College Prep’s math program is problem based and student centered.
Using an approach that integrates the traditional areas of mathematics—algebra, geometry, trigonometry, pre-calculus, and calculus—throughout six sequential levels of study, students become independent learners who excel in reading, writing about, exploring, applying, and communicating mathematical concepts.
College Prep’s computer science offerings focus on hands-on skill acquisition for the modern world of programming and design. The program offers a full scope and sequence suitable for students with skills from entry-level to advanced.
The math curriculum is structured around these principles:
Algebra is foundational as a modeling and problem-solving tool
Geometry in two and three dimensions is integrated across topics at all levels and includes coordinate and transformational approaches
The study of vectors, matrices, counting, data analysis, and other topics from discrete mathematics is woven into core courses
Computer-based and calculator-based activities are part of core courses
Topics are explored visually, symbolically, and verbally
The capacity to develop problem-solving strategies depends on an accumulated body of knowledge
These principles are addressed in the integrated curricula of Math 1-6. Math 3, 4, and 5 are each offered at two levels that showcase different teaching and learning styles. The standard classes feature more direct teacher instruction and cover fewer topics. The “i” versions of each course cover more topics at a faster pace and students work more independently. Both levels require collaboration in the form of daily group work among four tablemates. The program also offers opportunities for advanced work, including AP Statistics, Math 5/5i, and Math 6. Math 5/5i prepares students for either the AP Calculus AB or BC exam while Math 6 covers multivariable calculus. Math Club, open to all interested students, meets regularly to share ideas and investigate problems beyond the scope of the normal curriculum and to help students prepare for local and national math competitions.
A placement test is used to determine the appropriate level of math for each incoming student. Math support is available via the Math & Science Academic Support Specialist as well as from teachers in the Math Office and peer tutors via the Math Squad.
This course includes topics from algebra, geometry, and trigonometry. Students learn techniques and theorems through problem solving. Collaborative study helps develop the ability to reflect on and explain mathematical processes. Topics include lines, polygons and vectors, circles and parabolas, and right triangle trigonometry. Similarity and congruence are studied through the lens of transformations. An investigation of linear motion leads to the use of parameters and consideration of optimal paths of travel.
This course develops foundational problem-solving skills, the translation of prose into mathematical equations and diagrams, oral and written presentations of mathematical processes, and mathematical intuition. Topics from algebra and geometry are integrated and include conversions and rates, proportional reasoning, area and perimeter, linear and quadratic equations, inequalities, and coordinate geometry. An emphasis on algebra skills supports problem solving.
These courses explore nonlinear motion and nonlinear functions: circular motion and the functions that describe it, ellipses and hyperbolas, exponential and logarithmic functions, dot products and matrices, and geometry on the surface of the earth. Advanced trigonometric techniques recur throughout the year. Logarithms are used to straighten nonlinear data, and matrices are used to describe geometric transformations and various patterns of growth.
These courses build on the foundation of function and trigonometry and continue into introductory calculus. Analysis topics include sequences and series, vectors, polar and parametric functions, and complex numbers. Topics from discrete math include combinatorics and probability. Trigonometry topics include sum/difference formulas and trigonometric identities. Vector topics include the dot product and its applications. Calculus topics include limits, first and second derivatives of the basic functions, applications to maxima and minima, and rates of change.
These courses cover differential and integral calculus at the college level. Math 5 covers techniques and applications of derivatives and integrals. It prepares students for the “AB” AP Calculus Exam. Math 5i covers the same material along with additional topics, such as infinite series, differential equations, and recursion. This course prepares students for the “BC” AP Calculus Exam.
This multivariable calculus course extends the concepts of differentiation and integration that were introduced in single variable calculus to functions of more than one variable. Topics include parametric curves, polar coordinates, vectors in two- and three-dimensions, partial derivatives, the gradient, optimization in more than one variable, line integrals, multiple integrals, and the theorems of Green, Stokes, and Gauss (the divergence theorem). This course also covers first order differential equations, second order constant coefficient linear equations, Fourier series, and Laplace transform.
Statistics is the art and science of collecting, organizing, analyzing, and drawing conclusions from data. This course focuses on four major themes: exploratory data analysis, designing studies, probability models and simulation, and statistical inference. Students design, administer, and tabulate results from surveys and experiments. Sampling distributions provide the logical structure for confidence intervals and hypothesis tests. Students use a TI-83/84 graphing calculator, JMP statistical software, and web-based Java applets to investigate statistical concepts. This course is recommended for those interested in any field that uses data, including the sciences, engineering, social sciences, or business studies.
College Prep offers Computer Science courses from beginning through advanced levels. The introductory course (CS1) is a deep dive into programming, developing proficiency in a single language (Python), and building a foundation in the general constructs of programming languages. In the department’s intermediate-level, project-based course (CS2), students apply their programming skills to build embedded system prototypes using microcontrollers—such as Arduinos and Raspberry Pis, sensors, and other electronics. The advanced course (CS3) focusses on data science, analysis, and modeling in Python.
In this course students demystify how computers work, learn how data can be manipulated and moved around the world, and gain basic proficiency in a programming language. A variety of topics and skills are introduced through classroom discussions and hands-on labs and projects. The course uses Python as the primary language to gain a foundational framework of what programming is and how it works. Students showcase their skills through a series of collaborative and creative projects.
Using the Python language, this course focuses on fundamental concepts of computer programming: abstraction, algorithms, efficiency, and data manipulation. Its simplicity and readability makes Python an ideal first programming language, and its versatility makes it an excellent choice for a wide variety of applications. Topics include the variables used in programming, Boolean logic and the use of conditional statements to control the flow of a program, and loops and how to apply recursion to solve problems. Students use functions to perform tasks that break a complex problem into smaller pieces that are easier to solve. The course introduces object-oriented programming in which students learn how to use objects and classes to provide a clear structure to their code that makes it easier to read, understand, and debug. Coding skills are honed on a series of individual and group projects. As a final project, students work in groups to design and create their own text adventure game.
This course equips students with the tools and skills of a data scientist using the Python programming language. Students learn how to collect and clean raw data, explore different data visualization tools that make it easier to see and understand trends, and learn to analyze their data, transforming and modeling it to draw conclusions and inform decision-making.
This project-based course is for students interested in learning how to build things. The course focuses on mechatronics: the intersection of mechanical and electrical engineering and begins with the elements of design thinking. No design is perfect the first time; students learn from their mistakes and from observing the users of their designs. Students work on mini-projects that build in complexity throughout the semester. The goal of the early individual projects is building skills using the tools of the xLab, learning basic electronics, and how to program the Arduino micro-controller. Many of the projects are centered on the Arduino—learning to tie together various input devices (e.g., switches, light sensors, temperature sensors, distance sensors, etc.) and output devices (e.g., motors, speakers, LEDs, LCDs, etc.). As students gain proficiency, projects become more open-ended and group-oriented and include regular design critiques to improve each iteration of a project as well as to share knowledge.
List of 9 members.
Kevin Wray
Math Teacher
510-652-0111 x 234
Francis Frederick
Math Teacher
510-652-0111 x234
Max Hukill 17
Math Teacher
510-652-0111 x234
Cliff Kao
Math Teacher
510-652-0111 x234
Minh Nguyen
Math Teacher
510-652-0111 x 234
Norm Prokup
Math /Computer Science Teacher
510-652-0111 x234
Margot Schou
Math Teacher
510-652-0111 x234
Cuong Ta
Math Teacher
510.652.0111 x234
Gretchen Verner
Math Teacher
510-652-0111 x234
I’ve wanted to be a math teacher since I was in high school. Math is sometimes thought to be a solemn subject, but I always look for unexpected moments that will captivate the students, or make them laugh. It resets the classroom and it is engaging for all of us.”