In this booster, we discuss basic algebra. Topics covered include: variables, equations, order of operations, substitution, algebraic expressions and laws. These files are SCORM packages and can be easily uploaded to your Learning Management System (LMS), such as Blackboard or Desire2Learn. If you want to view or use the files without an LMS, download the files to your computer, extract (unzip) the file, open the extracted folder, and click to open the story.html file. The booster or test will open in your browser window. If used on your LMS, for the booster, the user will be given a score of complete or incomplete; for the pre and post-tests, the user will be given a numerical score. This scoring functionality and completion data is only available if used on an LMS. The SCORM packages are complete and not available for editing. If you would like to include additional information, consider adding the content before or after the booster on your LMS.


Basic Math 1 (Fractions and Reciprocals)

Basic Math II (Number Formats and Order of Operations)

Introduction to Algebra (Like Terms and Algebraic Expressions)

Solving Simple Equations (Solving Equations, Variables, Formula Rearrangement)

Geometry (Pythagorean Theorem and Common Shapes)

MAT 111: College Trigonometry - Module 1: Trigonometric Functions, Module 2: Graphs of Trigonometric Functions, Module 3: Analytic Trigonometry, Module 4: Oblique Triangles, Module 5: Polar Coordinates, Module 6: Conic Sections

MTH 245 - Math for Biological, Management, Social Science This is a survey course of discrete mathematics for non-physical science majors. Topics include systems of inequalities, linear programming, probability and probability distributions, and an introduction to descriptive statistics. The course emphasizes problem solving through the use of computer spreadsheets. Course Outcomes: 1. Identify and solve linear programming problems. 2. Write and analyze algebraic models for business and other applications. 3. Solve business and biological applications using probability distributions.