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.

Cliff Konold Demonstrates Data Games, Discusses Research at UMN

"I don't think that we've really demonstrated that we can teach the fundamental ideas at any level. It'd sure be nice to do that!"

Cliff Konold, Director of the Scientific Reasoning Research Institute (SRRI) and Research Associate Professor at the University of Massachusetts Amherst, graced us with his presence on Friday, November 30. He is a major voice in the statistics education research community, and our CATALST course makes extensive use of the software he helped design, TinkerPlots™, for learning introductory statistics using simulation, randomization, and the bootstrap.

Cliff the Researcher

Cliff started out the day, however, wearing his researcher hat. Students in Joan Garfield's statistics education research seminar asked him about his evolution as a researcher, accompanied by a dotplot ("headplot"?) of all his first-author papers, as reported by his publications page at UMass:

Over the years, Cliff has used his head extensively for research purposes

Cliff's research has ranged from close studies of how people perceive randomness to informal inference and data analysis. He said his most proud accomplishment as a researcher is his 2002 Journal for Research in Mathematics Education article with fellow UMass researcher Alexander Pollatsek, "Data analysis as the search for signals in noisy processes", which explores why students are not comprehending the usefulness of measures of center. They argue that ideas of stochastic processes, rather than samples and populations, should be more emphasized in statistics instruction.

Cliff's papers getting all mixed up in TinkerPlots™.

Students Elizabeth Fry and Ethan Brown then decided to turn Cliff's creation against him. They put a selection of his papers into a TinkerPlots™ mixer—a simulated device for random sampling—and shuffled them to pick two papers to discuss with him. The first was a 1997 paper that Ruma Falk was the lead author on, "Making Sense of Randomness: Implicit Encoding as a Basis for Judgment" in Psychological Review. Cliff thought of this as some of the tightest research that came out of SRRI and described what a pleasure it was to have Ruma Falk there visiting and collaborating. The next paper which popped out of the mixer, "Understanding probability and statistical inference through resampling" from 1994, sparked reminiscences of getting deeply lost in Perugia, Italy at the first meeting of the International Conference on Teaching Statistics, where he presented the paper.

Cliff the Software Designer

For the afternoon, Cliff put on his software designer hat to show us his latest project with KCP Technologies, Inc., Data Games, a series of activities where students have to successfully analyze game data to improve their strategy. He's a co-PI on this project with Bill Finzer (see the full team here).

But his researcher hat was still on, poking out from below the software designer hat! Cliff discussed how we typically introduce students to univariate data by discussing natural objects or events such as people's heights. He argues, however, that this is actually a very difficult context to think about measures of center and variability, because there is no concrete thing that the "average person's height" represents.

Instead, he proposes that we can more easily teach these concepts using repeated measures settings. He designed an activity where different students measure the teacher's head; in this case, the center of the distribution is the actual person's head, and the variability is the student's errors in measurement (rounding issues, where exactly they hold the measuring tape, and so on).

Cliff uses not only his own head, but Professor Joan Garfield's as well.

Another promising setting is a production processes: in this settings, the center is the target of the process, and the variability is a combination of measurement error and production errors, which again can be named and pointed to.

But how can these be efficiently brought into the classroom? Having students do a production process or repeated measures takes quite a lot of time to collect the data. This is where the Data Games project comes in.

Ship Odyssey teaches students how to use rats for statistical inference.

Ship Odyssey gives students a chance to engage with repeated measures in a fanciful simulated environment. As intrepid treasure hunters on the high seas of yesteryear, gamers can send down highly skilled rats who find a treasure and then swim up. But they don't swim precisely straight up—they may get tossed to and fro, introducing variability. Students learn how to send down enough rats to get a good estimate of the center of the rat-measures distribution. When they send down their hook, they either see that they've collected a pile of sludge or they hear the satisfying cha-ching of successfully getting the treasure.

We had a great time seeing Cliff and hearing about his research, and we can't wait to see how Data Games develops. In the meantime, our challenge is to not let playing Ship Odyssey distract us from our end of semester work!

Senior Lecturer Michelle Everson on Online Discussions, News-Based Activities, and the Journal of Statistics Education

"I feel I get to know each student's voice more in the online course because I get to witness how he or she talks through different concepts and ideas and I get to witness how that changes over the course of the semester."

The latest issue of the Journal of Statistics Education features Allan Rossman's interview [PDF] with our very own Senior Lecturer, Michelle Everson! Michelle discusses her path to teaching and her growth as an online teacher and member of the statistics education community, and her ideas for the future direction of the Journal of Statistics Education as she prepares to take on the mantle of head editor.

How can we engage students with news stories? Can online environments help shy students flourish? What are ways that statistics educators can collaborate more? Michelle shares her honest and thoughtful insights from her years of award-winning teaching and designing courses.

Graduate Programs in Statistics Education Workshop: Planning for a Vibrant Future

  
Where will future statistics education researchers come from? The discipline now has journals and conferences, but we face a need for systematic, high quality training of a continual pipeline of statistics education researchers to create a flow of fresh perspectives that integrate with a deep understanding of what has been learned before.

Building on the successes of its 10-year-old statistics education program in the Department of Educational Psychology, the University of Minnesota hosted a Graduate Programs in Statistics Education Workshop on September 28, 2012, for other institutions looking to develop their programs, connect their research, and find opportunities for collaboration. This meeting at UMN's STEM Education Center brought together faculty already involved in planning and implementing these efforts to share their progress, consult on challenges, and form productive collaborations, and was made possible by a Member Initiated Grant from the American Statistical Association (ASA).

Xiao-Li Meng

On the first day, we heard from participants about the main issues that institutions face in implementing statistics education graduate programs. What departments should a statistics education program be affiliated with? How should the teaching and research components be balanced? How much statistics training should be involved? How should statistics education non-degree, Masters, and Ph.D. programs fit with structures in place for Mathematics or Science Education Ph.D.s? Xiao-Li Meng of Harvard University discussed the importance of preparing excellent statistics instructors, and Dennis Pearl of Ohio State University discussed how the current workshop related to guidelines [PDF] developed by a previous workshop that was endorsed by the ASA and the Consortium for the Advancement of Undergraduate Statistics Education. Joan Garfield and Michelle Everson of the University of Minnesota discussed the issues and challenges of a "Stat Ed 101" course with participants.

Dick Scheaffer, Mike Shaughnessy

The participants got to work on the second day to brainstorm next steps. Dick Scheaffer (past president of ASA) and Mike Shaughnessy (past president of the National Council of Teachers of Mathematics) set the tone by discussing the importance of statistics education graduate programs to K-12 teachers, and much of the remainder of the day was spent on small group discussions on the logistics, funding, and coursework that would be involved in non-degree, Masters, and Ph.D. programs. Dennis Pearl provided context for the discussion by providing an overview of a report that resulted from an American Statistical Association retreat on research priorities for statistics education, Connecting Research to Practice in a Culture of Assessment for Introductory College-level Statistics [PDF].

This report underscores why we need these statistics education programs to begin with: the urgent need to improve our understanding of cognitive outcomes, affective constructs, curriculum, teaching practice, teacher development, technology, and assessment in our field means we need strong institutional homes and training grounds for improving the breadth and effectiveness of the research.

Celebrating 10 Years of the Graduate Program in Statistics Education

So many friends came to Minnesota last month to help us celebrate the beginning of our second decade! They were from nearby, or from faraway; wise, or wet-behind the ears; and their academic affiliations showed the omnipresent variability of disciplines that inform our field -- curriculum and instruction, mathematics education, educational psychology, statistics, mathematics, and more. It was a lovely celebration, and we're quite grateful to the STEM Center at the University of Minnesota for helping us to toast the future of statistics education.

The night started with an unexpected haunting by our program's ghosts of statistics education past (Joan Garfield), present (Andy Zieffler), and future (Rebekah Isaak):

Bob delMas, who clearly has been having far too much fun on sabbatical in Australia, challenged the audience in this video to recognize as many catchy statistics education acronyms as possible... and to grapple with the thought-provoking cosmic mystery of pants:

Our supporters, friends, and colleagues who helped us get here chimed in with their reflections. Tamara Moore of the University of Minnesota STEM Center talked about her journey to understanding the relations between statistics and math education, and Michael Rodriguez discussed the healthy challenges that the program and its students bring to the university. Daniel Kaplan of Macalester College challenged us to think about the urgency of quantitative literacy for today's students. Dani Ben-Zvi of University of Haifa and Beth Chance of California Polytechnic State University shared reflections on their professional journeys in statistics education alongside Joan Garfield, while Rob Gould of UCLA dressed her up in a chef's outfit (with a little help from Photoshop). Dennis Pearl of wrapped up the speeches by discussing the importance of the work that's being done at the University of Minnesota and elsewhere to train the next generation of statistics education researchers.

To make the field sustainable, however, there needs to be more statistics education programs. That's why we also hosted a workshop on how to start more, so stay tuned to find out more about how that went.

CATALST Textbook

Andrew Zieffler, Joan Garfield, Robert delMas, Rebekah Isaak, Laura Le, and Laura Ziegler of Educational Psychology, have responded to concerns about high textbook prices for students enrolled in classroom sections of an undergraduate course, Basic and Applied Statistics (EPsy 3264), by producing an e-book entitled Statistical Thinking: A Simulation Approach to Modeling Uncertainty. It is available through amazon.com; the combined price of the textbook and software required for the course costs students as little as $15. (In previous semesters the textbook alone cost student $95.)

[Read the full article here]

Welcome to the Newest Catalysts for Change!

We have two new additions to the Catalysts for Change. Congratulations Laura and Laura!

Sean Ziegler

Evan Le

Both babies and moms are doing well.