Work in progress: Redesigning a multidisciplinary engineering statistics course

Abstract

Over time, the evolution of academic programs can place new constraints on courses that could not be envisioned when a course was originally designed. This may be especially true for multidisciplinary courses where additional constraints due to changing accreditation requirements, new programs adopting a course, and the shifting emphases of academic programs likely occur more frequently than in many program-specific courses. For example, a new program may require a certain topic (e.g., discrete probability distributions) to be emphasized more than the current programs, which may in-turn de-emphasize the instruction of other course topics. A logical result is that, over time, any attempt to change how a course is taught will be met with resistance from the course's stakeholders. In a worst-case scenario, the constraints could become so numerous, interdependent, and complex that more effort is expended maintaining the status quo than is spent on improving and adapting the course's content, instructional methods, and outcomes to a changing world. In this work-in-process paper, we will outline our initial work for a two to three-year effort to redesign a multidisciplinary, lab-based, engineering statistics course at a large public university. The course was originally designed nearly 20 years ago for the college's Industrial Engineering program and today serves six programs and approximately 25% of the college's undergraduate students. The timing of this effort coincides with an ever-increasing interest in data science and analytics, and a larger effort to restructure the university's longstanding general education requirements. Our work completed to-date consists of initial efforts to understand the course's constraints stemming from topical coverage, understand stakeholder requirements and preferences, understand student views about the course, and establish a general vision for the future. In this paper, we focus on student views and opportunities to enhance instructional methods to improve student engagement and discuss considerations for assessing student learning. We also outline our larger vision for the course as it relates to students' understanding of statistics and the potential for the course to play a role in the university's general education program.