College of Science

Transition to College Level Mathematics 12th Grade Course

Transition to College Mathematics Course and Professional Development

This course and accompanying professional development were developed by a team of Mathematics and Mathematics Education faculty members from California State University, Hartnell College and several school districts in Monterey County and in collaboration with the Monterey County Office of Education. The project was funded by a grant to California State University Monterey Bay from the California Department of Education as part of the California Mathematics Readiness Challenge Initiative.

The Transition to College Level Mathematics course is intended for high school seniors, as a fourth year mathematics course, for students who would like to continue mathematics, but do not currently want to pursue the pre-calculus, calculus pathway. When students enter college after completing this course they will be well positioned to take a variety of college level courses including: Pre-calculus, Statistics, Discrete Mathematics, or Quantitative Reasoning.

Course Overview

Transition to College Level Mathematics serves any student who has successfully completed Integrated Math 3 or Algebra 2 and emphasizes modeling, problem solving and applications of mathematics to the real world. Students learn new concepts as well as develop a deeper understanding of previous concepts and relationships between them. The course requires students to justify and explain their thinking and work in groups. CCSS-M mathematical practices 4: Modeling with Mathematics; and 1: Make Sense of Problems and Persevere in Solving Them, are accentuated, but all eight mathematical practices are developed and applied throughout the course.

Sections	Units
Data in the Real World	Modeling Change with Functions: Families of functions including linear, polynomial and exponential.
	Interpreting Categorical Data: Introduction to probability, two-way frequency tables, conditional probability and independence.
	Statistical Inference: Rules of probability and applications of analysis of data.
Decision Making in the Real World	Voting and Apportionment: Decision-making relative to voting
	Financial & Business Decision Making: Financial mathematical models.
Computing	Counting Methods: Rules of counting including permutations and combinations
	Graph Theory: Applications
	Informatics: Information processing with a focus on security, access and efficiency
Geometry in the Real World	3-D Representations: Visualizing and representing three-dimensional shapes
	Symmetries and Tilings: Study of patterns of geometric figures in the plane including tessellations, symmetry and frieze patterns