Kari Lock Morgan, Duke University
Tuesday, December 13, 2011 - 2:00pm
We discuss how and why we now use simulation methods (bootstrapping and randomization) to introduce fundamental topics of inference (intervals and tests) in an introductory statistics course. We describe ways to make these methods accessible early in the course, demonstrate new user-friendly applets for teaching and using these methods, and discuss some of our experiences with using this approach.
Georgette Nicolaides, Syracuse University; and Leigh Slauson, Capital University
Tuesday, November 8, 2011 - 2:00pm
This webinar will discuss the presenters' experiences conducting research with collaborators at several different institutions. Both presenters have in the CAUSE research cluster program for more than two years. This NSF funded program brings together statistics educators earlier in their career for the purposes of research. We will discuss some literature that suggests collaborations have a better chance of publication, the difficulties and the rewards of cross institutional research based on our own experiences and how clusters' view of the research process has changed over these past two years.
Dale Berger, Amanda Saw, Giovanni Sosa, Justin Mary, and Christopher Pentoney; Claremont Graduate University
Tuesday, October 11, 2011 - 2:00pm
This webinar will present the tutorials, applets, and other resources available on the Web Interface for Statistics Education project (wise.cgu.edu). Following an overview of WISE resources, we will demonstrate and discuss how instructors can use interactive applets to help students gain a better intuitive understanding of fundamental concepts like sampling distributions and statistical power. The webinar will conclude with a demonstration of a mini-lecture on statistical power, using an interactive applet to show how statistical power, sample size, effect size, and alpha error rate are interrelated. Student handouts and exercises will be provided.
Adam Childers & Jeff Spielman, Roanoke College
Tuesday, September 13, 2011 - 2:00pm
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.
Brenda Gunderson, University of Michigan
Tuesday, August 9, 2011 - 2:00pm
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.
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.
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.
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.
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?
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.
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.