Statistics Course Redesigns at NCSU Roger Woodard

Statistics Two course redesigns Ohio State –Under original N.C.A.T model. –Funded through Pew grant. –Buffet approach NCSU –Under the radar –No special funding

Statistics A question for you.

Statistics

ST311 Introductory Statistics –700 students per semester –Majors from social and biological sciences –Not for business or engineering Sections –Taught by graduate students –10 to 12 per semester –65 students per section

Statistics Previous structure No formal training –Mentored by course coordinator in informal way Common text but syllabus only loosely coordinated –Time on topics varied greatly

Statistics Problems Instructors did not know what to emphasize –Concepts of the material not clear. –Amount of content varied greatly. Amount of work varied greatly –Students –Instructors Grade distributions varied Complaints were heavy

Statistics Redesign Goals –Improve consistency of the course grading and experience. –Improve the experience of graduate instructors teaching the course.

Statistics Improved Experience Reduce the amount of time graduate instructors spend on teaching the course, especially those elements that are primarily administrative. Provide a support network to deal with teaching and administrative issues.

Statistics Learning Experience Teaching should be a learning experience –Graduate students should be equipped to teach their own class –Substantial experience teaching the course Time commitment should not be excessive –Keep workload comparable to other assignments –Instructors concentrate on the big issues of how to teach the material

Statistics Learning Experience Instructors should make their own lectures –Not just teach from preset notes or slides –Let them think more deeply about the material –Let them find the way to present the material that works best for them. Instructors make up their own midterm exams –Get the experience of making exams

Statistics Minimize Time for Grad Instructors Remove mundane tasks that take a lot of time Homework –Common across sections with same due dates –WebAssign, online homework system: Automatically graded, immediate feedback –Well tested Coordinated administrative paperwork –Equalize size of sections: coordinated add/drop –Coordinate completion of incompletes

Statistics Minimize Time for Grad Instructors Common makeup exams –Reduction of instructor time –Online form Common final exam –Reduce time during final exams –Uniform grading

Statistics How do we know what to teach? “What should I teach about _____?” “How do I know what is going to be on the final?”

Statistics Key components Detailed learning objectiveslearning objectives –Over 100 task level items –Spell out exact content for instructors and students. Faculty to faculty communication

Statistics Key components Coordinated office hours –35 hours per week: maximum service for students –Each instructor and grader does only 3 hours Detailed Study guides for students –Based on learning objectives –Readings, activities, practice problems

Statistics Training Program Initial workshop –Two days prior to the beginning of the semester –Intensive training –Presentation skills –Course/classroom technology –Overview of the course content –Administrative issues (FERPA, ADA, etc)

Statistics Ongoing training Weekly meetings –Administrative issues (upcoming events, clarification of policies, etc). –Just-in-time discussion of upcoming topics –Content, activities, data sets Observation –Videotaped observation –Self reflection

Statistics Results Overall improvement in evaluations –Still varies based on instructor talent Defendable grade distributions –Fair! Self reported time on task –Comparable but still varied based on instructor

Statistics Advice Address the big problems Take small steps Communicate –with the team –with the students

Statistics

Learning Objectives Given a study, identify population, sample, parameter, sampling frame and statistic. Given a study, recognize typical forms of biases such as potential undercoverage, nonresponse, and response bias. Given side-by-side boxplots, contrast key features of the groups represented by the boxplots. Given a study, interpret the results of a test of significance in context.