Workshop sessions will be held from 8:30 AM through 4:30 PM each day. The contents of the sessions are described below.
The workshop outline is based on the recommendations contained in the GAISE College Report (www.amstat.org/education/gaise).
Day 1: Statistical thinking and conceptual understanding
What is statistical thinking? What big concepts do you want your students to take away from a first statistics course? How do we use the GAISE guidelines? On the first day of the workshop we'll share experiences in introductory courses and recommendations for the concepts and content in the first course.
Day 2: Finding and using real data
It can be difficult to identify sources of real data for use in introductory courses. We'll share collections of real data, strategies for finding more real data, and approaches to incorporating real data into the course. We will also present our experiences with service learning in statistics course.
Day 3: Getting away from formulas and fostering active learning
Many believe that students learn and retain concepts better when they are actively engaged. We'll discuss the role of formulas and interactive activities in the first course. We'll emphasize resources available on the CAUSEweb.org site, including those contributed and refereed.
Day 4: Assessment of student learning
All of our best efforts to teach statistics mean little if the students don't learn the material better. We will describe research and resources for assessing student understanding of the concepts in introductory statistics. Our focus will be on the resources available through Assessment Resource Tools for Improving Statistical Thinking (ARTIST). This comprehensive Web resource includes an assessment builder and extensive resources for creating authentic assessments.
Evening: WORKSHOP BANQUET!
Day 5: The role of technology in introductory statistics
We will be using different technologies throughout the workshop, but we need to consider the broad role of technology. Can we rethink how technology relates to the concepts vital to understanding and application of introductory statistics? Technology has already changed the way most of us teach statistics, but logistical constraints often prevent using the full potential of technology. We'll share a variety of resources and experiences for incorporating technology into a first statistics course for the benefit of students.