Webinars

  • Reading and Writing in an Inquiry-Based Introductory Statistics Course

    Adam Childers & Jeff Spielman, Roanoke College
    Tuesday, September 13, 2011 - 2:00pm ET
    Some of the challenges that we face teaching introductory statistics are the students' fear of mathematics and negative perceptions of the subject that they bring with them as enter the classroom. In an attempt to change these negative associations we have begun teaching theme-based introductory statistics courses that emphasize reading and writing integrated with the usual emphasis on quantitative reasoning. In this presentation we will discuss how using a central theme and incorporating reading and writing has affected both the way we teach the course and the experience that the students have.
  • Using a Paper Ruler Activity to Help Students Understand the Difference Between Random and Systematic Errors

    Jamis Perrett, Texas A&M University
    Tuesday, August 23, 2011 - 2:30pm ET
    Class activities that get students to physically participate in the data collection can be fun for the students, can keep them attentive during class, and can help them remember key concepts. The paper ruler activity is a fun way to solidify students' understanding of the difference between random and systematic errors and the only material needed for the activity is a piece of paper and a pen/pencil.
  • Homework + e-Textbook = Integrated Online Learning

    Brenda Gunderson, University of Michigan
    Tuesday, August 9, 2011 - 2:00pm ET
    Abstract: A homework/e-textbook prototype (lecturebook.com) is being used in a course with >1,500 students. This prototype makes the e-textbook a supplement to the homework. Results show an increase in average grades and an increase of buy-in of the e-textbook option as students appreciate the integration of textbook with tailored homework questions. Description: Students are accustomed to accessing information immediately. So we develop ways to enhance the teaching and incorporate technological methods into all aspects of the students' learning environment. This presentation will share a new online tool (www.lecturebook.com, a new component of www.lecturetools.com), that facilitates creation and grading of homework linked to an electronic version of the course textbook. The idea is to make the e-textbook a supplement to the homework questions. This homework/e-textbook prototype has been used in an introductory statistics course with semester enrollments of over 1500 students since the Fall of 2010. A bank of customized questions has been created and linked directly to e-textbook content. The solutions can be enhanced by the instructor to go beyond just providing the correct answer. Problems are selected and assigned weekly to match content presented in lectures and lab. Students work through the weekly homework online, with direct links to the e-textbook material if questions or a review is needed. The submission of the paperless homework is automatic and set for one common time for all students (no more 'I lost my homework' or 'I forgot to turn in my homework'). Grading is completed online with the ability to provide tailored feedback quickly. Students receive the solutions immediately after submission and their scores with tailored feedback a few days later. Students have all homework assignments with their answers and feedback in one place for future reference. We have seen an increase in average grades and an increase of the buy-in of the e-textbook option as students appreciate the integration of textbook with tailored homework questions. Future plans include embedding mini video hints, tagged to specific homework questions. This tool allows students to build connections between the material they encounter to see the bigger picture. This session will demonstrate how homework assignments are set up, submitted, and graded when using the Lecturebook tool. There will also be some sharing of feedback from students and GSIs who have used this tool.
  • Happyville: Putting A Smile Into Statistical Ideas

    Kevin Robinson, Millersville University of Pennsylvania
    Tuesday, July 26, 2011 - 2:30pm ET
    This webinar will present a simple activity/handout called happyville, a community of 100 households, that has been used successfully in statistics courses. Happyville is utilized throughout the course to aid student understanding of statistical concepts including descriptive statistics, sampling techniques, sampling variation, sampling distributions, central limit theorem, confidence level, confidence intervals and type I & II errors. The happyville activity has the beneficial properties of being used throughout the course, visual demonstration and student engagement. The activity lends itself to both hands on simulation as well as computer based simulation. The activity maintains the attention and engagement of students, enables the students to discover important statistical ideas and overcome misconceptions often encountered in introductory statistics courses. Website: http://sites.millersville.edu/krobinson/happyville/
  • Reviewing and Writing for the Journal of Statistics Education (JSE)

    John Gabrosek, Grand Valley State University
    Tuesday, July 12, 2011 - 2:00pm ET
    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.
  • Using Crossword Puzzles in Applied Statistics Courses

    John McKenzie, Babson College
    Tuesday, June 28, 2011 - 2:30pm ET
    This webinar explains how crossword puzzles can be used as in-class exercises, quizzes, and examination questions in applied statistics courses to assist the students in learning basic statistical terminology. It presents innovative numerical crossword puzzles that can be to ask questions about statistical software output. It explains how the use of such puzzles was impractical in the past due to time it took to construct them but that this is no longer the case with the availability of a number of Internet sites.
  • Create an Iron Chef in statistics classes?

    Rebekah Isaak, Laura Le, Laura Ziegler, and the CATALST Team
    Tuesday, June 14, 2011 - 2:00pm ET
    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.
  • Active Methods for Teaching Central Tendency

    David Lane, Rice University
    Tuesday, May 24, 2011 - 2:30pm ET
    The concept of central tendency is typically taught by presenting measures of central tendency and then describing their properties. A (perhaps) better alternative is to think about different ways in which central tendency can be defined and then find statistics that fit these definitions. An activity using Java applets that allows students to discover statistics for each of three definitions of central tendency will be presented.
  • Is Stats 101 prepared for the CC Student?

    Jerry Moreno, John Carroll University
    Tuesday, May 10, 2011 - 2:00pm ET
    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?
  • The Role of a Wine Pricing Competition in Teaching Data Mining at Stanford

    Susan Holmes & Nelson Ray, Stanford University
    Tuesday, April 26, 2011 - 12:00pm ET
    We will discuss how we coordinated, held, and judged a wine pricing competition (hosted on Kaggle-in-Class - inclass.kaggle.com) to engage students in applying prediction techniques learned in our data mining class at Stanford. We found that with proper incentives, the competition was very successful in getting students interested in working collaboratively in a race against the clock to eke out additional predictive performance in their models.

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