BOOKS
Handbook of research on statistics teaching and learning
Dani Ben-Zvi, Katie Makar and Joan Garfield (eds.), Springer 2018
Reasoning about uncertainty: learning and teaching informal inferential reasoning
Andy Zieffler and Elizabeth Fry (eds.), Catalyst Press. 2015 (Outcome of SRTL-8)
Developing students’ statistical reasoning: connecting research and teaching practice
Joan Garfield and Dani Ben-Zvi, Springer 2008
Ben-Zvi, D. & Garfield, J. (Eds.). The challenge of developing statistical literacy, reasoning, and thinking. Dordrecht, the Netherlands: Kluwer Academic Publishers. (Outcome of SRTL-1 and SRTL-2)
http://wikiet.edu.haifa.ac.il/images/f/f7/SRTL_book_front-matter.pdf
JOURNALS
SRTL 13:
Upcoming: A Special Issue in ZDM, 57(1), Developing students’ reasoning with data and data-ing; Editors.: Jill Fielding, Katie Makar, Dani Ben-Zvi; https://link.springer.com/journal/11858
SRTL 12:
A Special Issue in Teaching Statistics, Volume 45, Issue S1, Special Issue: Teaching Data Science and Statistics: Re-thinking Learners’ Reasoning with Non-traditional Data; Editors: Jennifer Noll, Sibel Kazak, Lucía Zapata-Cardona, Katie Makar; https://onlinelibrary.wiley.com/toc/14679639/2023/45/S1
SRTL 11:
A Special Issue in MTL Studies presented in SRTL-11 will be published in a special Issue of the journal Mathematical Thinking and Learning. The theme of this issue is: New ways of interacting with data, context and chance in statistical modeling processes. The Guest Editors are: Jennifer Noll, TERC (USA); Susanne Schnell, Goethe University Frankfurt (Germany); Rob Gould, UCLA (USA); and Katie Makar, The University of Queensland (Australia). Expected publication date is July 2020.
SRTL 10:
Special issue in ZDM on “Innovations in Statistical Modelling to Connect Data, Chance and Context.” The guest editors of this Special issue are: Maxine Pfannkuch and Stephanie Budgett, Auckland University, New Zealand; and Dani Ben-Zvi, Haifa University, Israel.
Articles in this Special issue:
Innovations in statistical modeling to connect data, chance and context
Maxine Pfannkuch, Dani Ben-Zvi, Stephanie Budgett
Dot plots and hat plots: supporting young students emerging understandings of distribution, center and variability through modeling
Jill Fielding-Wells
Statistical modelling and repeatable structures: purpose, process and prediction
Katie Makar, Sue Allmond
Sixth grade students’ emerging practices of data modelling
Sibel Kazak, Dave Pratt, Rukiye Gökce
Statistical modeling to promote students’ aggregate reasoning with sample and sampling
Keren Aridor, Dani Ben-Zvi
The role of model comparison in young learners’ reasoning with statistical models and modeling
Michal Dvir, Dani Ben-Zvi
Developing a statistical modeling framework to characterize Year 7 students’ reasoning
Anne Patel, Maxine Pfannkuch
Students’ construction and use of statistical models: a socio-critical perspective
Lucía Zapata-Cardona
Middle school students’ reasoning about data and context through storytelling with repurposed local data
Michelle Hoda Wilkerson, Vasiliki Laina
Elementary preservice teachers’ reasoning about statistical modeling in a civic statistics context
Rolf Biehler, Daniel Frischemeier, Susanne Podworny
Every rose has its thorn: secondary teachers’ reasoning about statistical models
Nicola Justice, Andrew Zieffler, Michael D. Huberty, Robert delMas
Students’ use of narrative when constructing statistical models in TinkerPlots
Jennifer Noll, Kit Clement, Jason Dolor, Dana Kirin, Matthew Petersen
Modeling and linking the Poisson and exponential distributions
Stephanie Budgett, Maxine Pfannkuch
Statistics students’ identification of inferential model elements within contexts of their own invention
Matthew D. Beckman, Robert delMas
SRTL 9:
Special issue in Statistics Education Research Journal (SERJ) on “Statistical Reasoning about Models and Modelling in the Context of Informal Statistical Inference”. The guest editors of this Special issue are: Rolf Biehler, Daniel Frischemeier and Susanne Podworny (University of Paderborn, Germany)
Articles in this Special issue:
Computational Modelling and Children’s Expressions of Signal and Noise
Janet Ainley and Dave Pratt
The Co-Emergence of Aggregate and Modelling Reasoning
Keren Aridor and Dani Ben-Zvi
Modeling Signal-Noise Processes Supports Student Construction of a Hierarchical Image of Sample
Richard Lehrer
A Modeling Approach to the Development of Students’ Informal Inferential Reasoning
Helen M. Doerr, Robert delMas, and Katie Makar
Students’ Emergent Articulations of Statistical Models and Modeling in Making Informal Statistical Inferences
Hana Manor Braham and Dani Ben-Zvi
Students’ Emergent Modelling of Statistical Measures—A Case Study
Christian Büscher and Susanne Schnell
Promoting Modelling and Covariational Reasoning among Secondary School Students in the Context of Big Data
Einat Gil and Alison L. Gibbs
Modeling as a Core Component of Structuring Data
Clifford Konold, William Finzer, and Kosoom Kreetong
TinkerPlot™ Model Construction Approaches for Comparing Two Groups: Student Perspectives
Jennifer Noll and Dana Kirin
Elementary Preservice Teachers’ Reasoning about Modeling a “Family Factory” with Tinkerplots—A Pilot Study
Rolf Biehler, Daniel Frischemeier, and Susanne Podworny
Pre-Service Mathematics Teachers’ Use of Probability Models in Making Informal Inferences about a Chance Game
Sibel Kazak and Dave Pratt
An Analysis of Secondary Teachers’ Reasoning with Participatory Sensing Data
Robert Gould, Anna Bargagliotti, and Terri Johnson
SRTL 7:
Special issue in Educational Studies in Mathematics (March 2015, 88, 3):
Ben-Zvi, D., Bakker, A., & Makar, K. (2015). Learning to reason from samples. Educational Studies in Mathematics, 88(3), 291-303.
Konold, C, Higgins, T.,Russell, S. J.,Khalil, K. (2015). Data seen through different lenses. Educational Studies in Mathematics, 88(3),305-325.
Garfield, J., Le, L., Zieffler, A., Ben-Zvi, D. (2015). Developing students’ reasoning about samples and sampling variability as a path to expert statistical thinkingEducational Studies in Mathematics, 88(3), 327-342.
Pfannkuch, M., Arnold, P., & Wild, C. J. (2015). What I see is not quite the way it really is: students’ emergent reasoning about sampling variability. Educational Studies in Mathematics, 88(3), 343-360.
Meletiou-Mavrotheris, M., Paparistodemou, E. (2015). Developing students’ reasoning about samples and sampling in the context of informal inferences. Educational Studies in Mathematics, 88(3), 385-404.
Ainley, J., Gould, R., & Pratt, D. (2015). Learning to reason from samples: commentary from the perspectives of task design and the emergence of “big data”. Educational Studies in Mathematics, 88(3), 405-412.
Noll, J., Hancock, S., (2015). Proper and paradigmatic metonymy as a lens for characterizing student conceptions of distributions and sampling. Educational Studies in Mathematics, 88(3), 361-383.
SRTL 6:
Special issue Mathematical Thinking and Learning 2011 Volume 13, Numbers 1-2
ISSN 1098-6065, http://www.informaworld.com/smpp/title~content=t775653685
EDITORIAL
The Role of Context in Developing Reasoning about Informal Statistical Inference
Katie Makar and Dani Ben-Zvi (Guest Editors)
EDITORIAL
The Role of Context in Developing Reasoning about Informal Statistical Inference
Katie Makar and Dani Ben-Zvi
ARTICLES
Lessons from Inferentialism for Statistics Education
Arthur Bakker and Jan Derry
The Role of Context in Developing Informal Statistical Inferential Reasoning:A Classroom Study
Maxine Pfannkuch
The Role of Context Expertise When Comparing Data
Cynthia Langrall, Steven Nisbet, Edward Mooney, and Sinchai Jansem
Conceptual Challenges in Coordinating Theoretical and Data-centered Estimates of Probability
Cliff Konold, Sandra Madden, Alexander Pollatsek, Maxine Pfannkuch,Chris Wild, Ilze Ziedins, William Finzer, Nicholas J. Horton, and Sibel Kazak
Explanations and Context in the Emergence of Students’ Informal Inferential Reasoning
Einat Gil and Dani Ben-Zvi
Statistically, Technologically, and Contextually Provocative Tasks: Supporting Teachers’ Informal Inferential Reasoning
Sandra R. Madden
Authentic Practices as Contexts for Learning to Draw Inferences Beyond Correlated Data
Adri Dierdorp, Arthur Bakker, Harrie Eijkelhof, and Jan van Maanen
The Reasoning Behind Informal Statistical Inference
Katie Makar, Arthur Bakker, and Dani Ben-Zvi
SRTL 5:
Special issue Statistics Education Research Journal, Volume 7 Number 2, November 2008
http://www.stat.auckland.ac.nz/~iase/publications.php?show=serjarchive
Introducing the Special Issue on Informal Inference
Dave Pratt and Janet Ainley (Guest Editors)
Reasoning about Informal Statistical Inference: One Statistician’s ViewInvited
Allan J. Rossman
Statistical Cognition: Towards Evidence-Based Practice in Statistics and Statistics Education
Ruth Beyth-Maron, Fiona Fidler, and Geoff Cumming
A Framework to Support Research on Informal Inferential Reasoning
Andrew Zieffler, Joan Garfield, Robert delMas, and Chris Reading
Exploring Beginning Inference with Novice Grade 7 Students
Jane M. Watson
Developing Young Students’ Informal Inference Skills in Data Analysis
Efi Paparistodemou and Maria Meletiou-Mavrotheris
Local and Global Thinking in Statistics Inference
Dave Pratt, Peter Johnston-Wilder, Janet Ainley, and John Mason
Statistical Inference at Work: Statistical Process Control as an Example
Arthur Bakker, Phillip Kent, Jan Derry, Richard Noss, and Celia Hoyles
SRTL 4:
Special issue Statistics Education Research Journal, Volume 5 Number 2, November 2006
http://www.stat.auckland.ac.nz/~iase/publications.php?show=serjarchive
Reasoning about distribution: A complex process
Guest Editors: Maxine Pfannkuch and Chris Reading
The Concept of Distribution
Chris Wild
Comparing Box Plot Distributions: A Teacher’s Reasoning
Maxine Pfannkuch
An Emerging Hierachy of Reasoning About Distribution: From a Variation Perspective
Chris Reading and Jackie Reid
The Role of Causality in the Co-ordination of Two Perspectives on Distribution Within a Virtual Simulation
Theodosia Prodromou and Dave Pratt
Using Data Comparisons to Support a Focus on Distribution: Examining Preservice Teachers’ Understandings of Distribution When Engaged in Statistsical Inquiry
Aisling Leavy
SRTL 3:
Special issue Statistics Education Research Journal, Volume 3 Number 2, November 2004
http://www.stat.auckland.ac.nz/~iase/publications.php?show=serjarchive
Research on Reasoning about Variability: A Forward
Dani Ben-Zvi and Joan Garfield (Guest Editors)
Variability: One Statistician’s View
Rob Gould (Invited)
Strategies for Managing Statistical Complexity with New Software Tools
James Hammerman and Andee Rubin
Reasoning about Variability in Comparing Distributions
Dani Ben-Zvi
Reasoning about Shape as a Pattern in Variability
Arthur Bakker
Student Description of Variation while Working with Weather Data
Chris Reading