Program in Course Redesign

Penn State University

Project Abstract

Penn State plans to redesign its introductory Statistics course, which is required for undergraduate students in about 60 different majors At the University Park campus, the course has an annual enrollment of about 2,200 An additional 400 students are enrolled each year at the university's 20 other campuses Currently, students attend three one-hour lectures and two one-hour recitation meetings per week. The lectures are given to groups of about 240 students by experienced full-time faculty. The recitation meetings are conducted in sections of about 40 students and are taught by twelve graduate teaching assistants each semester.

The course suffers from several academic problems. Lectures and recitation sections are large and relatively impersonal They do not address the broad range of differences in student learning styles and quantitative skills. The present format does not encourage active participation nor does it offer much opportunity for hands-on experience with data analysis and collection. The current course structure also relies heavily on teaching assistants who often have undergraduate degrees in general math or science fields, limiting the effectiveness of the statistics instruction they can provide. Finally, the present course does not provide adequate tutoring assistance for students; consequently, students receive little individual attention. During the past academic year about 15% of the students performed very poorly, earning D's (4%), F's (6.5%), or W's (late drops, 4.5%).

The course redesign involves reducing lectures from three to one per week, changing traditional recitation sections to computer-mediated workshops, adding technology-based independent learning materials and computerized testing, and shifting instructional roles from information presentation to learning facilitation. The redesigned course will use interactive, Web-based materials and computerized, low-stakes quizzing to give students needed practice and feedback. Technology-based materials will teach statistical concepts interactively An altered format for midterm and final examinations will enable most questions to be computer-graded. Team teaching will reduce individual preparation time for lectures and presentations A combination of instructors, teaching assistants, and undergraduate interns will participate in the computer-based classes, thus enabling faculty to model ways to facilitate learning.

Enabling faculty to have more one-to-one contact with individual students will enhance quality Smaller classes and computer-mediated data workshops will enable faculty to more readily address the different needs of individuals, and students can be challenged according to their own skill levels Active learning will be increased significantly; students will collaborate on course-related problems in class and computer labs. There will be frequent hands-on experience with statistical analysis.

The impact on student learning will be measured in a variety of ways. Student performance on tests, quizzes, and projects from previous semesters of Statistics will be compared with a sample of similar learning artifacts obtained during the project. Focus groups of faculty from other departments will evaluate how well-prepared Statistics students are in their courses requiring statistics knowledge. Student attitudes and preparation for subsequent courses having Statistics as the prerequisite will be measured by pre-, post-, and follow-up tests of statistical concepts Students will also be surveyed to determine their perceptions of how well prepared they were for subsequent courses that had Statistics as a prerequisite.

Redesign will result in a 30% reduction of the cost-per-student from about $176 to $123 This translates to annual savings of at least $116,600.

Back

 

Program in Course Redesign Quick Links:

Program In Course Redesign Main Page...

Lessons Learned:
Round 1...
Round II...
Round III...

Savings:
Round I...
Round II...
Round III...

Project Descriptions:
Sorted by Discipline...
Sorted by Model...
Sorted by Success...
Sorted by Grant Rounds...