ICOTS 10 2018

Kyoto, Japan

Proceedings

• Welcome from the IASE President : Gail Burrill
• Proceedings Editor’s Preface : M. Alejandra Sorto

Keynotes

• Education of the grammar of science for sciences and society : Hiroe Tsubaki
• Cultivating Creativity in Data Work : Hilary Parker
• See how the rest of the world lives, sorted by income : Anna Rosling Rönnlund
• Through a glass darkly : Chris Wild
• Combining 360 degree reflections for looking forward : Helen MacGillivray

Excellence Awards for Early Career Papers

Winner

• Susanne Schnell: Integrating Theoretical and Empirical Considerations – Young Students’ Understanding of the Empirical Law of Large Numbers

Highly commended papers

• Pip Arnold: Critiquing Investigative Questions
• Ethan C. Brown: Developing Students’ Causal Understanding of Sampling Variability: A Design Research Study
• Takashi Kawakami: How Models and Modelling Approaches Can Promote Young Children’s Statistical Reasoning
• Rachael Passmore: Time Series – Its Place in the Secondary School Curriculum

Topic 1: Statistics education: Looking back, looking forward

1A: An Innovative Educational Model of Elementary Statistics Course with MOOC, PBL, and AI (panel)

• 1A1: Overview of an Educational Model of Elementary Statistics for the Data Science Program of Shiga University : Shizue Izumi, Michinori Hatayama

1B: Statistical education software: Looking back and looking forward

• 1B1: Design principles, realizations and uses of software supporting the learning and the doing of statistics – A reflection on developments since the late 1990s : Rolf Biehler
• 1B2: Imagining the future of statistical education software : Amelia McNamara
• 1B3: Should all statistics students be programmers? : Hadley Wickham

1C: Statistics Education: What, how and with whom?

• 1C1: GAISEing Backward and Forward : Megan Mocko, Michelle Everson
• 1C2: Confounding and Cornfield: Back to the Future : Milo Schield
• 1C3: The Practice of Statistics at School: Growing Collaboration across Sectors : Jane Watson, Christine Franklin, J. Michael Shaughnessy

1D: Out of the past and into the future: a global perspective

• 1D1: Igniting the statistical spark in the social sciences : Rhys Jones
• 1D2: The challenges of teaching statistics to undergraduate business and economics students In Spain : Luis F. Rivera-Galicia
• 1D3: The Future of Statistics Education from the Perspective of Educational Practices in New Zealand : Hiroto Fukuda

1E: Assessment: its lessons and effects

• 1E1: Improving student learning and instructional effectiveness through the innovative use of automated analysis of formative assessments : Alex Lyford, Jennifer Kaplan
• 1E2: Real-world contexts in statistics components of UK mathematics examinations: aiming forward, walking backwards : James Nicholson, Jim Ridgway
• 1E3: Research on statistical projects: looking for the development of statistical literacy, reasoning and thinking : Ana Gómez-Blancarte, Alberto Santana

1F: Statistics as a Liberal Art and the Real World

• 1F1: Rethinking the statistics curriculum: Holistic, purposeful and layered : Katie Makar
• 1F2: Statistics IS a liberal arts major : K. Scott Alberts, Hyun-Joo Kim, Jillian Downey
• 1F3: Teaching Statistics for Sustainability : Hanan Innabi

1G: Backwards and forwards with research

• 1G1: The nature and use of theories in statistics education – looking back, looking forward : Per Nilsson, Maike Schindler
• 1G2: Storytelling and Teaching Statistics : Carl Sherwood
• 1G3: Impact of non-cognitive interventions on the performance of women, minority and international students in Introductory Statistics : Cindy van Es, Ritesh Shinde

1H: Data science, technology and the future

• 1H1: Leading change: Developing a new Applied Data Science programme : Jennifer Brown
• 1H2: Data Visualization for the New Age: An Experimental Study Exploring the Merits of Human Perception on Visualization Techniques for Improved Statistical Communication : Patricia Rose Donato, Isabella Benabaye, Dominic Dayta, Sean Oliver Escalante
• 1H3: Using Web Apps in the classroom : Sharleen Forbes, John Harraway, Bryndl Hohmann-Marriott

1I: The significance of establishment of Japanese Inter-organizational Network for Statistics Education

• 1I1: The role of Japanese Inter-organizational Network for Statistics Education (JINSE) : Yasuto Yoshizoe
• 1I2: New undergraduate departments and programs of data science in Japan : Akimichi Takemura
• 1I3: Challenges in developing real-world data driven business environment to create new business model and practice for data scientists in artificial intelligence : Takuya Kudo, Matsui Kenichi, Shun Yoshida, Michael Munn, Ozlem Celik-Tinmaz, Michiko Watanabe

Topic 2: Statistics education at the school level

2A: Learning to reason with statistical models and modeling at the school level (Part 1)

• 2A1: Scaffolding Year 8 students’ statistical modelling reasoning using Follow Up Tasks to a Model Eliciting Activity : Anne Patel, Maxine Pfannkuch
• 2A2: Teacher assistance in modeling chance processes : Panchompoo Wisittanawat, Richard Lehrer
• 2A3: Model Comparisons as a means of providing an informal quantitative estimation for statistical uncertainty : Michal Dvir, Dani Ben-Zvi

2B: Engaging young learners in using models and modelling in data investigations (Modelling Part 2)

• 2B1: Supporting young students emerging statistical understandings of centre through modelling : Jill Fielding-Wells, Judith Hillman
• 2B2: The modelling path for informal inferential reasoning : Lucía Zapata-Cardona
• 2B3: Young students’ ways of constructing and evaluating statistical models : Sibel Kazak, David Pratt, Rukiye Gökce

2D: A perspective on statistics education from three different countries

• 2D1: Indonesian students’ experience with real-life data and cross-border collaboration: What does the graph say? : Russasmita Sri Padmi, Fina Hanifa Hidayati, Mutiatul Hasanah
• 2D2: A Workshop in Pakistan on Teaching Statistical Inference Through a Freely Available Online Software : Saleha Naghmi Habibullah
• 2D3: Using ICT’s for to Introduce to Statistic : Carlos Mantilla

2E: Linking research and practice in teaching and learning statistics at the school level

• 2E1: Three paradigms to develop students' statistical reasoning : Dani Ben-Zvi
• 2E2: Students' reasoning about association of categorical variables : Stephanie Casey, Rick Hudson, Lauren Ridley
• 2E3: Making the Connections: From Statistics Education Research to Teaching Advice : Rosemary Callingham, Jane Watson, Dianne Siemon

2F: Perspectives on statistics education with a focus in primary schools

• 2F1: Is data a quantitative thing? An analysis of the concept of the mode in textbooks for grade 4-6 : Karin Landtblom
• 2F2: Ingenuity and challenges to incorporate statistical-inquiry process into statistics lessons in primary schools: The case of Japan : Takashi Kawakami, Kazuhiro Aoyama
• 2F3: Informal Statistical Inference and Pre-service Primary School Teachers: The Development of Content Knowledge in Teacher College Education : Arjen de Vetten, Judith Schoonenboom, Ronald Keijzer, Bert Van Oers

2G: Probability and modelling across the schooling levels

• 2G1: How models and modelling approaches can promote young children’s statistical reasoning : Takashi Kawakami
• 2G2: Classroom design to judge by statistical probability in junior high school : Norihiro Nishinaka, Atsushi Yoshikawa
• 2G3: Improving Statistical Pedagogy Among K to 12 Mathematics Teachers in the Philippines : Enriqueta Reston, Carmelita Loquias

2H: Perspectives on statistics education with a focus in secondary schools - session 1

• 2H1: Statistical contents and lessons in the Japanese curriculum of mathematics for lower secondary schools : Shinichiro Matsumoto, Kazuhiro Aoyama
• 2H2: Critiquing investigative questions : Pip Arnold, Maxine Pfannkuch
• 2H3: Time Series – its place in the secondary school curriculum : Rachel Passmore

2I: Perspectives on statistics education with a focus in secondary schools - session 2

• 2I1: Introduction of hypothesis testing through an informal inference approach in a Mexican high school : Eleazar Silvestre Castro, Victor Garcia, Ernesto Sánchez
• 2I3: High school, TinkerPlots, Fathom… and Independence and ANOVA. How come? : Hugo Hernández

2J: Active-learning approach for statistics in school education

• 2J1: Using Box-and-Whisker Plot in Problem Solving Learning : Kimie Kazama, Chieko Matsumoto
• 2J2: On Statistical Education in Secondary Mathematics Education in Japan : Hisao Oikawa, Shunichi Nomura
• 2J3: Practice of the Improvement in Statistical Problem-Solving Faculty through the Analysis of Regional Data : Yusuke Nagumo

Topic 3: Statistics education at the post-secondary level

3A: Developing undergraduate data science programs grounded in statistics

• 3A1: Data Science for all: A stroll in the foothills : Jim Ridgway, Rosie Ridgway, James Nicholson
• 3A2: Building a foundation in statistics in the era of data science : Alison Gibbs
• 3A3: Challenges and opportunities for undergraduate data science major and minor degree programs : Johanna Hardin, Nicholas Horton

3B: Randomisation and bootstrapping: the quick way to inference

• 3B1: Development of a tool to assess students’ conceptual understanding in introductory statistics : Nathan Tintle, Jill VanderStoep
• 3B2: Student Gains in Conceptual Understanding in Introductory Statistics With and Without a Curriculum Focused on Simulation-Based Inference : Beth Chance, Stephanie Mendoza, Nathan Tintle
• 3B3: Connecting Intuitive Simulation-Based Inference to Traditional Methods : Robin Lock, Kari Lock Morgan, Patti Frazer Lock

3C: Modern data and visualizations in the introductory statistics course

• 3C1: Exploring modern data in a large introductory statistics course : Anna-Marie Fergusson, Liza Bolton
• 3C2: Keeping it Real with Data Visualization : Volker Kraft, Rob Carver
• 3C3: Students’ Understanding of Data Visualizations : Charlotte Bolch, Tim Jacobbe

3D: Preparing pre-service statistics teachers across the grade levels

• 3D2: Indicators of didactical suitability to evaluate the statistical training of future Chilean mathematics teachers : Felipe Ruz, José Miguel Contreras, Elena Molina-Portillo
• 3D3: Statistical Understanding of Pre-service Elementary Teachers : Rachel Chaphalkar

3E: Students’ negative attitudes towards statistics: an arduous challenge

• 3E1: Attitudes towards Research as a source for negative Statistics Attitudes : Florian Berens
• 3E3: The views of undergraduate students about their introductory statistics course process : Zeynep Medine Özmen, Adnan Baki

3F: Statistical computing and communication

• 3F1: Improving Statistical Communication in Statistical Computing Courses : Hunter Glanz, Shannon Pileggi
• 3F2: Defining the relationship between statistical thinking and statistical computing : Victoria Woodard
• 3F3: Statistics as rhetoric: why a statistics education must incorporate communication skills : Brad Quiring

3G: Developing understanding of statistical concepts: From undergraduate students to pre-service mathematics teachers

• 3G1: An analysis of patterns of classroom talk in an IT environment : Ken Li, Merrilyn Goos
• 3G2: Students’ preferences when choosing data Sets with different characteristics : Johannes Schulz, Amy Masnick, Burkhard Priemer
• 3G3: Enhancing civic statistical knowledge of secondary preservice teachers for mathematics : Susanne Podworny, Daniel Frischemeier, Rolf Biehler

3H: Distributions to spatial statistics: New approaches to teaching statistic

• 3H1: Developing students’ causal understanding of sampling variability: A design research study : Ethan Brown, Robert delMas
• 3H2: Learning through Induced Errors: A Garden-path Approach to Introductory Statistics : John Blake
• 3H3: Using a problem-driven approach for teaching statistics at the African Institute for Mathematical Sciences : Emanuele Giorgi

Topic 4: Improving teaching and capacity in statistics education

4A: Statistical education: the education of teachers and children

• 4A2: Professional development programs for statistics teachers: the role of reflection : Difariney González-Gómez, Lucía Zapata-Cardona
• 4A3: Brazilian research contributions to the investigation field and to the practice in statistics education in early childhood : Roberta Buehring, Regina Célia Grando
• 4A4: Creative insubordination and the argumentative process in Statistical Education in early childhood : Solange Aparecida Corrêa, Celi Espasandin Lopes

4B: An Inquiry Teaching Environment for Data Producers: Statistics Tasks for Elementary Years of Schooling

• 4B1: Early Childhood Experiences In Inferential Statistics Using An Inquiry Approach : Debra Mcphee, Katie Makar
• 4B2: Data representations in a STEM context: The performance of catapults : Noleine Fitzallen, Jane Watson, Suzie Wright, Bruce Duncan
• 4B3: Scaffolding data conversations in a primary classroom : Sue Allmond, Katie Makar

4C: ISLP improving teaching and capacity in statistics education in Ibero-America

• 4C1: What a wonderful world: Portugal in the international posters competition : Maria Nascimento, Pedro Campos, José Alexandre Martins
• 4C2: The math textbook, a support for the ISLP? : Audy Salcedo
• 4C3: Narratives of Brazilian participants in the International Posters Competition : Suzi Samá, Mauren Porciúncula, Claudette Vendramini

4E: Teachers’ knowledge and curriculum

• 4E1: Assessing the association between quantitative maturity and student performance in an introductory statistics class: simulation-based vs non simulation-based : Jill VanderStoep, Olivia Couch, Cassandra Lenderink
• 4E2: Secondary school teachers’ knowledge of the standard deviation concept : Sylvain Vermette
• 4E3: Capacity Building of Statistics Teachers through Mentoring and other Innovative Ways : Shirlee Ocampo, Bladimir Ocampo

4F: Teachers, their questions, and their interpretations

• 4F1: Teaching Average Through Implementing Cognitively Demanding Statistical Tasks : Vuslat Şeker
• 4F2: Exploration of preschool teachers’ representativeness notions of statistical graphs : José Antonio Orta Amaro, David Alfonso Paez, José Antonio Altamirano Abad, Eleazar Silvestre Castro
• 4F3: College Instructors’ Attitudes toward Confidence Intervals : Hyung Won Kim, Aaron Wilon, Ho Kyoung Ko

4G: Professional Development Programs

• 4G1: Evaluating the quality of the Master’s Program in Statistics: a study of the curriculum effect on the quality of students' master theses : Tatjana von Rosen
• 4G2: What kind of content remains in memory after a Continuous professional development for statistics? Results of an interview study : Thomas Wassong
• 4G3: Professional Development to Transform Middle and High School Teachers' Understandings about Distribution : Susan Peters

4H: Statistical reasoning and teaching and learning processes

• 4H1: Statistically deep learning based on the investigative cycle of a sixth-grade elementary school student : Mitsuru Matsushima
• 4H2: Comparing the HyFlex (Hybrid-Flexible) Model of Course Delivery in an Introductory Statistics Course and a Probability and Statistics Course for Engineers and Scientists : Jackie Bryce Miller, Melinda Baham
• 4H3: Using A Group Cooperative Learning Approach in Teaching Statistics : Zeny Mateo

4I: Challenges and different pedagogies for the teaching of statistics

• 4I1: Activities to learn fundamental ideas in statistics : Marcos Magalhães
• 4I2: Development and Implementation of In-class Activities in a Large Introductory Statistics Classroom : Eugenia Yu
• 4I3: Use of quizzes in large statistical lectures : Elinor Jones, Matina Rassias, Simon Harden, Niloufar Abourashchi

4J: Innovative projects for statistical education

• 4J2: A study of students' attitudes change and performance improvement in a flip class : Aklilu Zeleke, Carl Lee
• 4J3: A Framework and Survey for Measuring Instructors’ Motivational Attitudes Toward Statistics : Leyla Batakci, Wendine Bolon, Marjorie Bond

4K: Curriculum and unique approaches for statistics discipline in various departments and centers at Japanese Private Universities

• 4K1: Statistical education in department of industrial and management systems engineering of Waseda university : Yasushi Nagata
• 4K2: Statistical Education Initiatives at Rikkyo University : Kotaro Ohashi
• 4K3: Statistics major offered by the Department of Mathematics at Keio University: Curriculum and student-led events : Mihoko Minami, Tomoshige Nakamura
• 4K4: Bringing Up Data Scientists in Japan: Yokohama City University : Jinfang Wang, Masataka Taguri

Topic 5: Statistics education in the workplace, government and across disciplines

5A: Official Statistics for Education - Consolidated efforts of Japanese National Statistic Institutes

• 5A1: Official Statistics for Education – Variety of statistical education web contents offered by Statistics Bureau of Japan : Minako Marui
• 5A2: Official Statistics for Education - Advocating statistics education for official statistics as public goods : Ryosuke Kurematsu
• 5A3: Initiatives of Statistical Research and Training Institute in Japan – for development of statistical literacy of government officials : Motoy Uematsu

5C: Statistical Education and Training for Public Policies

• 5C1: Statistical Training in Support of Evidence Based Policy Making : Yoshiyuki Kobayashi
• 5C2: Changing system of Statistics Education for Official Statistics : Kumar Ashish
• 5C3: Education of Data Science in Japan: Shiga University Model : Seiji Takata, Shizue Izumi, Akimichi Takemura

5D: Statistical Education and Work Integrated Learning

• 5D2: Flanders’ Training Network for Methodology and Statistics (FLAMES) : Karen François, Emmanuel Abatih, An Carbonez, Els Goetghebeur, Koen Plevoets
• 5D3: Industry Collaboration through Work-Integrated Learning in a Capstone Unit : Ayse Aysin Bilgin, David Bulger, Peter Petocz

5E: Statistics Education Across Discipline

• 5E1: A statistics module that interactively engages undergraduate medical students : Sophie Lee, Eirini Koutoumanou
• 5E2: The role of mathematics anxiety and statistics anxiety in learning statistics : Caterina Primi, Francesca Chiesi
• 5E3: Psychological factors associated with academic performance in statistics : Martin Malaspina

5F: Statistical Education for Decision Makers for Evidence Based Policy Making

• 5F1: Evidence-based assessment and policy-making for cultural demands at Chinese Rural Areas : Dongdong Ji, Jie Zhang
• 5F2: Teaching Basic Statistics Using Integrated Global Census and Survey Data : Miriam King, Lara Cleveland, Kristen Jeffers
• 5F3: Adult Learning as a Chance for Improving Statistical Literacy of Decision Makers: Focusing the Case of Croatia : Ksenija Dumicic, Toni Milun

5G: Designing Collaborative and Tailored Training in Statistics and Data Science

• 5G1: Statistics education within research methods teaching : Shirley Coleman
• 5G2: Integrating collaboration, communication and problem solving to promote innovation in statistics education : Carla Vivacqua, André Luís Pinho, Marcus Nunes, Eric Vance
• 5G3: International Program in Survey and Data Science : Frauke Kreuter, Florian Keusch, Evgenia Samoilova

5H: Statistics Education Across Disciplines: pedagogy and assessment for statistical literacy, critical thinking, and evidence-based practice

• 5H1: Statistics education for public health nurses in the statistics seminar : Toshiharu Eto, Hiroyuki Nakao, Noriko Matsumoto, Keiko Aoishi, Yoshio Hidaka, Yoshinori Fujii
• 5H2: A short classroom-based workshop on Latent Class Analysis : Daniel Green, Eirini Koutoumanou
• 5H3: The Multiple Choice Question: Assessing Statistical Literacy and Critical Thinking in the Introductory Statistics Course at the College Level : Rossi Hassad, Gerald Iacullo

5I: Understanding the statistical education needs of researchers in applied disciplines

• 5I1: Five-year follow up survey of usage of tools given in a one-day sample size course : Angela Wade
• 5I2: Practical Education of Statistics for Veterinary Medicine and Animal Science : Satoshi Sekiguchi, Yosuke Sasaki, Ryoko Uemura, Masuo Sueyoshi, Yoshinori Fujii
• 5I3: Back to basics? Identifying educational needs in statistical consulting : Sue Finch, Ian Gordon, Graham Hepworth

5J: Education of statistical quality control for industries in Japan

• 5J1: Education of Statistical Quality Control by the Union of Japanese Scientists and Engineers – Practical Statistics Education for Engineers in Industries : Kenji Suzuki
• 5J2: Active Learning of Statistical Quality Control in Practice with Hope-add-inn : Takenori Takahashi
• 5J3: The Quality Management Certificate Examination in Japan : Hisakazu Shindo, Nobuhiko Inaba

Topic 6: Innovations in teaching probability

6A: Conditional Probability, Part 1: Learning probability with visualisation

• 6A1: Conditional probability: friend or foe? : Marie Fitch, Stephanie Budgett
• 6A2: The effect of visualizing statistical information in Bayesian reasoning problems : Markus Vogel, Katharina Böcherer-Linder
• 6A3: Frequency phobia in spite of probability blindness : Patrick Weber, Stefan Krauss, Karin Binder

6B: Learning Conditional Probability, Part 2

• 6B1: Categorizing errors in Bayesian situations : Andreas Eichler, Katharina Böcherer-Linder
• 6B2: Classroom activity in Secondary School for introducing conditional probability : Emilse Gómez-Torres, Ivonne Latorre-Verano
• 6B3: Year 13 students’ reasoning from an eikosogram: an exploratory study : Malia S Puloka, Maxine Pfannkuch

6C: Teaching Probability in School - Understanding Probability and Linking to Statistical Inference

• 6C1: Do high school students understand the sampling distribution of a proportion? : María M. Gea, Nuria Begué, Carmen Batanero, Pablo Beltrán-Pellicer
• 6C3: Fundamental Ideas in the Probabilistic Reasoning of High-School Students in Binomial Distribution Activities : Ernesto Sánchez, Guadalupe Carrasco, Mariana del Ángel Herrera

6D: Role of Probability ‘Games’ in Learning

• 6D1: Applying probability rules to games of chance than involve risk: a didactical strategy : Beatriz Adriana Rodríguez González, Isaias Miranda Viramontes
• 6D2: Extending introductory probability through games : Adam Molnar, Laura Behrens
• 6D3: Understanding randomness: From gimmicks to effective learning : Helen Chick

6E: Concepts in teaching probability: learning obstacles and proposals for how to overcome them

• 6E1: Fundamental Concepts and their Key Properties in Probability – How to Identify them and Provide Sustaining Intuitions : Manfred Borovcnik
• 6E2: Integrating theoretical and empirical considerations - Young students' understanding of the empirical law of large numbers : Susanne Schnell
• 6E3: A study on mathematical activity with a focus on linking the theoretical and experimental approaches to probability : Takuma Takayama

6F: Novel Approaches to Teaching Probability

• 6F1: Effectiveness of Use of Diagrams for Teaching Conditional Probability from A Semiotics Viewpoint : Ippo Ishibashi
• 6F2: On the use of key words and visual representations in solving probability problems : Sweet Rose Leonares
• 6F3: Integrating Computational Learning in Probability : Amy Wagaman

6G: Challenges in Teaching Probability

• 6G1: A survey of teachers’ self-reported practices of probability teaching in primary and secondary school levels in Québec : Vincent Martin, Mathieu Thibault, Normand Roy
• 6G2: Using Activity-Based Cooperative Learning Materials to Develop High School Students’ Critical Thinking and Problem Solving Skills in Statistics and Probability : Judella Langcauon, Enriqueta Reston
• 6G3: Granular Density in the Evolving University Probability Course : J. Todd Lee

6H: Post-secondary Conceptions of Probability

• 6H1: Students' Conveyed Meanings for Probability : Neil Hatfield
• 6H2: The Problem with Deciding if Order Matters : Gale Russell, Egan Chernoff
• 6H3: The Challenge of Teaching Probability to elderly people : Teresita Teran

Topic 7: Statistical literacy in the wider society

7A: Promoting understanding of civic statistics: Linking conceptual frameworks, datasets, visualizations, and resources

• 7A1: Understanding statistics about society: A framework of knowledge and skills needed to engage with Civic Statistics : Rosie Ridgway, James Nicholson, Iddo Gal
• 7A2: Developing Official Statistics Literacy: A proposed model and implications : Iddo Gal, Irena Ograjenšek
• 7A3: Civic.Stat.Map - Mapping Datasets, Viz tools, Statistical Concepts and Social Themes : Paula Lopes, Sonia Teixeira, Pedro Campos, Jim Ridgway, James Nicholson

7B: ISLP past and now

• 7B1: How to collaborate with the media to enhance statistical literacy of the general public : Pim Bellinga, Thijs Gillebaart
• 7B2: History of the Statistical Graphs Competition in Japan and its Role in Statistical Literacy Developments : Kazunori Yamaguchi, Michiko Watanabe
• 7B3: ISLP past and now : Reija Helenius

7C: Promoting statistical literacy with visualisation

• 7C1: Visualizing statistical information with unit squares : Katharina Böcherer-Linder, Andreas Eichler, Markus Vogel
• 7C2: T(h)ree steps to improve Bayesian reasoning : Karin Binder, Stefan Krauss, Georg Bruckmaier, Jörg Marienhagen
• 7C3: Vocational training students’ reading levels of statistical graphs : Pedro Arteaga, J, Manuel Vigo, Carmen Batanero, J. Miguel Contreras

7D: Fostering students‘ knowledge and statistics related affect

• 7D1: What happens when attitudes toward statistics change (increase vs descrease) during the course? : Francesca Chiesi, Caterina Primi
• 7D2: Metacognitive Scaffolding to Develop Critical Consumers of Research : Rachelle Hackett, Linda Bol
• 7D3: The use of Socrative in promoting classroom engagement: a qualitative investigation : Laura Tirlea, Samuel Muir, Bradley Elphinstone, Minh Huynh

7E: Using statistical literacy in tools for the society

• 7E1: Towards a Framework for Interrogating Data-Based Augments Perpetuated in Social Media : Travis Weiland
• 7E2: Educating Older People for Retirement Housing Decisions A Case Study in Australia : Timothy Kyng, Ayse Aysin Bilgin, Ling Li
• 7E3: The use of technology and social media in teaching Statistics : Charalampos Chanialidis

7F: Challenges for statistics in the past and in the future

• 7F1: Big Data literacy : Karen François, Carlos Monteiro
• 7F2: Statistics, Reality, Truth : Giovanni A. Barbieri
• 7F3: Teaching and learning about tree-based methods for exploratory data analysis : Joachim Engel, Tim Erickson, Laura Martignon

7H: Statistical literacy of teachers

• 7H1: Statistical literacy, reasoning and thinking in mathematics teachers training : Felipe Ruz, Danilo Díaz-Levicoy, Elena Molina-Portillo, Karen Ruiz-Reyes
• 7H3: Training on Statistics for Teachers of Daan Sarile Integrated School in Cabanatuan City, Nueva Ecija, Philippines : Genelyn Ma. Sarte

Topic 8: New approaches to research in statistics education

8A: Inference in Times of Crisis, Part 1

• 8A1: Teaching Statistical Inference at the University Level: the Italian Experience : Franca Agnoli
• 8A2: Improving the Interpretation of Confidence and Credible Intervals : Rink Hoekstra, Richard Morey, Eric-Jan Wagenmakers
• 8A3: Confidence intervals and replication - the reality : Ian Gordon

8B: Inference in Times of Crisis, Part 2

• 8B1: Teaching replication : Fiona Fidler, Jon Grahe, Tim Parker
• 8B2: Using “statcheck” to Detect and Prevent Statistical Reporting Inconsistencies : Michele Nuijten
• 8B3: A simulation study of the strength of evidence in the recommendation of medications based on two trials with statistically significant results : Don van Ravenzwaaij

8C: Reasoning

• 8C1: Using the Toulmin model of argumentation to validate students' inferential reasoning : Ana Gómez-Blancarte, María Guadalupe Tobías-Lara
• 8C2: Assessing statistical literacy and statistical reasoning : Anelise Sabbag, Joan Garfield, Andrew Zieffler
• 8C3: Students’ conceptual understanding of the relationship between study design and conclusions in an introductory statistics course : Elizabeth Fry

8D: New Methods in the Age of Big Data

• 8D1: Finding meaning in a multivariable world: A conceptual approach to an algebra-based second course in statistics : Karen McGaughey, Beth Chance, Nathan Tintle, Soma Roy, Todd Swanson, Jill VanderStoep
• 8D2: Enhancing learning outcomes with 'big data' from pedagogy for conceptual thinking with Meaning Equivalence Reusable Learning Objects (MERLO) and Interactive Concept Discovery (INCOD) : Masha Etkind, Theodosia Prodromou, Uri Shafrir
• 8D3: Comparison of testing and evaluation methods for new resources in statistical education : Bruce Dunham, Gaitri Yapa, Melissa Lee

8E: Theory and Frameworks

• 8E1: Use of the focusing framework for characterizing students’ foci of attention when reasoning about data distributions : Luis Saldanha, Mathieu Thibault
• 8E2: Revealing Conceptual Difficulties when Interpreting Histograms: An Eye-Tracking Study : Lonneke Boels, Rutmer Ebbes, Arthur Bakker, Wim van Dooren, Paul Drijvers
• 8E3: Towards a research-based framework for statistics education : Darren Macey, Ellen Jameson, Rachael Horsman, Vinay Kathotia, Lynne Mcclure, Lucy Rycroft-Smith

Topic 9: Technology and multimedia in statistics education

9A: Supporting students doing data analysis by using digital tools designed for use by students

• 9A1: Co-Design of the Common Online Data Analysis Platform (CODAP) for cross-disciplinary use at grades 6–14 : William Finzer, Daniel Damelin
• 9A2: Developing E-Modules to Support Preservice Secondary Mathematics Teachers’ Statistical Thinking : Rick Hudson, Hollylynne Lee, Stephanie Casey, William Finzer, Gemma Mojica, Christina Azmy, Adam Eide
• 9A3: Gaining iNZights from Data : Chris Wild

9B: Data science in secondary education

• 9B1: Mobilize: a Data Science Curriculum for 16-year-old students : Robert Gould, Suyen Moncado-Machado, James Molyneux, Terri Johnson, LeeAnn Trusela
• 9B2: Data Clubs for middle school youth: engaging young people in data science : Andee Rubin, Jan Mokros
• 9B3: Data Moves: one key to data science at the school level : Tim Erickson, William Finzer, Frieda Reichsman, Michelle Wilkerson

9C: Using R for effective teaching of Statistics

• 9C1: Code Sharing in Statistics Workshops : Dean Langan, Angela Wade
• 9C2: Teaching with R – a curse or a blessing? : Dulce Gomes, Bruno de Sousa
• 9C3: Modeling First: A Modeling Approach To Teaching Introductory Statistics : James Stigler, Ji Son

9D: Engaging students in learning statistics

• 9D1: From co-created learning resources to personalised online courses for blended learning : Pim Bellinga, Thijs Gillebaart
• 9D2: Keeping students engaged with Shiny interactive tools : Justin Wishart
• 9D3: Enhancing Statistical Literacy through Real World Examples: A Collaborative Study : Sashi Sharma

9E: Software and smartphone technology developments

• 9E1: Current situation and issue for effective use of statistical software in Japan : Yoshinori Fujii
• 9E2: Use of Technology to Close Statistical Knowledge Gaps – Teaching Students with Limited Background in Mathematics : Beatrice Gichohi
• 9E3: An ontology-based enriched ebook for teaching statistics : Jean-Marc Meunier, Samuel Szoniecky

9F: Using data visualization to build statistical thinking

• 9F1: Infusing data visualization into intro stat using Tableau : Stacey Hancock
• 9F2: How much do model violations affect regression results: a demonstration using Shiny : John Walker, Harry Wu
• 9F3: Concept Images and Statistical Thinking: The Role of Interactive Dynamic Technology : Gail Burrill

9G: Design matters: How resources and experiences impact learning in online courses

• 9G1: The Open Learning Initiative (OLI) Online Statistics Course: How Statistics Education Helped Define Promising Directions for the Use of Technology-Enabled Instruction in Higher Education : Oded Meyer
• 9G2: Impact of online resources in teaching Statistics to undergraduates : Elinor Jones, Simon Harden, Jian Yu
• 9G3: Designing for educators in a Teaching Statistics MOOC: Design principles and use of multimedia to support participant engagement : Hollylynne Lee, Jennifer Lovett, Gemma Mojica

9H: Teaching Statistics Online

• 9H1: Design and Evaluation of a Hypothetical Learning Trajectory to Confidence Intervals based on Simulation and Real Data : Santiago Inzunza
• 9H3: Change? Bring it on: Experiences in Moving a First Year Biostatistics Course Online : Nicolette Fozzard, Abdullah Karaksha

9I: Gathering and modeling data

• 9I1: Using Personal Activity Data in an Undergraduate Statistics Course : Kady Schneiter, Lacy Christensen, Victor R. Lee
• 9I2: Students' statistical modeling activities using TinkerPlots : Jennifer Noll, Jason Dolor, Kit Clement, Dana Kirin, Matthew Petersen
• 9I3: Virtual Environments for Teaching Qualitative Research Methods : Michael Bulmer, Katelyn Doyle

9J: Use of new technology for promoting classroom engagement

• 9J1: Implementing research results in technology induced teaching of statistics - A literature review : Andreas Eckert
• 9J2: Increasing Engagement in a Probability Course through Novel Technically-enhanced Communication : Sohee Kang, Marco Pollanen, Sotirios Damouras, Bruce Cater
• 9J3: TeachIT: Turning the Classroom into a Research Laboratory via Interactive e-Learning Tools : Philipp Burckhardt, Alexandra Chouldechova, Rebecca Nugent

9K: Alternative and creative ways to teach statistics

• 9K1: Data in Search of a Context: An Icebreaker Activity : Alexander White, Layla Guyot, Amanda Walker
• 9K2: Presentation of statistical concepts with dynamic graphics and simulations in R : Andrej Blejec
• 9K3: Exploristica - Adentures in Statistics with Augmented Reality : Pedro Campos, Jorge Ribeiro

9L: Trends in statistical education via internet in Japan

• 9L1: Computer-based testing for Japan Statistical Society Certificate: Outline and problem evaluation : Hirohito Sakurai, Atsuhiro Hayashi, Masaaki Taguri
• 9L2: Prospects of teaching statistics using interactive applications by Shiny : Takafumi Kubota
• 9L3: Development of teaching materials and the data analysis competition for secondary education : Akinobu Takeuchi, Katsuyuki Suenaga, Michiko Watanabe

9M: Statistics Education with MOOC

• 9M1: Developing a Mobile Learning Course of Elementary Statistics for K-MOOC by Using Modules of Dynamic Graphical Software for Teaching Statistics, eStat : Jung Jin Lee, Tae Rim Lee
• 9M2: Developing a massive open online course of introductory statistics in Japan : Fumitake Sakaori
• 9M3: A report on the online learning system on statistics, provided for the students in Tokyo University of Information Sciences : Yumi Yahagi

Topic 10: Organisations and collaboration in statistics education

10A: Collaboration between industries/international-connections and university-level education:

• 10A1: Statistics in Practice: Making of Professional Statisticians in a Classroom : Dilhari Attygalle, Asoka Ramanayake
• 10A2: Do you have experience? Incorporating Experiential Learning Opportunities into Statistics Education is Messy but Important : Nathan Taback
• 10A3: Peer teaching in a first year undergraduate class: indigenous language mediating the learning experience : Thina Zukiswa Maqubela

10B: Activites related to interaction with schools

• 10B1: Appetizers and Desserts in Teaching Statistics : Josefina Almeda
• 10B2: Uniting Primary, Secondary & Tertiary Education, Industry and Statistics : Peter Howley, Tim Roberts
• 10B3: Working with a community organisation to create open data sets from records and files : Ian Hay, Rosemary Callingham

Contributed papers

• C102: Preservice Mathematics Teachers' TPACK Development in Statistics Teaching: A Microteaching Lesson Study : Gamze Kurt Birel, Erdinç Çakıroğlu
• C103: Developments of teachers’ knowledge facets in teaching statistics with digital tools measured with retrospective self-assessment : Ralf Nieszporek, Rolf Biehler, Birgit Griese
• C104: Cognitive transfer assessment in post-secondary statistics : Matthew Beckman, Robert delMas
• C105: School students’ skills to compare datasets : Burkhard Priemer, Wiebke Musold
• C108: Attitudes & Beliefs in Statistics Learning for Social Science Graduate students : Liuli Huang, Erin Scott-Stewart
• C110: Simulations for addicts of gambling : Piet van Blokland
• C115: Social and Economic Networks and Financial Literacy in Statistics Classes: Lessons and Experiences : Peter Kovacs, Klara Kazar, Eva Kuruczleki
• C117: Statistics: A Window to Understanding Diversity : Mahtash Esfandiari
• C118: Do Video Clips and Online Self-tests have Added Value in Educating Statistics ? : Elly Korendijk, Jos Hageman
• C119: Dunning-Kruger effect for students taking statistics courses : Carl Lee, Aklilu Zeleke
• C120: Graduate Students Teaching Statistics: Their Experiences In Community and Beliefs About Teaching : Nicola Justice
• C121: Innovations in statistical training: reflections from the UK Q-Step Initiative : Jackie Carter, Mark Brown
• C124: The use of a story-based task to explore sampling distributions : Collette Lemieux
• C131: Effect size and statistical inference : Jeffrey Witmer
• C135: Data-Driven Learning Strategy in Introductory Statistics Courses : Xiaoyi Ji
• C138: Statistical Contents and Lessons in the Japanese Curriculum of Mathematics for Upper Secondary Schools : Yuichi Oguchi, Yasuhiro Kikuchi
• C139: Teaching practice of “analysis of data” using computer games — team making with Quality Control problem solving method : Tomomi Masuda
• C141: An education curriculum for developing analytical system engineer being good at statistics : Naoko Sakurai
• C142: Perspectives in Teaching Statistics in a Pedagogy Course in DE : Auriluci Figueiredo, Michel Costa
• C145: The Accessibility Analysis of Senior High School Statistics Texts in Indonesian Textbooks : Nurul Taflihati Masykar, Kai-Lin Yang, Khairiani Idris
• C146: Building a culture of data driven decision making in higher education using data warehousing : Johnson Mwangi, Bernard Alaka
• C147: The Effect of the Structure of Contingency Table Data on Students’ Inferences : Ting-Ying Chu, Kai-Lin Yang, Xin-Yi Liu
• C152: Decision-making in uncertainty-infused learning situations with experiments in physics classes : Tobias Ludwig, Burkhard Priemer, Doris Lewalter
• C155: Using R to teach statistics : Charles Taylor
• C158: Comparing Instructor Created vs. Externally Created Homework Assignments And Their Effects On Exam Scores : David Swart, Lynette Hudiburgh, Karsten Maurer
• C159: Impacts of A Teaching Statistics MOOC on Educators’ Perspectives and Practice : Gemma Mojica, Hollylynne Lee, Jennifer Lovett, Christina Azmy
• C167: Can a Simulation-Based Inference course be flipped? : Noelle Pablo, Beth Chance
• C168: An Integrative Work in Statistical Classes : Diana Kohan, Teresita Terán, Marisa Battisti
• C170: Activities and types of statistical graphs in textbooks of primary education in Perú : Danilo Díaz-Levicoy, Miluska Osorio, Felipe Ruz-Ángel
• C171: Improving capacity and quality of undergraduate statistics instruction through research-based TA training experiences : Jennifer Kaplan, Kristen Roland
• C174: Implementing a Simulation-Based Inference Curriculum in Indonesia: a Preliminary Report : Kie Van Ivanky Saputra, Olivia Couch
• C175: What is Statistics? Examining the Disciplinary Beliefs of Incoming Statistics TAs : Kelly Findley, Jennifer Kaplan
• C176: Building support communities for statistics educators : Lynette Hudiburgh, Amy Hogan
• C177: Assessing retention of statistical concepts after completing a post-secondary introductory statistics course : Stephanie Mendoza, Soma Roy
• C178: A Three-tiered Training Program for Graduate Teaching Assistants : Lynette Hudiburgh
• C179: Examining Distractors in Multiple-Choice Questions for Classroom Assessments: Learning from Psychometrics : Yan Liu, Amery Wu, Minjeong Park, Ernest Kwan
• C182: Effects of statistical words on the way students view data : Hiroki Otani, Hiroto Fukuda, Kaori Tagashira, Hideki Iwasaki
• C186: The Engagement with Big Data Analytics in Business: A Preparation : Nelia Ereno
• C190: Case study on expected value and standard deviation of sample mean : Eun Ha Kim, Cheong Soo Cho
• C192: Could open-ended questions be replaced by multiple-choice questions in Statistics exams? : EJ Bakker, Hilde Tobi
• C193: Statistics capacity building and alignment of learning outcomes with business sector needs in the GCC Countries : Ibrahim Alfaki, Rafiq Hijazi
• C195: Teaching Time Series to Undergraduate Students : Mike Forster
• C200: A Framework and Survey for Measuring Students’ Motivational Attitudes toward Statistics : Douglas Whitaker, Alana Unfried, Leyla Batakci
• C201: Strategies Employed by Secondary Mathematics Teachers on Inferential Reasoning Tasks : Maryann Huey, Wendy Weber
• C202: Transforming Teaching and Learning Statistics: A Multidimensional Approach : Monica Dabos
• C203: The Impact on Teacher Attitudes and Statistical Pedagogical Knowledge of a Regional Hub and Mentorship Program for Two-Year Colleges in the U.S. : Michael Posner, Monica Dabos
• C207: Teaching design of cross-curricular statistical education at high school in JAPAN : Fumihiko Mitsunaga
• C211: Secondary teachers’ understanding of statistical modeling after teaching a simulation-based statistical inference course : Michael Huberty, Nicola Justice, Andrew Zieffler, Robert delMas
• C213: Overcoming challenges with service courses in Statistics : Matina Rassias
• C220: Using the SETS level A items to classify pre-service teachers' self-efficacy to teach statistics: an application of the Mixture Rasch Model : Leigh Harrell-Williams, Jennifer Lovett, M. Alejandra Sorto, Rebecca Pierce, Lawrence Lesser, Teri Murphy
• C223: Post-secondary teachers’ understanding of p-value : Jason Mark Dolor, Dana Kirin
• C227: Students’ behavioral intentions regarding the future use of statistical methods : Polona Tominc, Maruša Krajnc, Klavdija Vivod, Blaž Frešer
• C229: Improving Teaching and Capacity in Statistics Education: The case of Ghana : Bashiru I.I Saeed, Azumah Karim
• C234: Teaching Biostatistics course with flipped classroom : Mingan Yang
• C235: Blended Learning in Higher Education: A Case Study in Postgraduate Applied Statistics Programs : Jahar Bhowmik, Brian Phillips, Denny Meyer
• C240: Diversity-Related Projects in an Introductory Statistics Course : Kirsten Doehler, Laura Taylor
• C244: Comparing the efficiency of mathematical V. intuitive explanations in conditional probability : Sigal Levy, Yelena Stukalin
• C245: Similarities and Differences of Learning Approaches of Student in Statistics and Mathematics: A Case Study from Turkey : Eti Mizrahi, Ayse Aysin Bilgin, Irma Hacinliyan, Gizem Intepe, Sitki Gozlu
• C246: Project-based curriculum as a guide for the re-sequencing of a discipline specific statistics course : Veronica Fruiht
• C247: Specialist and Non-Specialist Students' Attitudes Towards Statistics : Zainal Abidin Koemadji, Professor Janet M. Ainley
• C251: Significance of intuitive explanation of CI for non-statistician students : Yelena Stukalin, Sigal Levy
• C253: You R, so you are ! : Koo Rijpkema
• C258: Introductory Statistics with Deferred Uni Variate for Long Term Academic Degree Program : Lita Pertiwi, Febry Utami, Noor Laila, Aulia Dini, Nuha Gunawan
• C259: The Effects of Virtual Manipulatives on Statistics Achievement of Undergraduate Students : Xin Ma, Anushka Karkelanova, William Rayens
• C261: Developing and assessing written communication skills in large introductory statistics classes : Elizabeth Johnson, David Holmes
• C264: Developing the skills demanded of a statistician beyond statistics: a case study in biostatistics : Stephanie Hubbard, Smith Ellesha
• C268: Repeated Sampling as a step toward Informal Statistical Inference : Marianne van Dijke-Droogers, Paul Drijvers, Arthur Bakker
• C270: Taming Statistics for Students with APL : Stephen Mansour
• C278: Cultivating Interdisciplinary Undergraduate Research in Applied Statistics : David Holmes, Elizabeth Johnson
• C279: Preparing students for a career in Statistics : Jay Mandrekar
• C282: Practical use of correlation coefficients in the Social Sciences : Oscar Hernandez, Russell Alpizar-Jara
• C283: Teaching probability and statistics to pre-service elementary school teachers : Yoshiji Takagi
• C290: Challenges for Independent Student Projects: A Perspective of the Teacher : Layla Guyot, Amanda Walker, Alexander White
• C295: Utilizing a Flipped Classroom for an Introductory Biostatistics Course : Jacqueline Milton
• C298: Teaching Learner-Centered Statistics: A Case for Blended Delivery using Google Apps : Leon Cygman
• C302: Can a three-day intensive statistics boot camp increase graduate students' core knowledge and self-efficacy? : Brian Leventhal, S. Jeanne Horst, Derek Sauder, Karen Ford
• C304: Factors Affecting Performance In Statistics Of Benguet State Unversity College Students : Precious Valentin, Marycel Sajise
• C305: Simultaneous Modeling Of Rainfall Quantity And Incidence In Pangasinan Using Poisson-Gamma Distribution : Jennifer Miguel, Marycel Sajise
• C307: Event History Analysis of Attrition and Degree Completion in Graduate Studies : Bobby Roaring, Marycel Sajise

Posters

• P1: The Impact of Homework Feedback on Statistical Literacy in Austrian Computer Science Students : Thomas Forstner
• P2: Use of Interactive Apps in Teaching Bayesian Statistics : Haydar Demirhan, James Baglin
• P3: Learning Statistics From Data : Yuan-chin Chang
• P4: Using concept questions to teach statistical terms : John Blake
• P5: Practice of Proactive Utilization of Mathematical Representation in Learning of Statistics : Kunihiko Shimizu
• P6: Attitudes toward Statistics as Moderator Variables in the Evaluation of Activating Methods in Lectures on Statistics : Florian Berens, Sebastian Hobert
• P7: Context of statistical graphs in primary school textbooks in Costa Rica : Maynor Jiménez Castro, Pedro Arteaga, Carmen Batanero
• P9: Learning of statistics in a Mexican telescondary school: impact of statistical enquiry in students outcomes : Alberto Santana Ortega, Ana Gómez-Blancarte, Dora Pérez Hernández
• P10: A robust method to identify the statistical learning abilities of students : Hung Hung
• P11: The introduction of chemometrics course as a step forward to modernization of study curriculum at engineering faculties : Strahinja Kovacevic, Sanja Podunavac-Kuzmanovic, Milica Karadzic, Lidija Jevric, Jasna Canadanovic-Brunet, Gordana Cetkovic
• P12: Molecular modeling and statistical software in modern organic chemistry teaching – Step forward to modernization of undergraduate studies at engineering faculties : Strahinja Kovacevic, Sanja Podunavac-Kuzmanovic, Milica Karadzic, Lidija Jevric, Gordana Cetkovic, Jasna Canadanovic-Brunet
• P13: Modified Information Matrix Tests for Detecting Misspecification in the Random Effects of GLMMs : Kuo-Chin Lin
• P14: Teaching Graduate Students Sample Size Planning by Using R : Wei-ming Luh, Jiin-Huarng Guo
• P15: Every learner is unique so why couldn’t their assignments be unique? The use of simulated datasets in inferential statistics courses. : Brian Leventhal, S. Jeanne Horst
• P16: Another Look at the Box Model : Dennis Sun, Joseph Alfredo
• P17: Developing secondary preservice mathematics teachers’ statistical knowledge for teaching : Stephanie Casey, Andrew Ross, Samantha Maddox
• P19: Integration of Extensive Technology in a Canadian Service Statistics Course : Wesley Burr, Melissa Van Bussel, Skye Griffith
• P20: Launching a statistical enquiry: Posing statistically worthwhile questions : Aisling Leavy, Daniel Frischemeier
• P22: Technology in bi-dimensional statistics in High School textbooks : María M. Gea, María del Mar López-Martín, Juan J. Ortiz, Rafael Roa
• P24: Student attitudes towards statistics at a South African university : Nombuso Zondo, Delia North, Temesgen Zewotir
• P25: A study of practical statistics education using questionnaire survey : Mie Fujiki
• P26: Discussion in a student’s statistics report including controversy on social justice : Takashi Nakanishi
• P27: University Math and Stats Support Centre and how to reduce a rate of unsuccessful studies : Maria Králová
• P28: Sharing statistical analysis techniques using dental practice data : Rosie Pritchett, Shirley Coleman
• P29: A novel way to teach biostatistics to public health students : Qi Zheng
• P30: datascientist education by e-Learning system : Kenichi Hirano
• P31: Information Request of the Society as a Condition for the Development of Statistical Literacy : Elena Zarova, Polina Kryuchkova, Pavel Smelov, Sergei Musikhin, Ilya Zalmanov
• P33: Modelling and statistics in food product design - modernization of food engineering courses : Gordana Cetkovic, Jasna Canadanovic-Brunet, Strahinja Kovacevic, Sanja Podunavac-Kuzmanovic, Milica Karadzic, Lidija Jevric
• P34: Implementing Inverted Instruction in Undergraduate Introductory Statistics Courses : Anushka Karkelanova, William Rayens, Xin Ma
• P35: C-SOMAS: Measuring Classroom Characteristics : Marjorie E. Bond
• P36: Young learners’ reasoning with informal statistical models and modelling : Michal Dvir, Dani Ben-Zvi, Yotam Hod
• P37: Basic statistics starts with bivariate for academic degree program : Lita Pertiwi, Noor Laila, Aulia Dini
• P39: A web-based learning system for junior high school students and high school students : Takatsugu Yoshioka, Yuichi Mori
• P40: Latent trait models highlight deficits in student understanding. : Robert Quinn, Petra Graham, Anne Karpin, Ayse Aysin Bilgin
• P41: A case study on the development of statistical thinking using multivariate data：Based on Olympic Decathlon : Koki Hosoda
• P42: Rethinking Exams in Large Lectures : Melissa Pittard
• P43: Mastery-Based Grading in Introductory Statistics : Katherine M. Kinnaird
• P44: StatHand: A Mobile Application to Support Students' Statistical Decision Making : Peter Allen, Frank Baughman, Lynne Roberts, Natalie Loxton, Adam Rock, Dirk Van Rooy, James Finlay
• P45: Students competences in dealing with the classical and frequentist approach to probability : Tobias Rolfes, Boris Girnat, Christian Fahse, Anne M. Hupfer, Alexander Robitzsch
• P46: The Effectiveness of Using ICT Technology in Statistics Education : Makoto Handa
• P47: The construction of the central ideas of the sampling through tecnology in university students : Amable Moreno
• P48: 100% satisfactioned medical statistics seminar that healthcare workers really need at present : Keiko Aoishi, Toshiharu Eto, Noriko Matsumoto, Yoshio Hidaka, Hiroyuki Nakao
• P49: Do standardized tests contribute to statistical education? : Adriana D´Amelio
• P50: An Examination of Computer Versus Tactile Simulations for Teaching Sampling Distributions in Introductory Statistics : Wendy Rummerfield, Stacey Hancock
• P51: What Would Fisher Do? A Useful Tool for Teaching the Model Construction Process : Julie Garai, Marina Ptukhina, Walt Stroup
• P52: Assessing High School Students' Statistical Literacy about the Measures of Central Tendency : Yanqing Ding
• P53: Statistical Practices: What do Statisticians do? : Layla Guyot
• P55: Dealing with Symbols with Multiple Meanings in Inferential Statistics : Von Bing Yap
• P58: Using Real Data on Beliefs about Maths to improve Primary Teachers Students' Capacities in Statistic Education : José Carlos Carrión Pérez
• P59: Effects and characteristics of representative values for the 6th grade in elementary school : Naoki Ohta
• P61: Data Science Education using Statistical Graphic Concour : Chitose Nishiyama, Yuichi Mori
• P62: Views of Benguet State University Employees on the Role of Statistics in the Workplace : Marycel Sajise
• P65: Comparison of Assessment Methods in an Undergraduate Biostatistics Course : Jennifer Daddysman, Tofial Azam
• P67: Comparison of Campus and Online Sections of a Flipped Introductory Statistics Course : Craig Johnson, Ryan Cromar
• P68: Statistical Literacy through Guided Block Play: An Exploratory Multiple Case Study : Robert Giebitz
• P69: Validity Evidence Claims and Plan for the SOMAS Instruments : Douglas Whitaker
• P70: Using Google Docs and Sheets to Design and Collect Data for Classroom Experiments : Wendine Bolon
• P71: Adapting statistics education to a cognitively heterogeneous student population : Solve Sæbø, Hilde Vinje, Trygve Almøy, Helge Brovold