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About the course


To provide an accessible venue to support participants in preparing for credit-bearing mathematics course.

Leadership team

  • If you have any questions, contact the  Math MOOC Team.
  • Jennifer Kosiak is a Professor of Mathematics since 2004 specializing in Mathematics Education. In 2010, she won the prestigious Teacher Educator of the Year Award from the Student Wisconsin Education Association. In 2012, she won the 2012 Regents Teaching Excellence Award.

Target learners

There are many groups who will be attracted to this course, and efforts will be made to reach out to each.

  • High school students. The Wisconsin Early Mathematics Placement Tool (EMPT) is sponsored by the University of Wisconsin System, the Wisconsin Technical College System, and the Wisconsin Department of Public Instruction. This tool is designed to allow high school students to assess their current readiness to pursue math courses at the post secondary level. Thousands of students use this tool each year.
  • Students within the University System who are required to take remedial math courses to prepare for college credit bearing math and science courses.
  • Individuals who have been away from formal instruction and who are interested in learning mathematics, possibly in preparation to enter or re-enter college or simply to improve their math skills to compete within the workforce.
  • Individuals intending to take a major gateway exam that has a math component (GRE, ACT, SAT, PPST, College Placement, etc.).

There will be no enforced prerequisites. Individuals who are considering enrollment into the course will be allowed access to the syllabus and a pre-diagnostic self assessment quiz, which will help them gauge their readiness for the course and identify the modules that will be of the greatest value.

The proposed MOOC aligns with the on-campus course MTH 051 Intermediate Algebra. As the results of the pilot (discussed below) indicate, success in the course prepares one for placement beyond MTH 051 in the curriculum. UW System maintains a sophisticated transfer matrix that allows students to compare and understand the courses within the System and beyond. In addition, the Wisconsin Early Mathematics Placement Tool site lists the mathematics requirements by major  for each campus, and aligns course prerequisites to their level of performance on the early math placement tool. The proposed MOOC is designed to advance individuals to Level 5, and recent evidence suggests that the course will achieve the design goals.

Design of learning materials

Over the past several years, technology-enhanced materials for mathematics have been developed and tested at the IIURL. The projects involve many UW faculty and undergraduate students, and provide professional development associated with the creation of innovative educational materials packaged as digital Learning Objects (LOs). In the PRAXIS project, for example, the LOs were designed to help pre-service teachers understand and recall key content that appears on the math component of the state licensure examination. An end-product of these initiatives is a tested module design and a growing collection of LOs developed by teams of faculty and students (often pre-service teachers). The process of creating the LOs has shown to increase prospective teachers' mathematics content knowledge, awareness of how students learn mathematics, and the pedagogical understanding of teaching and learning mathematics with technology (Kosiak & LeDocq, 2008). The success of these projects has been well documented and provided the foundation for the FastTrack pilot that followed.

FastTrack pilot project

The pilot involved 38 students in an online course in the summer of 2012. Two components of the Math Placement Exam, Basic Math and Algebra, are used to measure readiness for admission into a UW System institution and its courses. The scores of each student in the pilot indicated a requirement to take one or more remedial mathematics courses prior to entering college level math and science courses. The students spent six weeks working together online studying mathematics, and by all measures, the course was a great success. At the conclusion, the students sat once again for the placement exam (administered through the Counseling and Testing Center). The group scores increased, on average, in the Basic category from 460 to 604, and from 433 to 506 in the Algebra category. Both of these results were found to be statistically significant using a paired t-test (with each p value less than .0001), and perhaps more importantly, all but one of the students were able to improve their placement scores sufficiently to allow them to enter college-level math and science courses. 

Learning Objectives

The desired learning objectives for the course is to increase mathematical proficiency, conceptual understanding, procedural fluency, and logical reasoning in students intending to use mathematics in their future coursework, profession, or day-to-day life. This course aims to increase student success in a rigorous preparation for college-level mathematics, while meeting the needs of students by being efficient through a strong curricular design of online courses. The course consists of 14 algebraic modules covering basic algebra, absolute values and inequalities, linear equations, geometry, systems of linear equations, exponents, polynomials, factoring, solving by factoring, radicals and exponents, rational expressions, quadratic equations, and quadratic functions. Each module provides for measurable, attainable learning outcomes aligned with the Common Core State Standards in Mathematics. For example, a learning outcome under the module Systems of Linear Equations states: Demonstrate an understanding of systems of linear equations, specifically finding solutions through graphing, elimination, or substitution. Utilize these skills in solving word problems. This learning outcome aligns with the following CCSS: 8.EE.C.8a, b, c; A-CED.A.2, A-REI.C.5, A-REI.C.6.

Data will be collected and analyzed to determine which students and from which backgrounds this MOOC is most effective. In addition, the data will be used to identify those components that provide the greatest impact for various learners and seek to identify additional supports that are needed. The study will also analyze the data captured from the MOOC to learn which is most informative and how such data might be best used for the advancement of learning.