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Webinars

  • Reviewing and Writing for the Journal of Statistics Education (JSE)

    John Gabrosek, Grand Valley State University
    Tuesday, July 12, 2011 - 2:00pm
    The Journal of Statistics Education (JSE) is a leading journal for the dissemination of knowledge for the improvement of statistics education at all levels, including elementary, secondary, post-secondary, post-graduate, continuing, and workplace education. Current JSE Editor John Gabrosek will discuss how JSE handles submissions. Discussion will include guidelines and tips for writing papers for JSE and for reviewing papers as a JSE referee or Associate Editor.
  • Create an Iron Chef in statistics classes?

    Rebekah Isaak, Laura Le, Laura Ziegler, and the CATALST Team
    Tuesday, June 14, 2011 - 2:00pm
    This webinar provides an overview of the research foundations of a radically different introductory statistics course: the CATALST course. This course teaches students the skills they need in order to truly cook with statistics, not just the procedures they need in order to follow a statistical recipe. In addition to the research foundations of the course, we will describe unique aspects of this course as well as details of a one-year teaching experiment to learn how this course can be taught and its impact on student learning.
  • Is Stats 101 prepared for the CC Student?

    Jerry Moreno, John Carroll University
    Tuesday, May 10, 2011 - 2:00pm
    Forty-three states have signed on to the mathematics part of the Common Core State Standards (CC). Statistics and Probability play a prominent part in CC grades 6-11 for all students. How may Stats 101 have to change to accommodate potentially better prepared quantitatively literate students?
  • Eat Less Salt, Drink More Wine, Dump The Cellphone, Eat More Salt, And Live Longer: Teaching Students To Understand The Role Of Data Collection In Statistical Inference

    Rob Gould, UCLA
    Tuesday, April 12, 2011 - 2:00pm
    The role that data collection plays in causal inference is of fundamental importance in introductory statistics, and yet is outside the comfort zone for many of us. In this webinar, I'll discuss why causal inference is important and also fun, and give some advice for teaching this topic.
  • To Teach Statistical Inference, Try Standing On Your Head

    Cliff Konold, Director, Scientific Reasoning Research Institute, University of Massachusetts Amherst
    Tuesday, March 8, 2011 - 2:00pm
    Generally in learning statistical inference, students reason backwards from data to the (usually invisible) process that produced them. I will demonstrate an alternative approach in which students begin at the process end, designing their own "data factories." Based on their output, students modify their factories such that, for example, a collection of cats produced by a cat factory has features that look more like real cats. This work is part of the NSF-funded "Model Chance" project. In this project, we have been adding probability modeling to the existing data-visualization capabilities of TinkerPlots and, using that environment, exploring how data and chance might be better integrated in our instruction beginning in the middle school.
  • Building a Statway to Heaven

    Uri Treisman, Director, Charles Dana Center, University of Texas at Austin
    Tuesday, February 8, 2011 - 2:00pm
    Developmental education in America's community colleges has been a burial ground for the aspirations of our students seeking to improve their lives through education. Under the leadership for the Carnegie Foundation for the Advancement of Teaching and the Charles A. Dana Center, nineteen community colleges and systems are building accelerated pathways to and through developmental education with the goal of helping students with low levels of mathematical preparation complete a college credit bearing, transferable statistics course within one year. Uri will describe the work to date, the challenges the initiative faces, and the underlying ideas of improvement science that are driving its development.
  • Introducing Informal Inference Using Data-Centric Lab Exercises

    Rakhee Patel, UCLA
    Tuesday, January 11, 2011 - 2:00pm
    Since formal hypothesis testing and inference methods can be a challenging topic for students to tackle, introducing informal inference early in a course is a useful way of helping students understand the concept of a null distribution and how to make decisions about whether to reject it. We will present two computer labs, both using Fathom, that illustrate these concepts using permutation in a setting where students will be answering interesting investigative questions with real data.
  • Facilitating Student Projects in Statistics

    Dianna Spence & Brad Bailey, North Georgia College & State University
    Tuesday, December 14, 2010 - 2:00pm
    When instructors have their students implement "real-world" projects in statistics, a number of questions arise: Where can students locate real data to analyze? What kinds of meaningful research questions can we help students to formulate? What aspects of statistical research can be covered in a project? What are reasonable methods for evaluating the student's work? The presenters will share resources developed during an NSF-funded study to develop and test curriculum materials for student projects in statistics, using linear regression and t-test scenarios.
  • Over the HILS: Learned Helplessness in Statistical Instruction

    Brandon Vaughn, University of Texas
    Wednesday, December 8, 2010 - 2:00pm
    Some students in statistics classes exhibit behaviors that share characteristics with the established construct of learned helplessness. This webinar will discuss this phenomenon, and detail an instrument recently developed which measures this (HILS: Helplessness in Learning Statistics).
  • Developing a Statistics Teaching and Beliefs Survey

    Jiyoon Park & Audbjorg Bjornsdottir, University of Minnesota
    Tuesday, November 9, 2010 - 2:00pm
    This webinar presents the development of a new instrument designed to assess the practices and beliefs of teachers of introductory statistics courses. The Statistics Teaching Inventory (STI) was developed to be used as a national survey to assess changes in teaching over time as well as for use in evaluating professional development activities. We will describe the instrument and the validation process, and invite comments and suggestions about its content and potential use in research and evaluation studies.

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