Monday, December 9, 2013

Omnipresent variation in visions of the future introductory statistics textbook

The latest issue of Technology Innovations of Statistics Education, edited by Rob Gould of the University of California at Los Angeles, presents three very distinct visions of the the possibilities for a future statistics textbook. These articles are based on a session organized by Joan Garfield at the 2011 Joint Statistical Meetings, in Miami, Florda.

Three members of the CATALST team—Andrew Zieffler, Rebekah Isaak, and Joan Garfield—discuss the role of textbook in developing an introductory undergraduate course based on using simulation, randomization, and the bootstrap to develop the core logic of inference.

The innovation is primarily pedagogical. Zieffler et al. discuss how they found that having a unified, structured document to be very useful in supporting students' learning in an activity-based, student-centered course. The latest version of the textbook is available for free from Catalyst Press under a Creative Commons license which allows modification and incorporation of the material in for-profit works. (See our previous post on this book). The article discusses future plans for further innovations to the book such as incorporating videos directly into an e-book.

Cetinkaya-Rundel, Diez, and Barr also present a free product, OpenIntro Statistics, which is totally open source (the source code is fully available for modification). Their approach is based on a normal-theory based approach to the introductory course, chosen to encourage wide adoption, and the authors discuss the advantage inherent in having such a radically open process for development.

Webster West of North Carolina State University presents a vision that is more technologically intensive, including algorithmically generated exercises and tight integration of the textbook with the course management system and analysis software. His experiences partnering with Pearson Education and developing StatCrunch speak to how one might integrate technology with widely used, mainstream textbooks (though he describes himself as "closet radical").

The whole issue is well worth reading, because it features some lively and skeptical comments representing conflicting opinions from statistics education luminaries Beth Chance and Allan Rossman, George Cobb, Paul Velleman, and Jessica Utts, followed by responses from the authors.

Thursday, October 10, 2013

Social Media and Statistics Education

Dr. Michelle Everson is helping to catalyze new directions in statistics education through social media and the online classroom.

Social networks such as Facebook and Twitter provide not only distractions, but also great opportunities.  Building on her work in online classrooms and her teaching experiments that incorporate social media, the University of Minnesota's Michelle Everson provides some tips and resources for using social media to teach some resources in the latest AMSTAT News. She candidly shares both the successes and failures that she's experienced using these approaches.

For a deeper dive, Michelle has also recently published an overview of the pedagogy of social media in the latest issue of Computers and Human Behavior, with coauthors Ellen Gundlach of Purdue University, and Jaqueline Miller of Ohio State University.  Entering the maelstrom of social media is a bit easier with these thoughtful and seasoned teachers to guide you!

Monday, September 23, 2013

SRTL-8: Great Discussions by a Great Lake

Great statistics education thinkers from around the world came to sleepy Two Harbors, Minnesota for a week of discussion, debate, and reflection on the great issues in our field. The theme of the Eighth Forum of the International Collaboration for Research on Statistical Reasoning Thinking and Literacy (SRTL-8) was: Reasoning about uncertainty in the context of making informal statistical inferences. Our explorations of students' reasoning about uncertainty included many videos of students working through problems, and we explored the process of informal inferences qualitatively and quantitatively among K–12 and undergraduate students and teachers.
Twenty-four international delegates attended the week-long event from nine countries across the globe: Australia, Colombia, Germany, Israel, the Netherlands, New Zealand, Turkey, the United Kingdom, and the United States. The Forum provided the group of scholars with an opportunity for dedicated discussion and debate of the theme, stimulated by in-depth presentations and informal sharing of projects. A distinctive feature of SRTL's format is the emphasis on reflection and group discussion: a conference on student learning that is set up to foster deeper participant engagement and open-ended exploration than is usually available at lecture-oriented conferences.
Follow-up events are to include a book based on the scientific program, published through Catalyst Press, informal gatherings at other upcoming statistics education meetings, and ongoing research collaborations among many of the delegates. Plans are already underway for the next meeting (SRTL-9) in Germany in 2015.
The Forum was sponsored by The University of Minnesota, the Statistics Education Section of the American Statistical Association, Springer Publications, and Alakef Coffee Roasters.
Joan Garfield and Elizabeth Fry from The University of Minnesota led the local planning and organizing prior to the SRTL-8 gathering, supported by Bob delMas (University of Minnesota) and Dani Ben-Zvi (University of Haifa, Israel), who ensured that the forum ran smoothly. Thanks to the efforts of the local organizers, participants were able to not only enjoy each other’s creative efforts during the scientific program but also to appreciate the local culture and natural beauty of Minnesota’s north shore!

For further information please contact the SRTL co-chairs:
Joan Garfield,
Dani Ben-Zvi,

Scientific Program

George CobbStatistician's address: Reasoning about uncertainty: why our tensions are essential
Cliff KonoldUsing data and chance to make conclusions
Hana Manor Braham, Dani Ben-ZviStudents' reasoning about uncertainty while exploring sampling distributions in an "Integrated Approach"
Arthur Bakker, Dani Ben-Zvi, Katie MakarReducing uncertainty in a hospital laboratory: A vocational student's web of reasons and actions involved in making a statistical inference
Janet Ainley, Dani Ben-Zvi, Hana Manor Braham, Dave Pratt:Children's expressions of uncertainty in statistical modelling
Rob GouldTeaching data handling
Rolf Biehler, Daniel Frischemeier, Susanne PodwornyPreservice teachers' reasoning about uncertainty in the context of randomization tests
Luca ZapataPromoting the development of teachers' ideas of uncertainty
Sandra MaddenConstructing simulations and interrogating empirical sampling distributions supports teachers' reasoning in the presence of uncertainty
Pip Arnold, Stephanie Budgett, Maxine PfannkuchExperiment-to-causation inference: The emergence of new considerations regarding uncertainty
Robert delMas & Ethan BrownStudents' emerging reasoning with uncertainty in a randomization-based first course in statistics at the tertiary level
Jennifer NollFacilitating students' Reasoning about uncertainty in the context of making informal inferences: the role of curriculum and technology
Jill Fielding-Wells, Katie MakarInferring to a model: Using inquiry-based argumentation to challenge young children's expectations of equally likely outcomes
Sibel Kazak"How confident are you?" Supporting young students' reasoning about uncertainty in chance games through students' talk and computer simulations

Wednesday, September 4, 2013

Free Book—Statistical Thinking: A Simulation Approach to Modeling Uncertainty

(cross-posted from Citizen Statistician)

Catalyst Press has just released the second edition of the book Statistical Thinking: A Simulation Approach to Modeling Uncertainty. The material in the book is based on work related to the NSF-funded CATALST Project (DUE-0814433). It makes exclusive use of simulation to carry out inferential analyses. The material also builds on best practices and materials developed in statistics education, research and theory from cognitive science, as well as materials and methods that are successfully achieving parallel goals in other disciplines (e.g., mathematics and engineering education).

The materials in the book help students:
  • Build a foundation for statistical thinking through immersion in real world problems and data
  • Develop an appreciation for the use of data as evidence
  • Use simulation to address questions involving statistical inference including randomization tests and bootstrap intervals
  • Model and simulate data using TinkerPlots™ software
Why a cook on a statistics book? It is symbolic of a metaphor introduced by Alan Schoenfeld (1998) that posits many introductory (statistics) classes teach students how to follow “recipes”, but not how to really “cook.” That is, even if students leave a class able to perform routine procedures and tests, they do not have the big picture of the statistical process that will allow them to solve unfamiliar problems and to articulate and apply their understanding. Someone who knows how to cook knows the essential things to look for and focus on, and how to make adjustments on the fly. The materials in this book were intended to help teach students to “cook” (i.e., do statistics and think statistically).

The book is licensed under Creative Commons and is freely available on gitHub. If physical copies of the book are preferred, those are available for $45 at CreateSpace (or Amazon) in full color. All royalties from the book are donated to the Educational Psychology department at the University of Minnesota.

Tuesday, July 23, 2013

Catalysts at the 2013 Advanced Placement Statistics Reading

N. Parker, Laura Ziegler, Robin Lock (of St. Lawrence University), and Elizabeth Fry at the Advanced Placement Statistics Reading in Kansas City, Missouri
Every year, statistics teachers congregate to grade the Advanced Placement Statistics Exam, the final assessment given to high school students who completed the Advanced Placement Statistics course. This year, three of our Ph.D. students, N. Parker, Laura Ziegler, and Elizabeth Fry made it down to Kansas City for the reading, June 11–17.

Laura was a table leader, and N. was an "acorn"—the affectionate name given to first-time readers. AP Statistics gets bigger and bigger every year, with about 630 readers grading nearly 171,000 exams!  In fact, this year there were enough exams that the AP readers conquered the "million question challenge":  by grading more than a million responses.

We look forward to the day when enough students are taking AP Statistics that we face a two million question challenge!

Sunday, June 2, 2013

Change: Catalysts at the 2013 US Conference on Teaching Statistics


Many of University of Minnesota's statistics education group sallied forth to wet, warm North Carolina to share and learn with statistics educators around the country at the US Conference on Teaching Statistics (USCOTS) 2013! The conference theme this year, "Change", is very dear to our group, and throughout the conference, we presented some of what we've learned about rebooting statistics education to serve students better. Along the way, we learned from the wide variety of perspectives and insights on the discipline from statisticians, education researchers, and teachers.

Right before the conference, we led two fully enrolled workshops:

Bob delMas (second from left), along with Ph.D. students Laura Ziegler, N. Parker, and Laura Le, taught a workshop on UMN's CATALST curriculum, which exclusively uses simulation and resampling methods to teach a post-secondary introductory statistics course.  

Michelle Everson (right), with Master's student Ethan Brown, Ph.D. student Rebekah Isaak, and Master's student Anelise Sabbag, discussed practical tips and tricks for teaching a dynamic, engaging online statistics course.

Did we stop there? Of course not. The conference opened that night with a series of 5-minute presentations, including one by Bob delMas about his wizardly journey to improve statistics education.

Bob led a breakout session on Friday on evaluating new curriculum, using materials developed by the eATLAS project, along with Laura Le, Anelise Sabbag, and Elizabeth Fry.

Michelle, the perennial evangelist of online statistics education, participated in two more breakout sessions—one on time-management in online statistics courses, and another on the flipped classroom, as well as leading a lunch discussion group on planning the 2014 electronic Conference on Teaching Statistics (eCOTS).

Liz, N., and Ethan, who've been working with Joan Garfield to improve Wikipedia's coverage of statistics education, led another lunch discussion table to gather feedback and new collaborators on what should be included there.

The University of Minnesota's Catalysts for Change were inspired and motivated by this year's USCOTS, including the plenary speeches from Macalester College's Daniel Kaplan and Nicholas Horton (soon to be at Amherst College), North Carolina State University's Hollylynne Stohl Lee, Harvard University's Xiao-Li Meng, and University of Auckland's Chris Wild, and many more.  The slides of these speeches can be downloaded from the conference website.

Here's all the Catalysts who could make it, smiling in the energizing glow of the shared passion for excellence in statistics education!

Friday, March 29, 2013

The Journal of Statistics Education shines out in new directions

(Photo source: Chandra X-ray Observatory, Smithsonian Institution)
Michelle Everson's hard work as the new editor of the Journal of Statistics Education has borne fruit! The March issue is hot off the presses and freely available online. The issue includes new research on faculty views of statistics, a presentation of a delicious active learning exercise using M&M's, and a new regular feature on research for K-12 education by Tim Jacobbe of the University of Florida.

Michelle is also bringing her social media experience to help spread JSE's beautiful words to new realms. You can catch up with JSE on its facebook page and follow its Twitter feed, @JStatEd. The JSE team is also planning a series of webinars on CAUSEweb starting in June to give readers a chance to interact with the authors of recent JSE features.

You can read all about the JSE team's plans on the JSE page and read the new issue here.

Tuesday, February 5, 2013

Building the Logic of Statistical Inference on Day 1: The CATALST iPod Shuffle Activity

How random is the iPod shuffle? Your students can investigate.
What does it mean for a process to be "random"? The CATALST introductory statistics course engages students in this question in the very first activity, written up in the latest issue of Teaching Statistics by U of M's Laura Ziegler and Joan Garfield.

As Rob Gould points out, students have extensive prior experience with data and randomness. They do not enter the introductory statistics classroom as so many blank slates!

This situation presents both challenges and opportunities: we've heard from many students that it seems like some artists play more frequently than others on the Apple iPod's "shuffle" mode, which plays all songs in a supposedly random order.

Apple even ran an ad campaign in 2005 for the iPod Shuffle device with the slogan "Life is random":

But how random is it? Laura and Joan describe how the iPod shuffle activity elicits and refines student's prior conceptions of randomness. Students first examine 25 randomly generated playlists of 20 songs from a library of 80 songs. They discuss what rules they would use to flag a playlist as non-random. For instance, many students think that a playlist that has more than 5 songs by the same artist should be flagged.

We then give them five more playlists and give them an opportunity to refine their rules based on the additional information. Oftentimes, their rules will incorrectly flag one of these additional playlists and students may want to rethink their rules.

Finally, they get a chance to apply their rules to three playlists to make a decision about whether they have enough evidence to decide these playlists aren't random.

The process of the CATALST iPod Shuffle activity

Laura and Joan regard the full-class discussion, however, as quite crucial. Here is where students can hear the variety of different rules and face the logic and perception of what it means to be random. Students make all sorts of decisions that provide opportunities for rich conversations about the nature of chance: some students can provide convincing arguments that their rules are useful even when they incorrectly flag a playlist known to be random, while others are quick to say that their rules "prove" that the 3 final playlists were generated randomly.

This in-class activity is distributed in the Unit 1 Materials (zip) (Unit-01 > Student-Activities > 01-iPod-Shuffle.doc) on the CATALST materials page. The article also describes a follow-up homework assignment where students actually create a computer model of the process in TinkerPlots. This assignment is not publicly distributed, but interested teachers can contact the first author of the paper to find out more.

The publication is timely, because here at the U of M our students are just finishing up this first activity! It's a great way to get students started on the path to statistical thinking, and we always have fun hearing the creative things that students come up with.

Friday, January 25, 2013

Presenting a radical introductory course at the 2013 Joint Mathematical Meetings

Standing: outgoing SIGMAA chair Andy Zieffler; seated: Robin Lock, Kari Lock Morgan, Laura Ziegler, Elizabeth Fry, Rachel Dunwell, Allan Rossman, Soma Roy
Elizabeth Fry and Laura Ziegler, PhD students in the University of Minnesota's statistics education program, didn't even slow down after finishing their projects and exams this fall. They powered on during winter break to present the innovative CATALST introductory statistics course at the Joint Mathematical Meetings in sunny San Diego, California.

CATALST represents a sharp break from many statistics education traditions. Elizabeth and Laura described its radical content, pedagogy, technology, and assessments as part of a panel discussion on randomization methods in the introductory course:

CATALST course materials can be downloaded from the CATALST website. Development was funded by NSF DUE-0814433, and the full project team can be viewed here.

What's so radical about CATALST? The course joins the new wave of randomization-based curricula, spurred on by statistic education luminary George Cobb: "Randomization-based inference makes a direct connection between data production and the logic of inference that deserves to be at the core of every introductory course." (from The Introductory Statistics Course: A Ptolemaic Curriculum?)

Laura and Elizabeth presented CATALST as a part of a panel discussion on randomization curricula organized by the Statistics Education SIGMAA group. This was one of U of M Senior Lecturer Andy Zieffler's final duties as the 2012 chair of the SIGMAA. Rachel Dunwell of Rhodes College started by talking about how they used to teach a traditional curriculum, and now they're doing simulations with Fathom; Allan Rossman and Soma Roy of California Polytechnic State University talked about their randomization course; and Kari Lock Morgan and Robin Lock talked about their new book and online StatKey software.

CATALST's pedagogy is also radical. The curriculum moves students through a range of activities that they work on in groups. Instructors deliver support with "just-in-time" statistics instruction that's driven by the activities. These activites are made possible by allowing students to directly model probabilities in TinkerPlots. Elizabeth and Laura's presentation discusses an activity, "Matching Dogs to Owners", where students create simulation models of a messy situation that would be difficult to solve analytically.

These radical techniques call for radical assessment that is based on the actual goals of the course. The assessments, known as GOALS and MOST and part of the e-ATLAS project for the Evaluation and Assessment of Teaching and Learning About Statistics, measure conceptual understanding rather than the procedural knowledge of how to compute t-statistics and correlations.

Elizabeth Fry with her poster on the e-ATLAS evaluation and assessment project.

Want to know more? U of M's Laura Ziegler and Joan Garfield wrote an article about the first activity in the course in the latest issue of Teaching Statistics! We'll be taking a closer look at this article in a forthcoming post.