August 14, 2007 Teaching & Learning webinar presented by Oded Meyer, Carnegie Mellon University, and hosted by Jackie Miller, The Ohio State University. Carnegie Mellon University was funded to develop a "stand-alone" web-based introductory statistics course, and for several semesters they studied different ways in which the course could be used to support instruction. In this presentation, Dr. Meyer discusses some of the challenges in developing such a learning environment and ways in which the course tries to address them, as well as describing the design and results of accompanying studies.
September 11, 2007 Teaching & Learning webinar presented by Ginger Rowell, Middle Tennessee State University, and hosted by Jackie Miller, The Ohio State University. The Internet is a great source of learning resources to help statistics teachers and students. Examples include interactive applets, videos, tutorials, lesson plans, case studies, and engaging learning activities. This webinar demonstrates how to assess statistics education learning materials based on the peer-review criteria used by digital libraries such as MERLOT and CAUSEweb.
October 9, 2007 Teaching & Learning webinar presented by Norean Sharpe, Babson College, and hosted by Jackie Miller, The Ohio State University. Writing can be a wonderful tool to help illuminate what students are learning in our statistics courses. Examples and strategies to include writing in your teaching toolkit -- and to increase the writing skills of students -- include team assignments, weekly case reports, in-class questions, and others. This webinar shares effective approaches and assignments gleaned from twenty years of experience using writing in introductory and upper-level statistics courses.
December 11, 2007 Teaching and Learning webinar presented by Mark L. Berenson, Montclair State University, and hosted by Jackie Miller, he Ohio State University. As we consider how we might improve our introductory statistics courses, we are constrained by a variety of environmental/logistical and pedagogical issues that must be addressed if we want our students to complete the course saying it was useful, it was relevant and practical, and that it increased their communicational, computational, technological and analytical skills. If not properly considered, such issues may result in the course being considered unsatisfying, incomprehensible, and/or unnecessarily obtuse. This Webinar focuses on key course content concerns that must be addressed and engages participants in discussing resolutions. Participants also had the opportunity to describe and discuss other content barriers to effective statistical pedagogy.
March 11, 2008 Teaching and Learning webinar presented by Deborah Nolan, University of California at Berkeley and hosted by Jackie Miller, The Ohio State University. Computing is an increasingly important element of statistical practice and research. It is an essential tool in our daily work, it shapes the way we think about statistics, and broadens our concept of statistical science. Although many agree that there should be more computing in the statistics curriculum and that statistics students need to be more computationally capable and literate, it can be difficult to determine how the curriculum should change because computing has many dimensions. In this webinar Dr. Nolan explores alternatives to teaching statistics that include innovations in data technologies, modern statistical methods, and a variety of computing skills that will enable our students to become active and engaged participants in scientific discovery.
April 8, 2008 Teaching and Learning webinar presented by Beth Chance and Allan Rossman, Cal Poly - San Luis Obispo and hosted by Jackie Miller, The Ohio State University. Math majors, and other mathematically inclined students, have typically been introduced to statistics through courses in probability and mathematical statistics. We worry that such a course sequence presents mathematical aspects of statistics without emphasizing applications and the larger reasoning process of statistical investigations. This webinar describes and discusses a data-centered course that we have developed for mathematically inclined undergraduates.