Bill Rayens, University of Kentucky
Tuesday, January 10, 2012 - 2:00pm
After teaching the concepts of statistics and statistical reasoning for almost twenty-five years I became convinced that my lecture-recitation format was inefficient and maybe even counter-productive with respect to student learning. Throw in an excruciating self reflection focused on "what do my students really need me for anyway?" and it quickly became clear that my style and my classroom needed some kind of substantive change. The result was the development of an inverted classroom environment where traditional lecture material is off-loaded as mp4 files, the classroom is used for discovery and discussion, and the recitations are better tailored to the deductive abilities of new TAs. In this presentation we will demonstrate some of what we are doing here at the University of Kentucky in a course that serves approximately 4200 students in a calendar year. We will be sure to point out the things that may not be working that well, in addition to those that are.
Questions to Think About
Assuming you teach an introductory conceptual statistics course in a lecture/recitation format with TAs in charge of the recitations:
Do you use first-year TAs in your recitations? If so, do they have difficulties with appropriately handling conceptual questions and demonstrations?
Have you ever thought about what things you say and do in the "lecture" that are truly essential for you to say and do? Are these things that reflect the depth of your knowledge and experience in the field of statistics?
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.
Chris J. Wild, University of Auckland
Friday, November 11, 2011 - 2:30pm
This webinar is a short visual, narrative journey from the vibrating boxplot imagery of the author's 2009 USCOTS Plenary and Wild et al. (2011) to visualisations of bootstrap confidence intervals and, if time permits, randomisation tests. Software under development will be used and made available as-is to any brave souls willing to live on the edge.
Wild, C.J., M. Pfannkuch, M., Regan, M. and Horton, N.J. (2011). Towards more accessible conceptions of statistical Inference (with Discussion). Journal of the Royal Statistical Society A, 174, 247-295.
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.
Jackie Wroughton & Joe Nolan, Northern Kentucky University
Tuesday, September 27, 2011 - 2:30pm
We teach counting techniques such as combinations and permutations to aid students in accurately computing the size of large "sample spaces" and "events" without the need to list each individual possibility. We believe based on personal experiences that this material is challenging for students in part due to their desire to be able to perform calculations instantaneously without the need for careful and critical analysis of the problem. We present an activity - using ideas from the games of poker and pinochle - designed to help students expand from basic counting techniques and formulas to begin to think more critically about their subtleties. In addition to involving the advanced levels of critical thinking we want students to experience, the use of poker is advantageous because it represents a real-life situation with which many students are already familiar. Our observations suggest that some students will more readily engage in the activity due to these interests. Complexity is added by utilizing the less familiar Pinochle deck. While this activity has been tailored for use with statistics majors and future teachers at NKU, we believe the activity to be both entertaining and applicable for many different levels of students (including high-school discrete mathematics courses that have substantial probability components). We will discuss the activity including learning outcomes, rationale, and opportunities for teachable moments.
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.
Jamis Perrett, Texas A&M University
Tuesday, August 23, 2011 - 2:30pm
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.
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.
Kevin Robinson, Millersville University of Pennsylvania
Tuesday, July 26, 2011 - 2:30pm
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.