See another day’s programme:
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Tuesday
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Friday
Detailed programme for Wednesday 16th July

Note: Only presenters are shown for Invited and Contributed Papers.
The full list of authors can be seen from the Session link in the left column.


(This schedule is kept up-to-date and consequently changes may occur.)


08:30-09:10P2: Focus on Posters: meet the authorsHumphreys
09:15-10:15Plenary Session
PlenaryRachel Fewster*Teaching statistics to Real People: adventures in social stochasticsProchnow
Chair: Timothy Dunne
10:20-10:50Refreshments
10:55-12:25Parallel Sessions
Invited
Session 1A
Building the capacity of mathematics and science teachers to teach statistics
Session organizer and Chair: Tim Jacobbe
HCCC:
Doyle
Jane Watson*Curriculum expectations for teaching science and statistics
Christine Franklin*The Statistical Education of Teachers (SET): an American Statistical Association policy document
Carmen Batanero*Building high school pre-service teachers’ knowledge to teach correlation and regression
Invited
Session 3A
Statistics instructors’ content knowledge
Session organizer and Chair: Susan Peters
1899:
Bright Angel
Maria Meletiou-Mavrotheris*Developing pre-service teachers’ technological pedagogical content knowledge (TPACK) of sampling
Cláudia Borim da Silva*Analysis of teachers’ understanding of variation in the dot-boxplot context
Jennifer L Green*Beyond calculations: fostering conceptual understanding in statistics graduate teaching assistants
Invited
Session 5B
Evidence-based management
Session organizer: Irena Ograjenšek
Chair: Kazunori Yamaguchi
HCCC:
Rees
Shirley Coleman*The prevalence of statistics and data mining in management journals
Sharleen Forbes*Bringing the workplace into a National Certificate in Official Statistics
Iddo Gal*How do school principals understand and use the statistics in reports from national large-scale assessments?
Invited
Session 6E
Modeling distributions to connect chance processes, data production, and data distributions
Session organizer and Chair: Hollylynne Stohl Lee
1899:
Clear Creek
Richard Lehrer*Model-based informal inference
J Todd Lee*Visual representations of empirical probability distributions when using the granular density metaphor
Theodosia Prodromou*Multidirectional modelling for fostering students’ connections between real contexts and data, and probability distributions
Invited
Session 8I
Research on risk literacy
Session organizer and Chair: Laura Martignon
HCCC:
Agassiz
David Spiegelhalter*Getting alternative representations for risk into the school syllabus
Christoph Till*Risk literacy: first steps in primary school
Kathryn Laskey*Comparing fast and frugal trees and Bayesian networks for risk assessment
Invited
Session 9C
The emerging concepts of “data science” and “big data” for educational purposes
Session organizer: Robert Gould, Hadley Wickham
Chair: Robert Gould
HCCC:
Fremont
James Ridgway*Exploring “white flight” via open data and big data
Amelia McNamara*Teaching data science to teenagers
Daniel Kaplan*Integrating big data into the science curriculum
Contributed
Session C10A
Contributed papers
Chair: Pedro Campos
Drury:
Kendrick
Hugo Hernandez*Investigation about curricular orientations in teaching statistics in Brazil and Mexico
Nelia S. Ereno*A 21st century teaching approach in statistics
Luis J Rodríguez-Muñiz*Analysis of linear regression in Spanish baccalaureate textbooks
Liza Lorena Jala*Sustaining student engagement in a college statistics course through a reflective teaching model using youth statistics
Contributed
Session C10B
Contributed papers
Chair: Lisbeth Cordani
Drury:
O'Leary
Susana Colaço*Learning statistics in the first grades
Katherine Halvorsen*Sustaining progress in statistics education in the United States through an analysis of the past 30 years of advancement
Hanan Innabi*Teaching statistics in the Arab countries: the ambitions and the needs
Annie Savard*Teaching statistics in a mathematics course in middle school: interdisciplinarity, really?
Contributed
Session C10C
Contributed papers
Chair: Jocelyn Cumming
Drury:
McMillan
Rachel Chaphalkar*Introductory statistics students’ conceptual understanding of variation and measures of variation in a distribution
Robert H Carver*It is time to include data management in introductory statistics
Jeremy Strayer*Observations of implementations of an active learning module in introductory statistics
Nicholas Horton*Teaching precursors to data science in introductory and second courses in statistics
12:30Lunch boxes followed by excursions