Enhancing Purposeful Learning in an Online Course Through the Use of Problem Solving Strategies and Real Life Applications

Concurrent Session 7

Session Materials

Brief Abstract

Learn how UMUC is incorporating a problem-solving approach and real life applications of concepts in a new statistics pathway alternative to college-level algebra using open educational resources. The goal is to increase transferability of career-relevant skills by enhancing both metacognition and relevancy of mathematical concepts to solving novel problems.


Dr. Coleman-Seiffert is a Collegiate Professor of Statistics, who has taught in University of Maryland University College's (UMUC) Stateside and Europe divisions. A frequent contributor to curriculum design and redesign projects, she taught pilot courses using Carnegie Mellon’s Open Learning Initiative courseware and is leading the effort to redesign the undergraduate introductory statistics course.

Extended Abstract

There are many challenges in teaching mathematics and statistics courses. The first major challenge is helping students to develop overarching critical thinking skills, where students do not focus on just solving a given problem. Rather, it is important to teach students “to think about how to think” about solving mathematical and/or statistical problems or, in other words, metacognition. Teaching students  “how to think about thinking” provides them with skills that are transferable beyond a single problem or concept area; instead, it enables students to have a strategy for approaching new problems.


Another challenge is to increase relevancy of course material to future endeavors, particularly for adult learners for whom high-school math is a distant memory. For many students there is a disconnect between math course content and the math skills that they may need to be successful. The state of Maryland recently revised the general education requirements for college-level math to include a broader focus on quantitative reasoning, reflecting the twenty-first century knowledge and skills that students need to succeed in college and in the workplace. There is a growing recognition that quantitative literacy and statistics may be more career-relevant skills for some disciplines than the traditional college-level algebra pathway that may not fit all students, particularly those in non-STEM fields.


UMUC, whose students are primarily online, adult learners, created a Mathematical Foundations course as a participating partner in a statewide Maryland Mathematics Reform Initiative (MMRI), to develop and evaluate a high-quality statistics pathway transferable through statewide articulation agreements with the goal of preparing students for statistics in lieu of a college-level algebra requirement for some majors. The course was co-designed by a mathematics faculty member and a statistics faculty member and informed by a needs analysis from all of the departments that required introductory statistics as part of their major programs. Both quantitative and qualitative information were collected and analyzed. The results indicated a need for more emphasis on statistical reasoning and interpretation skills, use of technology, and real world applications.


The new mathematics course helps students to develop quantitative literacy skills by having them think about the entire process of solving a problem, including the question being asked, the appropriate method for solving the problem, and interpretation of the results in light of the data provided and the context of the question. The problem-solving approach and real life applications incorporated in the course will help provide students with the foundation they need for the redesigned statistics course.

The course utilizes OERs and specially designed learning resources:

  • Open Source textbook chapters, a chapter written for the course, and chapters from a text written by a UMUC faculty member for another mathematics course.

  • Online Applets for:

    • Graphing equations (DESMOS calculator)

    • Creating graphs used in descriptive statistics (i.e., bar chart, pie chart, etc.)

    • Calculating basic statistics (i.e., measures of central tendency and measures of variability)

  • Problem-solving model designed and incorporated into course content area.

  • Applications designed using real data. Created scenarios to fit data and mesh with majors (i.e., business, healthcare management, etc.).

Participants in the session will have the opportunity to be guided through applying a problem-solving model to a business application problem and then share their insights about the process. The goal of the activity will be for participants to experience the difference between using a traditional approach to solving a straight skill set problem, such as dividing fractions, and a problem-solving method that uses a real life application.


For example, by providing a scenario students may encounter in a professional setting, problem solving skills applied in a specific context may enhance transferability of those skills to different situations. An example scenario in the course has students identifying new markets by using demographic data and calculating growth percentages over time.


We plan to share preliminary data, including qualitative feedback from students about their experience and student performance in the traditional vs. new pathway into statistics.