ICOTS 9 2014

Flagstaff, Arizona, United States of America

• Welcome from the IASE President : Iddo Gal
• Editors’ Preface and Acknowledgements : Katie Makar
• Sponsors

Plenaries

• On the relationships between statistics and other subjects in the K-12 curriculum : Zalman Usiskin
• What can we learn from real-world communication of risk and uncertainty? : David Spiegelhalter (and Jenny Gage)
• Teaching statistics to Real People: adventures in social stochastics : Rachel Fewster
• Statistics in 2014: Reflections on the occasion of the 175th anniversary of the American Statistical Association : Ronald Wasserstein
• Sustainable education for professional Statisticians : Pedro Luis do Nascimento Silva

Excellence Awards for Early Career Papers

Winners

• Einat Gil: Long-term impact on students’ informal inferential reasoning
• Christoph Till: Risk literacy: first steps in primary school

“Highly commended” papers

• Jennifer Green: Beyond calculations: fostering conceptual understanding in statistics graduate teaching assistants
• Bridgette Jacob: Statistical reasoning with the sampling distribution
• Laura Ziegler: Reconceptualizing statistical literacy: developing an assessment for the modern introductory statistics course

Topic 1: Sustaining strengths and building capacity in statistics education

Building the capacity of mathematics and science teachers to teach statistics

• 1A1: Curriculum expectations for teaching science and statistics : Jane Watson
• 1A2: The Statistical Education of Teachers (SET): an American Statistical Association policy document : Christine Franklin
• 1A3: Building high school pre-service teachers’ knowledge to teach correlation and regression : Carmen Batanero, Maria M Gea, Carmen Díaz, Gustavo R Cañadas

Statistics education outreach across the globe

• 1C1: Outreach efforts to enhance statistical education and statistical literacy in Hungary : Péter Kovács
• 1C2: OZCOTS: Bringing statistical educators and statisticians together : Brian Phillips
• 1C3: Japanese Inter-university Network for Statistical Education and new trials for development of students’ data analysis skills : Kazunori Yamaguchi, Michiko Watanabe

Building the capacity to teach and understand statistics in emerging economies

• 1D1: On the commencement of a culture of “statistics acceptance” in a higher education institution relatively new at research : Saleha Habibullah
• 1D2: Building capacity for developing statistical literacy in a developing country : Temesgen Zewotir, Delia North, Iddo Gal, Michael Murray
• 1D3: Statistics education in Ethiopia: successes, challenges and opportunities : Ann A O’Connell, Kassa Michael
• 1D4: Sustaining teachers’ capacity for teaching statistical inference through reflective practice : Enriqueta Reston, Liza Lorena Jala

Building capacity in Statistics majors

• 1E1: Skills needed for modern day statisticians : Andrej Blejec
• 1E2: Challenges and issues in developing real-world curriculum for data scientists in Japan : Takuya Kudo, Yoshihiro Hayashi, Michiko Watanabe, Tomiaki Morikawa, Tomoyuki Furutani, Manabu Iwasaki
• 1E3: Building capability in statistics majors: drawing strength from a diverse region : Alice Richardson

The importance of attitudes in statistics education: sustaining learning processes and outcomes

• 1F1: Student attitudes toward statistics from a randomization-based curriculum : Todd Swanson, Jill VanderStoep, Nathan Tintle
• 1F2: How do attitudes change from one stats course to the next? : Anne Michele Millar, Bethany White
• 1F3: A fallacy in student attitude research: the impact of the first class : Michael Posner
• 1F4: Comparing attitudes toward statistics among students enrolled in project-based and hybrid statistics courses : Caroline Ramirez, Marjorie Bond

Topic 2: Statistics education at school level

Early years statistics education: ages 4 - 8

• 2A1: Important ideas in statistics for children aged 4-8 years : Denise Spangler
• 2A2: Establishing statistical foundations early: data modeling with young learners : Lyn English
• 2A3: Exposing young children to activities that develop emergent inferential practices in statistics : Debra McPhee, Katie Makar

Middle school statistics education: ages 8 - 13

• 2B1: Middle school (ages 10 – 13) students’ understanding of statistics : Tim Jacobbe, Steve Foti, Douglas Whitaker
• 2B2: Where’s your evidence? Challenging young students’ equiprobability bias through argumentation : Jill Fielding-Wells
• 2B3: Student perspectives on being introduced to using Tinkerplots for investigations : Tim Burgess

Secondary school statistics education: ages 13 +

• 2C1: On the delicate relation between informal statistical inference and formal statistical inference : Rolf Biehler
• 2C2: High school (ages 14 – 18) students’ understanding of statistics : Tim Jacobbe, Steve Foti, Catherine Case, Douglas Whitaker
• 2C3: Teaching statistics at secondary education in Italy: some issues on large scale standardized test results : Stefania Mignani, M Gabriella Ottaviani, Robert Ricci
• 2C4: Analysis of teachers’ understanding of covariation in the Vitruvian Man context : Verônica Yumi Kataoka, Cláudia Borim da Silva, Irene Cazorla

Statistical education at the Secondary/Higher Education interface

• 2D1: What did they learn? Statistics skills: from French secondary school to university : Alain Bihan-Poudec, Philippe Dutarte
• 2D2: Bridging the statistical gap: creating successful secondary/higher education partnerships : Daren Starnes
• 2D3: Preparing future teachers to teach statistics : Gail Burrill

Using technology at school level to enhance statistical understanding

• 2E1: From hat plots to box plots in Tinkerplots: supporting students to write conclusions which account for variability in data : Sue Allmond, Katie Makar
• 2E2: Constructing, refining and validating a task for developing reasoning on stabilized frequency distributions in the context of informal inferences : Ana Serradó-Bayés
• 2E3: Games of chance: tools that help enhance teachers’ notions of statistics and probability : Nirmala Naresh

Innovative approaches to improve pedagogical content knowledge at the school level

• 2F1: Improving the perceived value and affect of statistics in elementary and middle school teachers through the development of pedagogical content knowledge : Tamara Pearson
• 2F2: Statistical knowledge for teaching: elementary preservice teachers : Christine Browning, Joshua Goss, Dustin Smith
• 2F3: High school teachers’ pedagogical content knowledge of variability : Sylvain Vermette, Linda Gattuso

Linking research and practice in teaching and learning statistics at the school level

• 2G1: Developing statistics teachers’ identity: a look at communities of practice : Difariney González, Lucía Zapata-Cardona
• 2G2: Communities of practice: a theoretical framework to design for teachers’ statistical learning : Ana Luisa Gómez-Blancarte, Isaias Miranda Viramontes
• 2G3: From observing and evaluating variation to measuring and comparing variation : Erna Lampen
• 2G4: Teachers as key stakeholders in research in statistics education : Michael Shaughnessy

Topic 3: Education and development of staff who teach statistics

Statistics instructors’ content knowledge

• 3A1: Developing pre-service teachers’ technological pedagogical content knowledge (TPACK) of sampling : Maria Meletiou-Mavrotheris, Irene Kleanthous, Efi Paparistodemou
• 3A2: Analysis of teachers’ understanding of variation in the dot-boxplot context : Cláudia Borim da Silva, Verônica Yumi Kataoka, Irene Cazorla
• 3A3: Beyond calculations: fostering conceptual understanding in statistics graduate teaching assistants : Jennifer L Green, Erin E Blankenship

Statistics instructors’ knowledge of students’ development of fundamental statistics concepts

• 3B1: A certification system for statistics knowledge and skills by Japanese Statistical Society : Yoshinori Fujii, Hiromi Fukazawa, Akinobu Takeuchi, Michiko Watanabe
• 3B2: Teachers’ knowledge of students’ conceptions and their development when learning linear regression : Stephanie Casey
• 3B3: The impact of a teachers’ attention deriving on students’ statistical discourse : Min-Sun Park, Kyeong-Hwa Lee

Statistical instructors’ knowledge of assessing students’ learning of statistics

• 3C1: Trends in students’ conceptual understanding of statistics : Robert C delMas
• 3C2: Discerning students’ statistical thinking: a researcher’s perspective : James Baglin
• 3C3: The LOCUS assessment at the college level: conceptual understanding in introductory statistics : Tim Jacobbe, Douglas Whitaker, Catherine Case, Steve Foti

Statistics instructors’ use of technology for teaching statistics

• 3D1: Using bootstrap dynamic visualizations in teaching : Jocelyn Cumming, Christine Miller, Maxine Pfannkuch
• 3D2: Reflections on using technology to teach statistics in Kenya : David Stern
• 3D3: Using the Open Learning Initiative (OLI) to support teaching statistics to international politics students : Parina Patel, Oded Meyer
• 3D4: The use of technology in a mentor teacher course in statistics education : Thomas Wassong, Rolf Biehler

Professional development of statistics instructors

• 3E1: Building the capacity of mathematics and science teachers to teach statistics : Katharine Richards, Neil Sheldon, Neville Davies
• 3E2: Project-SET materials for the teaching and learning of sampling variability and regression : Anna Bargagliotti, Celia Anderson, Stephanie Casey, Michelle Everson, Christine Franklin, Robert Gould, Randall Groth, John Haddock, Ann Watkins
• 3E3: Implementing GAISE recommendations through “doing statistics” tasks : Brandon Hanson, Jeremy Strayer, Katherine Mangione, Jessica Brown, Jeffrey Pair

Theory and practice of statistics: curriculum for statistics teachers

• 3F1: Suitability criteria for teachers’ education programs in mathematics and statistics education : Juan D Godino, Pedro Arteaga, Hernán Rivas
• 3F2: Relationships between curriculum knowledge of in-service Mexican teachers and statistics : Ernesto Sánchez, Verónica Hoyos
• 3F3: Preparing teachers to teach statistics: developing professional knowledge and practice : Ana Henriques, João Pedro da Ponte

Topic 4: Statistics education at the post-secondary level

Randomisation and bootstrapping: the quick way to inference

• 4A1: Accepting the challenge: constructing a randomisation pathway for inference into our traditional introductory course : A Marie Fitch, Matt Regan
• 4A2: Using simulation/randomization to introduce p-value in week 1 : Soma Roy, Allan Rossman, Beth Chance, George Cobb, Jill VanderStoep, Nathan Tintle, Todd Swanson
• 4A3: Intuitive introduction to the important ideas of inference : Robin Lock, Patti Frazer Lock, Kari Lock Morgan, Eric Lock, Dennis Lock

Use of student response systems in teaching statistics at the university level

• 4B1: Clickers, simulations, and conceptual understanding of statistical inference : Jennifer Kaplan
• 4B2: Teaching data analysis in large classes using clicker assessment : Michael Forster
• 4B3: Teaching discrete distributions using contingent teaching with clickers : Wayne Stewart, Sepideh Stewart
• 4B4: Personal response systems as a learning aid in an epidemiology course for postgraduate statistics students : Gillian Lancaster, Andrew Titman

Rank-based inference, association measures and nonparametric statistics

• 4C1: Is the real world normal? : Catherine Dehon
• 4C3: Combining nonparametric inferences using data depth, bootstrap and confidence distribution : Dungang Liu, Regina Y Liu, Min-ge Xie
• 4C4: Should we still teach rank-based distribution-free procedures? : E Jacquelin Dietz

Exchanging pedagogy between post-secondary and secondary school statistics courses

• 4D1: Exchanging statistics pedagogy between the master teacher and the future teacher : Deborah Nolan
• 4D2: Statistics for all students : Courtney Couvreur
• 4D3: Exchanging pedagogy between post-secondary and secondary school statistics courses : Kim Gilbert
• 4D4: Exchanging pedagogy between post-secondary and secondary school statistics courses: facilitating meaningful professional development : Josh Tabor

We know you need to know statistics, do you?

• 4E1: Measuring university students’ approaches to learning statistics: a cross-cultural and multilingual version of the ASSIST : Francesca Chiesi, Caterina Primi, Ayse Bilgin, Maria Virginia Lopez, Maria del Carmen Fabrizio
• 4E2: A comparison of attitudes between traditional and hands-on classes in an introductory statistics course : Aklilu Zeleke, Carl Lee, Chin-I Cheng, Jennifer Daniels, Kundana Divi
• 4E3: Turkish ASSIST: measuring university students’ approaches to learning statistics : Ayse Bilgin, Sitki Gozlu

Opening up the data world wider and faster

• 4F1: Introductory statistics in the 21st century : Richard De Veaux
• 4F2: DataFest: celebrating data in the data deluge : Robert Gould
• 4F3: Middleware for Middle Earth : Chris Wild
• 4F4: Open data, civil society and monitoring progress: challenges for statistics education : Joachim Engel

Topic 5: Statistics education in the disciplines and the workplace

Evidence-based policy making

• 5A1: The use of official statistics in evidence based policy making in New Zealand : Sharleen Forbes, Tania Janssen
• 5A2: Challenges to evidence-based policy making in the decentralized U.S. statistical system : Nancy Potok, Amy O’Hara, Ron Jarmin
• 5A3: Statistics education, collaborative research, and LISA 2020: a view from Nigeria : Olushina Olawale Awe, Eric A Vance
• 5A4: International statistical standards as enabler for evidence-based policy making: the case of tourism statistics : Oliver Herrmann

Evidence-based management

• 5B2: The prevalence of statistics and data mining in management journals : Shirley Coleman, Alex Douglas, Jiyu Anthony
• 5B3: Bringing the workplace into a National Certificate in Official Statistics : Sharleen Forbes, Alan Keegan
• 5B4: How do school principals understand and use the statistics in reports from national large-scale assessments? : Iddo Gal, Hani Shilton

Development of statistical thinking in the workplace

• 5D1: Improving statistical literacy at university : Jennifer Brown, Irene David, Elena Moltchanova, Hilary Seddon, Jenny Harlow
• 5D2: The contributions of Six Sigma to the development of statistical thinking in the workplace : Doug Montgomery
• 5D3: Development of training methods to accelerate the competencies in Weibull analysis: case study in the automotive industry : Halimatou Ndiaye, Sébastien Castric, Zohra Cherfi, Michael Huchette, Paul Schimmerling

Mentoring young statisticians in the workplace

• 5E1: The importance of inter-personal skills on statistical teams : Sara Fett
• 5E2: Best practices in mentoring and training young statisticians : Lisa Grace Bersales
• 5E3: Mentoring advanced and newly graduated masters and Ph.D students : Linda Young

Bridging the gap between current statistical practice in the workplace and modern statistics

• 5F1: Tradition should not supplant understanding and insight : Richard Wilson, John Maindonald
• 5F2: Once were warriors: the need of re-education in mathematics and computing for life “scientisticians” : Jorge Navarro Alberto
• 5F3: Training to develop modern statistics in the workplace using R and R Commander – experiences from the New Zealand government sector : Ian Westbrooke, Peter Ellis

In search of evidence: exploring the relationship between real workplace based data and statistics education

• 5H1: Workplace and official statistics: how can higher education contribute to a better relationship? : Mojca Bavdaž, Irena Ograjenšek, Lejla Perviz
• 5H2: Experiences with real and accessible recent data in context to motivate student learning at higher levels in statistics : John Harraway
• 5H3: Supporting statistical consultant decision-making within a case-based learning environment : Glenn Johnson, Durland Shumway

Topic 6: Innovation and reform in teaching probability within statistics

Bayesian inference (probability) goes to school: meanings, tasks and instructional challenges

• 6A1: Will the real Bayesian probablity please stand up!? : Egan Chernoff
• 6A2: Proto-Bayesian reasoning of children in fourth class : Laura Martignon, Tim Erickson
• 6A3: Exploring realistic Bayesian modeling situations : Per Nilsson, Per Blomberg, Jonas Bergman Ärlebäck

Probability and p-values — probing the problems

• 6B1: Impact of a simulation/randomization-based curriculum on student understanding of p-values and confidence intervals : Beth Chance, Karen McGaughey
• 6B2: Teaching probability: using levels of dialogue and proportional reasoning : Ian Hay
• 6B3: The interpretation of effect size in published articles : Rink Hoekstra

Interdisciplinarity and innovation

• 6C1: Sampling in the wild : Michelle Cotterman, Richard Lehrer, Leona Schauble
• 6C2: Using re-sampling and sampling variability in an applied context as a basis for making statistical inferences with confidence : Luis Saldanha, Michael McAllister
• 6C3: A case study of an elementary school student’s understanding of stochastic prognoses : Judith Stanja

Teaching probability to future teachers of mathematics and statistics

• 6D1: Step-by-step activities in the classroom preparing to teach the frequentist definition of probability : Lisbeth Cordani
• 6D2: Learning and teaching probability in the 21st century : Maurizio Manuguerra, Peter Petocz
• 6D3: Transforming media items into classroom tasks in the context of a study group : Dionysia Bakogianni, Efi Paparistodemou, Despina Potari

Modeling distributions to connect chance processes, data production, and data distributions

• 6E1: Model-based informal inference : Richard Lehrer, Ryan Seth Jones, Min-Joung Kim
• 6E2: Visual representations of empirical probability distributions when using the granular density metaphor : J Todd Lee, Hollylynne Stohl Lee
• 6E3: Multidirectional modelling for fostering students’ connections between real contexts and data, and probability distributions : Theodosia Prodromou

Teachers’ awareness of conceptual connections between probability and statistics

• 6F1: Teachers and students: from an intuitive approach to a rational evaluation of probability : Maria Pia Perelli D’Argenzio, Silio Rigatti-Luchini
• 6F2: Challenges for learning about distributions in courses for future Mathematics teachers : Marcos Magalhães
• 6F3: Odds that don’t add up : Michael Fletcher

Topic 7: Statistical literacy in the wider society

Statistical literacy beyond the classroom

• 7A1: Odyssey: a journey to lifelong statistical literacy : Milo Schield
• 7A2: Teaching statistics for engagement beyond classroom walls : Lawrence Lesser
• 7A3: Taking statistical literacy to the masses with YouTube, blogging, Facebook and Twitter : Nicola Ward Petty

Statistical literacy requirements for teachers

• 7B1: Statistical literacy requirements for teachers : Jeffrey Hovermill, Brian Beaudrie, Barbara Boschmans
• 7B2: Developing statistical knowledge for teaching of variability through professional development : Helena Wessels
• 7B3: Teachers’ views related to goals of the statistics classroom – from global to content-specific : Sebastian Kuntze

Assessment of statistical literacy

• 7C1: Towards statistical literacy - relating assessment to the real world : Penelope Bidgood
• 7C2: Establishing the validity of the LOCUS assessments through an evidenced-centered design approach : Tim Jacobbe, Catherine Case, Douglas Whitaker, Steve Foti
• 7C3: Sufficiently assessing teachers’ statistical literacy : Helen Chick, Robyn Pierce, Roger Wander

Developing statistical literacy: Case studies and lessons learned

• 7D1: Students’ beliefs about the benefit of statistical knowledge when perceiving information through daily media : Alexandra Sturm, Andreas Eichler
• 7D2: Changing the course: from boring numeracy to inspiring literacy : Kimmo Vehkalahti
• 7D3: A numeracy infusion course for higher education (NICHE): strategies for effective quantitative reasoning (QR) instruction : Esther Isabelle Wilder, Elin Waring, Frank Wang, Dene Hurley
• 7D4: Implementing a quantitative literacy core competency requirement in the College of Arts and Science at Miami University : John Bailer

Factors that affect statistical literacy

• 7E1: Critical thinking as an impact factor on statistical literacy – theoretical frameworks and results from an interview study : Einav Aizikovitsh-Udi, Sebastian Kuntze
• 7E2: A multilevel perspective on factors influencing students’ statistical literacy : Ute Sproesser, Sebastian Kuntze, Joachim Engel
• 7E3: Sustaining communication of the value of statistics in the humanities : Nicole Mee-Hyaang Jinn

Factors that affect statistical literacy II

• 7F1: Reconceptualizing statistical literacy: Developing an assessment for the modern introductory statistics course : Laura Ziegler
• 7F2: Improving statistical literacy through supplemental instruction : Alexandra Kapatou
• 7F3: Interpreting variation of data in risk-context by middle school students : Antonio Orta, Ernesto Sánchez

Topic 8: Research in statistics education

Research on developing students’ reasoning using simulation methods for introductory statistical inference: Session I

• 8A1: Students’ visual reasoning and the randomization test : Stephanie Budgett, Chris Wild
• 8A2: Designing and implementing an alternative teaching concept within a continuous professional development course for German secondary school teachers : Janina Oesterhaus, Rolf Biehler
• 8A3: Quantitative evidence for the use of simulation and randomization in the introductory statistics course : Nathan Tintle, Ally Rogers, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill VanderStoep

Research on developing students’ reasoning using simulation methods for introductory statistical inference: Session 2

• 8B1: The symbiotic, mutualistic relationship between modeling and simulation in developing students’ statistical reasoning about inference and uncertainty : Andrew Zieffler, Robert C delMas, Joan Garfield, Ethan Brown
• 8B2: Bootstrapping for learning statistics : Tim Hesterberg
• 8B3: From data to decision-making: using simulation and resampling methods to teach inferential concepts : Mia Stephens, Robert H Carver, Don McCormack

Research on developing students’ informal statistical inferential reasoning

• 8C1: Informal statistical inference revisited : Katie Makar, Andee Rubin
• 8C2: Students’ reasoning about uncertainty while making informal statistical inferences in an “integrated pedagogic approach” : Hana Manor Braham, Dani Ben-Zvi, Keren Aridor-Berger,
• 8C3: Exploring informal inferential reasoning through data games : Kosoom Kreetong

Research on developing students’ statistical reasoning

• 8D1: Long-term impact on students’ informal inferential reasoning : Einat Gil, Dani Ben-Zvi
• 8D2: Statistical reasoning with the sampling distribution : Bridgette L Jacob, Helen Doerr
• 8D3: Extending the curriculum with TinkerPlots: opportunities for early development of informal inference : Noleine Fitzallen, Jane Watson

Research on developing students’ probabilistic reasoning

• 8E1: Empirical research on understanding probability and related concepts — a review of vital issues : Manfred Borovcnik
• 8E2: Reasoning development of a high school student about probability concept : Julio C Valdez, Ernesto Sánchez
• 8E3: Characteristics of students’ probabalistic reasoning in a simulation-based statistics course : Aaron Weinberg

Research on professional development of teachers in statistics

• 8F1: Teachers’ professional development in a stochastics investigation community : Adair Mendes Nacarato, Regina Célia Grando
• 8F2: A teacher development program in statistics within a community of practice : Lucía Zapata-Cardona
• 8F3: Professional development for teaching statistics: a collaborative action research project with middle-school mathematics teachers : Leandro de Oliveira Souza
• 8F4: Learning and teaching statistical investigations: a case study of a prospective teacher : Raquel Santos, João Pedro da Ponte

Theoretical frameworks in statistics education research

• 8G1: Describing distributions : Pip Arnold, Maxine Pfannkuch
• 8G3: Cultural diversity in statistics education: bridging uniqueness : Pieternella Verhoeven, Dirk Tempelaar
• 8G4: About central issues of mental model theory in context of learning statistics : Markus Vogel, Andreas Eichler

Research on risk literacy

• 8I1: Getting alternative representations for risk into the school syllabus : David Spiegelhalter, Jenny Gage
• 8I3: Risk literacy: first steps in primary school : Christoph Till
• 8I4: Comparing fast and frugal trees and Bayesian networks for risk assessment : Kathryn Laskey, Laura Martignon

Research on technology in statistics education

• 8J1: Constructing inferential concepts through bootstrap and randomization-test simulations: a case study : Maxine Pfannkuch, Stephanie Budgett
• 8J2: Measuring the effectiveness of using computer assisted statistics textbooks in Kenya : Bernard Manyalla, Zachariah Mbasu, David Stern, Roger Stern
• 8J3: Comparing groups by using TinkerPlots as part of a data analysis task — tertiary students’ strategies and difficulties : Daniel Frischemeier

Topic 9: Technology in statistics education

The design of digital tools and technology-enhanced learning environments for teaching statistics

• 9A1: Expressions of uncertainty when variation is partially-determined : Janet Ainley, David Pratt
• 9A2: A learning trajectory on hypothesis testing with TinkerPlots – design and exploratory evaluation : Susanne Podworny, Rolf Biehler
• 9A3: Students’ emergent roles in developing their reasoning about uncertainty and modeling : Keren Aridor-Berger, Dani Ben-Zvi

Modeling, randomization and simulation tools for connecting data and chance

• 9B1: Hierarchical data visualization as a tool for developing student understanding of variation of data generated in simulations : William Finzer
• 9B2: StatKey: online tools for bootstrap intervals and randomization tests : Kari Lock Morgan, Robin Lock, Patti Frazer Lock, Eric Lock, Dennis Lock
• 9B3: Teaching resampling in an introductory statistics course : Webster West

The emerging concepts of “data science” and “big data” for educational purposes

• 9C1: Exploring “white flight” via open data and big data : James Ridgway, James Nicholson, Sean McCusker
• 9C2: Teaching data science to teenagers : Amelia McNamara, Mark Hansen
• 9C3: Integrating big data into the science curriculum : Daniel Kaplan, Paul Overvoorde, Elizabeth Shoop

E-learning, E-teaching and E-assessment in fully online, blended and open virtual web-based courses

• 9D1: Experiences teaching an introductory statistics MOOC : Alison Gibbs
• 9D2: Statistical reasoning’s new look : John McGready
• 9D3: Using Carnegie Mellon’s Open Learning Initiative (OLI) to support the teaching of introductory statistics: experiences, assessments and lesson learned : Oded Meyer, Marsha Lovette
• 9D4: A mobile web for enhancing statistics and mathematics education : Jamie Lentin, Anna Jonsdottir, David Stern, Victoria Mokua, Gunnar Stefansson

Supporting teachers’ use of new statistics technology in their classrooms and development of their technological-pedagogical content knowledge

• 9E1: Data and Chance with FATHOM — teaching material for implementing computer-based stochastic courses : Andreas Prömmel
• 9E2: Designing technology-rich learning environments for secondary teachers to explore and prepare to teach statistics : Sandra Madden
• 9E3: How a curriculum may develop technological statistical knowledge: a case of teachers examining relationships among variables using Fathom : Hollylynne Stohl Lee, Jennifer Nickell

Technology for developing statistical thinking, reasoning, and literacy

• 9F1: Year six students’ reasoning about random “bunny hops” through the use of TinkerPlots and peer-to-peer dialogic interactions : Sibel Kazak, Taro Fujita, Rupert Wegerif
• 9F2: Technology for developing statistical thinking: a psychological perspective : Peter Sedlmeier
• 9F3: Integrating technology in regular statistics courses and assessments of pre-service teachers : Andreas Eichler

Educational software for helping students learn statistics

• 9G1: An early look at rich learning analytics: statistics students playing “Markov” : Tim Erickson, Mariel Triggs
• 9G2: Improving the attitudes of high school students towards statistics: an island-based approach : Minh Huynh, James Baglin, Anthony Bedford
• 9G3: Using on-line quizzes to help students learn probability and statistics : Mitchum Bock, John McColl

Topic 10: Innovative collaboration in statistics education

Collaborations between Statistics agencies and academia (schools/universities/colleges)

• 10A2: Developing statistical literacy amongst in-service teachers through a collaborative project : Delia North, Temesgen Zewotir, Iddo Gal
• 10A3: SMARTCensus – making sense of census data : James Nicholson, James Ridgway, Sean McCusker
• 10A4: More ways to Heaven than one: improving statistical literacy in Ireland : Eoin MacCuirc, Steve MacFeely

Collaboration among countries

• 10C1: Statistics and probability curriculum development for future elementary teachers in Chile: collaboration among countries : Eugenio Chandía Muñoz, Anita Araneda, Alejandra Sorto, José Luis Abreu León
• 10C3: How the curriculum shapes teachers’ thinking: a comparison of New Zealand and Australian teachers’ thinking about statistics : Rosemary Callingham, Tim Burgess
• 10C4: Building strength from compromise: a case study of five year collaboration between the Statistical Services Centre of the University of Reading, UK, and Maseno University, Kenya : James Musyoka, David Stern, Roger Stern

Research projects collaborations

• 10E1: Open lessons impact statistics teaching teachers’ beliefs : Raimundo Olfos, Soledad Estrella, Sergio Morales
• 10E2: Conducting successful cross-institutional research in statistics education : Jacqueline Wroughton
• 10E3: Peer learning in statistics beyond the University curriculum : Peter Petocz, Aisha Newnham, Emily Trussell, Kirsten Warwick, Allysia Jarrett, Anna Reid, Ayse Bilgin

Contributed papers

• C101: A graphical approach to examine inferential reasoning development : Sharon Lane-Getaz
• C102: How to organize effective and efficient group work in tutorials using indicator strips : Toni C. Stocker
• C104: The potential of a grounded theory approach to study teaching probability : Andreas Eckert
• C105: Distance education of teachers of statistics : Jeffrey Hovermill, Brian Beaudrie
• C107: Challenges in teaching medical statistics in developing country : Ashwani Kumar Mishra
• C108: The wonderful lamp of Aladdin? Project work in engineering courses : Maria Manuel da Silva Nascimento, José Alexandre dos Santos Vaz Martins, Assumpta Estrada
• C109: After statistics reform: should we still teach significance testing? : Tony Hak
• C111: Measuring the basics of probabilistic reasoning: the IRT-based construction of the probabilistic reasoning questionnaire : Caterina Primi, Kinga Morsanyi, Francesca Chiesi
• C116: A review of probability and statistics apps for mobile devices : Howard Edwards
• C117: Games as a locus of self-empowered collaborative learning : Shonda Kuiper, Rod Sturdivant
• C119: Fostering deep statistical learning using diversity content: the “statistics of sexual orientation” course : Michele DiPietro
• C120: Excel simulation as a tool in teaching sampling distributions in introductory statistics : Leslie Chandrakantha
• C121: Perceptions of undergraduate and executive students about the use of an exercise-based statistics website : André Samartini
• C122: Students’ understanding of confidence intervals : Robyn Reaburn
• C123: Learning statistics in the first grades : Susana Colaço
• C126: Restructuring of disciplines in statistics based on students’ evaluation in online education programs : Mauren Moreira Porciúncula da Silva, Suzi Samá Pinto
• C128: Introductory statistics students’ conceptual understanding of variation and measures of variation in a distribution : Rachel Chaphalkar, Cindy Leary
• C129: Exploration of problem solving processes of students with learning disabilities : Megan Mocko, Melissa Crow
• C130: Normal inverse function in teaching inference about population mean and population proportion : Xiaoyi Ji
• C131: Reduced major axis regression: teaching alternatives to least squares : William Harper
• C134: It is time to include data management in introductory statistics : Robert H Carver, Mia Stephens
• C135: Environmental interfaces in teaching statistics : Celso Ribeiro Campos, Otávio Roberto Jacobini, Maria Lúcia Lorenzetti Wodewotzki, Denise Helena Lombardo Ferreira
• C137: Teaching statistics in a crisis zone : Irene David, Hilary Seddon, Jenny Harlow, Jennifer Brown
• C139: Formative assessment and learning analytics in statistics education : Dirk Tempelaar
• C140: Quality engineering: an experience in teaching statistics for engineers : Adelmo Anselmo Martins, Elisa Henning, Marcelo Savio Ramos
• C141: Learning objects for teaching statistics in engineering courses : Elisa Henning, Luciane Mulazani dos Santos, Dátila Cristina Mondini
• C142: Students’ conceptions of average and standard deviation : Véronique Dubreil-Frémont, Christelle Chevallier-Gaté, Noëlle Zendrera
• C143: Meanings of probability in Spanish curriculum for primary school : Emilse Gómez-Torres, J Miguel Contreras
• C144: Development of integrated quantity judgments: means of distributions appear more different than they are : Franca Agnoli, Gianmarco Altoè, Tatiana Marci
• C145: Observations of implementations of an active learning module in introductory statistics : Jeremy Strayer, Nancy McCormick, Natasha Gerstenschlager, Lisa Green, Scott McDaniel, Ginger Holmes Rowell
• C146: Training prospective teachers for teaching of probability at secondary school in Colombia : Emilse Gómez-Torres
• C147: Examining Venezuelan secondary school mathematics teachers’ professional competencies to teach statistics: focusing on the instruction of descriptive statistics : Orlando González
• C148: Simulation illogic repaired : Patricia B. Humphrey
• C149: Preservice teachers’ awareness of variability : Edward Mooney, Dhimitraq Duni, Elisha VanMeenen, Cynthia Langrall
• C150: A glimpse of two year college instructors’ understanding of variation in histograms : Monica Dabos
• C151: Middle and high school teachers’ transformative learning of center : Susan Peters, Jonathan D. Watkins, Victoria Miller Bennett
• C155: Investigation about curricular orientations in teaching statistics in Brazil and Mexico : Hugo Hernandez, Verônica Yumi Kataoka, Claudia Borim da Silva, Irene Cazorla
• C157: An early start on inference : Edith Seier
• C158: Computer-aided graphics to teach eigenvalues and eigenvectors : Jaime Curts
• C159: Sustaining progress in statistics education in the United States through an analysis of the past 30 years of advancement : Katherine Halvorsen, John McKenzie, Jr.
• C160: Exam question evaluation with Item Response Theory : Evert Jan Bakker, Elisabeth Korendijk
• C162: Students’ social representation of statistics in the humanities and social sciences : Jean-Marie Marion, Alain Bihan-Poudec
• C163: Communication and collaboration in support of a significant mathematical learning : Joyce Furlan, Lia Marques Marocci
• C164: Teaching precursors to data science in introductory and second courses in statistics : Nicholas Horton, Ben Baumer, Hadley Wickham
• C167: Attending to students’ thinking on bivariate statistical data at secondary level: two teachers’ pedagogical content knowledge : Sandra Quintas, Rosa Tomás Ferreira, Hélia Oliveira
• C168: Teaching innovations in introductory statistics courses : Ramon Gomez
• C169: High school teachers’ statistical reasoning about comparison of distributions of data in a computer environment : Santiago Inzunsa, José A Juárez
• C171: The professional knowledge of German secondary school teachers about descriptive statistics : Stefanie Schumacher
• C172: Peer assessment as active learning method : Tatjana von Rosen
• C173: The use of web resources in statistics education : Svetlana Tishkovskaya, Gillian Lancaster
• C176: Teaching statistics concepts through stock market contexts : Larry Weldon
• C177: Rethinking the intersection of statistics education and social justice : Lisa Poling, Nirmala Naresh
• C178: On-line homework in probability and statistics: WeBWorK incorporating R : Davor Cubranic, Bruce Dunham, Djun Kim
• C182: How students relate residuals behavior with parameter significance tests in a linear model: A case of study in a higher education Mexican institution : José Luis Ángel Rodríguez Silva
• C183: Stat321, an on-line statistics textbook based on intuitive inferential reasoning : Nicolas Greliche
• C184: A case study of Cypriot primary school students’ use of a dynamic statistics software package for analyzing and interpreting data : Irene Kleanthous, Maria Meletiou-Mavrotheris
• C187: Fostering changes in confidence intervals interpretation : Luisa Andrade, Felipe Fernández, Ingrith Álvarez Alfonso
• C188: Individualised project assessments for statistics courses – the best of both worlds? : Robert Grant, Ahmed Younis
• C189: Statistics content and pedagogy in a course for pre-service secondary math teachers : Kady Schneiter
• C190: Teaching statistics with lectures or activities: a comparative study : Jennifer L Loveland, Kady Schneiter
• C191: Technology tools and success in statistics: interpreting the research : Jason Schenker, Shawn Fitzgerald, Jian Li, Emtiaz Rony
• C192: How is success in statistics moderated by instructional practices used at the university level: interpreting 30+ years of research on the topic : Hanna Wilson, Shawn Fitzgerald, Jian Li, Jason Schenker
• C195: Teaching undergraduates through statistical consulting : Hyun-Joo Kim, K Scott Alberts, Scott Thatcher
• C196: The status of reform in statistics education: A focus on the introductory course : Rossi Hassad
• C197: A 21st century teaching approach in statistics : Nelia S. Ereno, Allen F Vicente
• C198: Assessment of students’ knowledge and skills in learning statistics in the 21st Century : Allen F Vicente, Nelia S. Ereno, Liberty Grace Baay
• C199: Probability and statistics in access exams to Spanish universities : P. Díaz, V. Mier, P. Alonso, Luis J Rodríguez-Muñiz
• C200: Graduate teaching assistants’ beliefs, practices, and preparation for teaching introductory statistics : Nicola Parker, Elizabeth Fry, Joan Garfield, Andrew Zieffler
• C202: Introductory statistics instructors’ practices and beliefs regarding technology and pedagogy : Elizabeth Brondos Fry
• C203: A shiny new opportunity for big data in statistics education : Karsten Maurer
• C206: A graphical illustration of binomial distributions : Kang Sup Lee, Dong Joo Yang
• C208: The interactive submarine: using boxplots as a likelihood approach : Pedro Campos
• C209: Analysis of linear regression in Spanish baccalaureate textbooks : P. Díaz, Luis J Rodríguez-Muñiz
• C210: Just sum the marks: spurious wisdom : Timothy Dunne
• C212: An evaluation of the statistical methods used by business researchers in South African publications : Gary D Sharp, Warren J Brettenny, Chantelle M Clohessy, Catherine G Logie
• C213: Statistical consultation as part of statistics education : Lizelle Fletcher
• C214: The role of lecturers in students’ performance : Klára Kazár
• C215: Sustaining student engagement in a college statistics course through a reflective teaching model using youth statistics : Liza Lorena Jala, Enriqueta Reston
• C216: Teachers’ confidence in teaching statistical ideas : Rosemary Callingham, Jane M. Watson
• C217: The impact of an inverted traditional teaching model on first level statistics students : Fransonet Reyneke, Lizelle Fletcher
• C218: Istat’s new tools in teaching statistics to digital natives : Barbara Ascari, Marina Peci
• C219: Teaching NHST vs Bayesian inference in post-secondary technology programs : John H. Mott, Erin E. Bowen
• C220: Integrating learning technologies for applied statistics in distance education at the graduate level: challenges and strategies : Erin E. Bowen
• C223: What’s missing in teaching probability and statistics: building cognitive schema for understanding random phenomena : Sylvia Kuzmak
• C226: How I learned to stop worrying about it and just teach MBA 5800 (with apologies to Dr. Strangelove) : Alan S Chesen
• C227: Business management students’ attitude and performance in statistics learning in Nigeria Metropolitan College of Technology : Adeyemi D Aromolaran, Abiodun Karim, Emmanuel Ikegwu, Uneke Okoroafor, Yemisi Ajiboye
• C228: Confirmatory and exploratory factor analyses of students’ developmental levels in learning statistics : Rini Oktavia, M. Alejandra Sorto
• C229: Using Calibrated Peer Review™ in introductary statistics courses : Melissa Q Pittard, William S Rayens
• C232: Metonymy as a lens into student understanding of sampling distributions : Stacey Hancock, Jennifer Noll
• C234: IPUMS International: a data resource for statistics education : Patricia Kelly Hall, Lara Cleveland, Matthew Sobek
• C237: Teaching scientific integrity through statistics : Marijtje A.J. Van Duijn, Wendy J. Post
• C238: Teaching hypothesis testing: a necessary challenge : Wendy J. Post, Marijtje A.J. Van Duijn
• C240: Elements of variance analysis, evaluation of difficulties by questionnaire : Osmar D. Vera, Carmen Díaz Batanero
• C242: Developing conceptual understanding: the role of interactive dynamic technology : Gail Burrill
• C244: Invariance and descriptive statistics : Guido del Pino
• C248: Teaching box plots: An intervention using refutational text and multiple external representations : Stephanie Lem, Goya Kempen, Eva Ceulemans, Patrick Onghena, Lieven Verschaffel, Wim Van Dooren
• C249: Is an active learning space better than traditional classroom for learning experience in a first year statistics tutorial class? : Ayse Bilgin, Greg Robertson, David Bulger
• C251: Vergnaud's theory applied to basic school students’ statistical representations : Soledad Estrella, Arturo Mena
• C252: Examining graduate students’ prior mathematics/statistics experiences and their statistics self-perceptions: a third order structural model with latent variable analysis : Karen Larwin
• C254: Designing opportunities for students to reason about the relationship between sources and structures of data : Jennifer Nickell, Hollylynne S. Lee
• C256: Graphical statistics as an option for the improvement of learning in Psychology : Mirian Agus, Maribel Peró-Cebollero, Joan Guàrdia-Olmos, Maria Pietronilla Penna
• C257: Education statistics for professional specialization: use of knowledge at the workplace of postgraduate in statistics : José Paúl Carrasco Escobar
• C258: A comparison of outlier labeling criteria in univariate measurements : Menus Nkurunziza, Lea Vermeire
• C259: Statistical and mathematical self-efficacy of incoming students at a large public university : Ulrike Genschel, Andee Kaplan, Alicia Carriquiry, Elgin Johnston, Wolfgang Kliemann, Kenneth Koehler, Ian Mouzon, Hien Nguyen
• C260: Clickers for engagement in the large undergraduate statistics classroom: do clickers improve final grades? : Krista Wilde
• C261: Teaching statistics to non-statistics majors : Kolentino N. Mpeta, Diteboho Xaba, Ellen Materechera, Mamolahluwa Mokoena
• C262: Overview of prospective mathematics teachers’ probabilistic thinking : Amable Moreno, José María Cardeñoso
• C263: Real-time educational interpreting in statistics : Thomas L. Berning
• C264: The application of blended learning to large groups : Ivona E. Contardo-Berning
• C266: The garden sprinkler: an interactive web-based application for teaching design of experiments : Bart De Ketelaere, Karl Siebertz, David van Bebber, Koen Rutten
• C270: Using the SETS instruments to investigate sources of variation in levels of pre-service teacher efficacy to teach statistics : Leigh Harrell-Williams, M. Alejandra Sorto, Rebecca Pierce, Larry Lesser, Teri Jo Murphy
• C271: Graduate students’ learning experience : Josefina Almeda
• C273: Assessing dimensionality of the communication, language and statistics survey: a multi-group analysis with introductory statistics students near the US-Mexico border : Amy Wagler, Lawrence M. Lesser
• C274: Thinking out of the box in teaching statistics : Tim Low
• C275: Teaching statistics in a mathematics course in middle school: interdisciplinarity, really? : Annie Savard, Dominic Manuel
• C276: A view of statistics education research in Brazilian extreme south coast : Mauren Moreira Porciúncula da Silva, Daiane Lemos de Sá, Suzi Samá Pinto, Lidiane Santos de Freitas
• C277: Twitter as a learning tool in higher education : Juan M. López-Zafra, Sonia de Paz-Cobo
• C279: Students' inferential reasoning about sample size : Ethan Brown
• C283: Against All Odds: Inside Statistics : Marsha Davis
• C284: A suggested theoretical basis for teacher learning in statistics : Fayez Mourad Mina
• C286: Teaching statistics in the Arab countries: the ambitions and the needs : Hanan Innabi
• C287: Enhancing statistical literacy and thinking through analysis of scientific journal articles : Mahtash Esfandiari, Kekona Sorenson, Dave Zes, Kevin Nichols
• C289: Bridging the gap of manpower training for statistics education in Nigerian colleges of education: an empirical evaluation of some selected colleges in south-western Nigeria : Oluokun Kasali Agunloye
• C290: Teaching critical thinking through the introductory statistics class : Mark Ferris, Sherri Cheng, Frank Wang, Jessica Perolio
• C291: Disabilities people: Quotas Law which may exist behind the RAIS statistics and census of IBGE : Paulo Oliveira

Posters

• P1: Probability heuristics in year 10 students — a New Zealand study : Howard Edwards
• P2: A first course in data mining: sustaining statistical education in the modern business curriculum : Deborah Gougeon
• P3: Changing how we use statistical lexicon: To the hilt : Diane Fisher, Jennifer Kaplan, Neal Rogness
• P4: Predictors of postgraduate asmission and students’ learning experiences in the school of statistics : Josefina Almeda
• P5: The impact of clicker technology in a large introductory statistics class environment : Zeny F. Mateo, Wan-Chen Lee
• P6: Learning statistics in an undergraduate interdisciplinary research setting — the CRAWL experience : Edith Seier, Joyner, Moore, Jones, Joplin
• P7: Teaching the exact test for proportions : Edith Seier
• P8: Comics and cartoons: sustainability in statistics education : Liza Lorena Jala
• P9: Assessment of different methods of teaching school children mathematical operations of two four-digit numbers using one way multivariate analysis of variance : Umeh Edith Uzoma
• P10: The “lady” has a name: teaching history of statistics using Salsburg with corrections : Kirk Anderson, Phyllis Curtiss
• P11: Comparison of student flow in different colleges of Kuwait University using absorbing markov analysis : Shafiqah A. Al-Awadhi
• P12: The power and ease of examples and exercises using a multivariate least squares computer program : Richard Gorsuch
• P13: Investigation of AP statistics students’ understanding of technical terminology with possible lexical ambiguities : Douglas Whitaker, Tim Jacobbe, Steve Foti
• P14: Students’ understanding of randomization-based inference : Catherine Case, Melanie Battle, Tim Jacobbe
• P15: The interaction between government agencies and the university in statistics education : Adriana D’Amelio, Silvana Dea Labat
• P16: Quality engineering: an experience in teaching statistics for engineers : Elisa Henning, Adelmo Anselmo Martins, Marcelo Savio Ramos
• P17: Using hierarchical models in assessment of teaching methods: an initial illustration : Jillian Lyon, Ulrike Genschel, Mark Kaiser
• P18: Teaching future high school teachers to teach statistics : Nancy Boynton
• P19: A proposal by ISTAT to support the teaching of statistics in primary school : Nadia Caporrella, Silvia Da Valle, Luciana Micucci, Susi Osti
• P20: Redesigning an undergraduate statistics course using a flipped classroom model : Kristin Harvey
• P22: A review of statistics education in KENYA : Beatrice Wanjiku Gichohi
• P23: Development of statistical literacy in undergraduate students : Diana Keosayian, Elizabeth Johnson
• P24: Teaching statistics - teaching maths An experimentation route : Gaetana Bartolomei, Ornella Giambalvo
• P25: Professional develpoment courses in statistical training institute : HyunSik Hwang, Kyung Ae Park
• P26: Evidence-based policy making and statistical education : Kyung Ae Park
• P27: A psychometric analysis of the goals and outcomes associated with learning statistics (GOALS) instrument : Anelise Sabbag, Andrew Zieffler
• P28: Students in need of an attitude adjustment? : April Kerby, Jacqueline Wroughton
• P29: Illustrating inference in an introductory statistics course using simulation : Jeff Kollath
• P30: Applying teaching for understanding in statistics : Teresita Evelina Terán, Diana Kohan
• P31: Epidemic: a computer based training environment for informal inferential reasoning : Joachim Engel, Tim Erickson
• P32: A case study of an elementary school student’s informal inferential reasoning in the paper helicopter experiment : Takashi Kawakami
• P33: Design of anticipatory tasks along a hypothetical learning trajectory for understanding probability distribution : Darcy Conant
• P34: Using actionable intelligence to enhance student success in introductory statistics courses : Brenda Gunderson, Karen Nielsen
• P35: On confidence intervals from permutation tests : Mara Tableman, Minh Nguyen, Michael Ernst
• P36: High school teachers’ conditional probability content knowledge : Adam Molnar
• P37: Attention to details: does it facilitate or impede learning : William Rybolt
• P38: Probability and statistics knowledge for teaching, in school teachers preparation in chilean universities : Eugenio Chandía, Anita Araneda
• P39: Assessment on the confidence levels of educators teaching statistics in South Africa : Desiree Timmet
• P40: Preliminary results of the effects and roles of fun in introductory statistics classes : Lawrence Lesser, Dennis Pearl, Reynaldo Reyes, John Weber
• P41: Two course-wide assessment tools for introductory statistics : Christopher E. Barat
• P42: Using R to create assessments for course management systems : Nichole Andrews, Bradford Dykes
• P43: Keeping the momentum: sustaining interest in statistics lectures for non-statisticians : Angela Wade, Eirini Koutoumanou, Vicki Aldridge
• P44: Advice for using faculty connections to create research opportunities for undergraduates : Ivan Ramler, Jessica Chapman
• P45: Towards a more conceptual way of understanding and implementing inferential rules : Johanna Hardin, Thalia Rodriguez
• P47: The challenges of implementing a randomization approach to introductory statistics in the high school setting : Brandon Hanson, Natasha Gerstenschlager
• P48: Exploring statistical literacy in Northeast China: finding a path from the classroom to the workplace : Robert Giebitz
• P49: Factors of sustainability in statistics education in Ukraine : Ruslan Motoryn, Motoryna Tetiana
• P50: On statistics education innovation from statistics development perpectives : Yu Zhu, Meng Wang
• P51: Education and training statistics in Russia : Olga Bashina, Pavel Smelov
• P52: Experience of carrying the National Statistical Olympiad in Russia : Pavel Smelov, Elena Egorova
• P53: Discovery projects in elementary statistics: curriculum materials and measurement of student outcomes : Dianna J. Spence, Gregg Velatini
• P54: Learning statistics based upon multiple theories of probability : Chong Ho Yu, Anna Yu