four basic operations (add, subtract, multiply, divide) - estimating without a calculator - understanding and properly using numbers with decimals - understanding and manipulating fractions esp. proportional relationships - understanding that fractions and proportions are the same thing, and that percentages are simply a special type of fraction - understanding, computing and applying percentages - computing an average -understanding a Venn diagram - using and understanding scientific notation -having some sense of the relative size of big and small numbers and how they relate to each other, or knowing how to estimate this Linear Equations and Functions - constructing x-y plots - slope, y-intercept -graphing linear equations - solving an equation for a single variable     Committee on the Undergraduate Curriculum Faculty meeting of April 21, 2010 <=4 8 C I [ $ = > 89AYZwx߾}u}}u}h"ZOJQJh~}^h"ZOJQJh"Z6OJQJh~}^h"Z6OJQJ h~}^h"Zh~}^h"Z5h9 h"Z^JaJ h h"ZhL&h"Z^JaJh'Nh"Z^JaJh h"Z^JaJh"Z^JaJ ht"h"Zh"Z h%ka5hHFh%ka5.=>I J n =  7$8$H$^gd"Z 7$8$H$^gd"Z & F7$8$H$gd"Z & F7$8$H$gd"Z 7$8$H$gd"Zgd"Z$a$gd"Z@A  }~ & Fgd"Z & Fgd"Zgd"Z & Fgd"Zgd"Z[\#$G  rs  }~~t u v w !!""""""##9$:$h~}^h"Z5OJQJh"ZOJQJh~}^h"Z6OJQJh~}^h"Z5 h~}^h"Zh~}^h"ZOJQJNDEv w ""##%%% & F gd"Z & Fgd"Zgd"Z & F gd"Z & Fgd"Zgd"Z:$%%K%L%m%n% &&w&x& ' 'Z'['}'~'((((O)P))))) *U*}*~***** + +C+++,,g-h----V.W.....////00001ͼͼͼ汣h~}^h"Z5B*\phh~}^h"ZB*ph h"Z6h~}^h"Z5OJQJh~}^h"Z6h"Z h"Z5h"ZOJQJh~}^h"Z5 h~}^h"Zh~}^h"ZOJQJ=%L% && ' 'Z'['}'~'((O)P)"*#*U*}*~***** +B+C+-- & Fgd"Z & F gd"Zgd"Z-////000000,1k111118222V3W3e333w45<5 0^`0gd"Zgd"Z11112222V3d3v4w444=5b5 6#66688988888~99990<O<<<<<<<<<<<<!=#=$=%=ĺĺĺ쳨h"Zhr(sh"Z6CJOJPJQJh%kajh%kaUh9 h"Z^JaJ h~}^h"Zh"Z6B*phh~}^h"Z6B*phh~}^h"Z>**ʰ"5B*pʰ"*"*/<5=5c556 6$6I66788888989999:H::;H;_;};;/<gd"Z 0^`0gd"Z/<0<O<h<}<<<<<<<<<<<<<<!="=#=$=%=!!$a$gd"Z 7$8$H$gd"Zgd"Z 0^`0gd"Z.:p"Z/ =!"#$% j%  OJPJQJ_HmH nH sH tH H`H A?Normal CJOJQJ_HaJmH sH tH dd %  Heading 1$$ & F<@&a$5CJ KH PJ\^JaJ `` %  Heading 2$ & F<@&56CJPJ\]^JaJbb 'N Heading 3$ & F<@&5CJOJPJQJ\^JaJbb 'N Heading 4$ & F<@&5CJOJPJQJ\^JaJdd 'N Heading 5 & F<@&$56CJOJPJQJ\]^JaJ^^ 'N Heading 6 & F<@&5CJOJPJQJ\^JaJPP 'N Heading 7 & F<@&OJPJQJ^JVV 'N Heading 8 & F<@&6OJPJQJ]^JX X 'N Heading 9 & F<@&CJOJPJQJ^JaJDA D Default Paragraph FontRiR Table Normal4 l4a (k ( No List 66  Footnote TextHH Footnote Text Char OJQJaJRR % Heading 1 Char5CJ KH OJPJQJ\aJ T!T % Heading 2 Char 56CJOJPJQJ\]aJR1R 'NHeading 3 Char5CJOJPJQJ\^JaJRAR 'NHeading 4 Char5CJOJPJQJ\^JaJXQX 'NHeading 5 Char$56CJOJPJQJ\]^JaJRaR 'NHeading 6 Char5CJOJPJQJ\^JaJLqL 'NHeading 7 CharCJOJPJQJ^JaJRR 'NHeading 8 Char6CJOJPJQJ]^JaJLL  'NHeading 9 CharCJOJPJQJ^JaJLL  L&0 Balloon TextCJOJPJQJ^JaJJJ L&0Balloon Text CharCJOJQJaJh@h L& Colorful List - Accent 1 ^m$OJPJQJ^JB'B L&0Comment ReferenceCJaJHH L&0 Comment TextCJOJQJ^JaJ>> L&0Comment Text Char^JTT L&0Balloon Text Char1CJOJPJQJ^JaJD@D "L&Header ! 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