Center for Teaching Statistics Seminar
May 29, 4-5pm
MS 5137

Phillip Stark
Professor, Dept. of Statistics, University of California, Berkeley

Writing and Teaching for SticiGui, an Online Set of Materials for Teaching Statistics

 I will describe my experience writing and teaching from SticiGui, an online set of materials  for teaching Statistics.  These materials are  comprised of 186 XHTML files containing about 108,000 lines of XHTML  and JavaScript,  65 Java classes containing about 16,000 lines of code, 16 JavaScript
libraries containing about 5,000 lines of code, 34 data files containing about 5,000 records, a cascading style sheet with about 400 lines, and a handful of .jpg and .gif files. I
use the materials to teach introductory classes, including Berkeley's first online course.

Using XHTML with Java, JavaScript and CSS allowed me to make the content dynamic: many examples and exercises change whenever the page is reloaded, so
students can get unlimited practice at certain kinds of problems. Each student gets a different version of each assignment, but can see the solutions to his/her version after the due date. Automation makes it easy to use mastery-based assessment: students can submit each assignment up to 5 times.  Only the last submission counts.  A student has to get a score of 85% or higher to "pass" the assignment, with a bonus for scoring 100%.  This helps assignments function better as learning tools instead of just yardsticks.

Bio
Philip B. Stark is professor of Statistics, University of California, Berkeley. He taught Berkeley's first online course: an introductory Statistics course for business and economics majors in summer 2007.  His research focuses on inference in nonparametric problems, with applications ranging from cosmology to earthquake prediction, hearing, Internet content filtering and election audits.