Ivo Dinov, UCLA; Dennis Pearl, Ohio State; and Kyle Siegrist, University of Alabama
Tuesday, November 27, 2012 - 2:30pm ET
There is a need for modern, efficient, and engaging pedagogical techniques for enhancing the teaching of probability theory, and its applications, that leave lasting impressions on learners. The Probability Distributome project has developed portable, browser-accessible and extensible resources including:
Computing probability and critical values for a wide array of distributions
Exploring probability distribution properties and inter-distributional relations
Fitting probability distribution models to data
Virtual resampling and simulation experiments
Integrated data, web-applications and learning-activities
We will show some of the Distributome web-resources and discuss best practices for integrating these tools, web-applications, activities and learning materials in probability and statistics curricula.
Marsha Lovett, Carnegie Mellon University; and Oded Meyer, Georgetown University
Tuesday, October 9, 2012 - 2:00pm ET
As part of the Open Learning Initiative (OLI), Carnegie Mellon University was funded to develop a web-based introductory statistics course, openly and freely available to individual online students so they could learn effectively without an instructor. In practice, this course is often used in "blended" mode, i.e., to complement face-to-face classroom instruction. In this webinar, we will demonstrate how students interact with the course and how the different activities were designed to provide pedagogical scaffolding. We will then discuss ways in which instructors have used the online course to support their teaching and provide a demonstration of the Instructor's Learning Dashboard, a tool which continuously provides detailed feedback on students' learning and progress. We will conclude by summarizing a set of studies in which we assessed the online course's effectiveness in blended mode.
Unfortunately, this webinar was not recorded due to a technical problem. We apologize.
Alison Gibbs, University of Toronto
Tuesday, September 25, 2012 - 2:30pm ET
In this webinar I'll give a nuts-and-bolts description of a fourth year capstone activity for students in statistics programs at the University of Toronto. The statistics students join research students from other disciplines as collaborators. I'll describe what takes place including the nature of the projects and the support provided, how we've structured the course and are evaluating the projects, who are the members of the six distinct groups of individuals at the university who are benefitting from the experience, and why we started the course and organized it the way we did.
Leigh M. Harrell-Williams, Virginia Tech/Georgia State University; M. Alejandra Sorto, Texas State University; Rebecca L. Pierce, Ball State University; Lawrence M. Lesser, The University of Texas at El Paso; Teri J. Murphy, Northern Kentucky University
Tuesday, August 14, 2012 - 2:00pm ET
Do some PreK-12 teachers lack confidence to teach confidence? What are PreK-12 teachers' "Core" beliefs about being able to teach statistics? We will present the development and validation phases of two instruments designed to measure a teacher's self-efficacy to teach statistics: one for middle school grades and one for high school grades. The implementation of the Common Core State Standards has changed the landscape of pre-service teacher education as well as professional development as teachers are called on to teach statistics material that may not have been part of their education. The Self-Efficacy to Teach Statistics (SETS) instruments are aligned with key concepts of the Common Core State Standards for Mathematics (CCSSM) and the PreK-12 GAISE. We will discuss potential and current uses of these instruments, including research, assessment, and analysis of need for professional development programs. This discussion will include the current use of the SETS instruments in research regarding pre-service teachers and in a state-wide professional development program for in-service teachers. At the end of the presentation, we will seek the opportunity to discuss ideas for use of the instruments with audience members, including teacher educators, professional developers, education researchers, and other interested parties.
Jane Oppenlander, Union Graduate College
Tuesday, July 10, 2012 - 2:00pm ET
A pedagogical approach is presented that emphasizes the importance of competence in statistics for a successful business career. Statistical methods are introduced in a framework that stresses problem formulation, application of appropriate statistical techniques, and interpretation of results in the business context. Classroom activities and assignments are designed to motivate students using relevant business problems and data. Statistical methods are connected to concepts from other courses in the business curriculum. Several examples of these applications will be presented during this webinar along with icebreakers for motivating statistical concepts. Finally, future challenges in statistics education in the business curriculum will be discussed.
Jennifer J. Kaplan, University of Georgia
Tuesday, April 24, 2012 - 2:30pm ET
Many ideas and recommendations for meeting the GAISE guidelines at the college level have targeted relatively small class sizes. This webinar will provide an overview of a suite of twelve simulation activities that were designed to develop student conceptual understanding of inference in large lecture classes using personal response systems (clickers) to collect data. Details will be provided for three of the activities, in which each student performs a simulation once using a calculator and the results are collected via clickers. The activities allow students to experience statistical concepts such as distributions or models, variability, and the Central Limit Theorem. The large class, therefore, becomes a learning asset, rather than a liability.
Megan (Meece) Mocko, University of Florida
Tuesday, April 10, 2012 - 2:00pm ET
Teaching several semesters of classes where all students in the class have a learning disability has offered me a unique perspective on how some LD students learn statistics. I have found that some students seem to "see" statistics problems differently than the average student. In this webinar, I will share with you some tips on how to show your LD students how to read statistics problems more effectively to help them overcome their learning disability.
Gina Reed, Gainesville State College
Tuesday, March 27, 2012 - 2:30pm ET
This presentation focuses on how to incorporate a service learning component into introductory statistics. Service-learning is a concrete application of statistical methods using real data with the analysis and interpretation that is useful to a community agency. Discussion will include how to locate an organization, the selection of appropriate content for the project with focus on understanding what questions need to be answered and how to do so, the grading rubric for the presentations or posters and the time line of formative evaluation as the project proceeds.
Robert delMas, University of Minnesota
Monday, March 12, 2012 - 2:15pm ET
The Statistics Education Research Journal (SERJ) publishes high quality research related to the teaching and learning of statistics. Bob delMas, co-Editor of SERJ, will present characteristics of manuscripts that tend to result in published articles, as well as point out critical flaws that can keep a manuscript from being published in SERJ. Ample time will be provided for the audience to ask questions of the co-Editor.
Chris Morrell, Loyola University
Tuesday, February 28, 2012 - 2:30pm ET
In the early 1990's, the National Science Foundation funded many research projects for improving statistical education. Many of these stressed the need for classroom activities that illustrate important issues of designing experiments, generating quality data, fitting models, and performing statistical tests. This webinar describes such an activity on logistic regression that is useful in second applied statistics courses. The activity involves students attempting to toss a ball into a trash can from various distances. The outcome is whether or not students are successful in tossing the ball into the trash can. This activity and the adjoining homework assignments illustrate the binary nature of a response variable, fitting and interpreting simple and multiple logistic regression models, and the use of odds and odds ratios.
Trashball activity website