|Program in Course Redesign
The Ohio State University
The Ohio State University (OSU) is engaged in a second-generation redesign of Introductory Statistical Concepts, a five-credit course enrolling 2850 students on the main campus each year plus 400 students on several branch campuses. A 1990 redesign retained three lectures per week and replaced two recitations with an active learning laboratory environment emphasizing hands-on experiments, group activities and real-world examples. Increased learning was, however, accompanied by increased costs due to numerous course inefficiencies, all of which will be addressed in the new redesign.
The redesign will tackle the following problems. Faculty use their time inefficiently in parallel, duplicative, poorly attended lectures. TA time is allocated in bursts: intensive grading and office hours just prior to an exam, coupled with unused office hours at other times during the quarter. A course coordinator responds to 150 emails per week, often answering redundant questions. These inefficiencies are compounded when 20% of the students must repeat the course in a subsequent quarter even though most have satisfactorily completed initial course units. Most importantly, students with highly variable learning styles and study skills are inefficiently served by a single "fixed-menu" course delivery strategy.
OSU will implement a "buffet" strategy, offering students a choice of interchangeable paths to learn each course objective in the framework of a four-stage learning model: 1) familiar example, 2) alternate context, 3) general principle, and 4) hands-on practice. The "buffet" will include lectures (reduced by more than half), individual discovery laboratories (in-class and Web-based), team/group discovery laboratories, individual and group review (both live and remote), small group study sessions, videos, remedial/pre-requisite/procedure training modules, contacts for study groups, oral and written presentations, active large group problem solving, homework assignments (TA graded or self-graded), and individual and group projects. To promote student commitment to follow-through and to enable efficient tracking of their progress, students will enter into an online "contract" at the beginning of each unit that captures their choice of learning modes.
OSU will also modularize course content, allowing students to earn from one to five credits based on successful module completion. Thus, the several hundred students who now fall behind and feel compelled to withdraw will have the option of demonstrating proficiency without having to drop a full five credits. By requiring students to demonstrate a passing level proficiency in one unit before proceeding to the next, severe deficiencies will be identified and addressed early, resulting in a lower failure/withdrawal rate. Analysis of previous data on drops shows that OSU will be able to eliminate one-fourth of the course repetitions, thereby opening slots for an additional 150 students per year.
Other course innovations include offloading assignment grading to course software; replacing office hours with facilitated group study sessions; creating a "statistics help desk" using a tech support model; identifying "customer service" issues to improve responses to individual student needs; and instituting a multi-level certification process for TAs that rewards them with cash bonuses and more assignment choice as they progress from one level of certification to the next.
Ohio State's assessment plan will involve both "before-after" comparisons of student mastery of statistics concepts and the investigation of differential outcomes for different "buffet" choices. As a result, it will collect summative data on effectiveness and provide considerable information about the interaction between student characteristics and specific aspects of instructional provision. Because the department has already established and benchmarked learning outcomes for statistics concepts in considerable detail and uses common exercises to operationalize these concepts, the basis of comparison is clear. The course team will also follow students to and beyond graduation to examine how well they retain key statistical concepts
OSU's redesign will reduce the cost-per-student at the main campus from $190 to $132, a 31% reduction. By modularizing the course, the university anticipates additional savings as a result of improved retention, producing a total annual savings of $194,554. Savings will be used primarily to reduce faculty teaching loads which are high in comparison to OSU's benchmark institutions as well as to reinvest some of the savings into the redesign of business statistics and statistical methods courses to create both improvements in the undergraduate program and increased savings.
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