Topic 7 : Statistical literacy in the wider societyA perennial ICOTS theme is our special responsibility to develop sustainable initiatives which enable citizens to lead and extend debates, in the media and elsewhere, on issues of inequality, crime, effects of smoking, use of alcohol, and support for societal preferences. This democratic imperative leads us to questions such as: How can we encourage people to want to engage in statistical learning? How can we contribute to subject-specific learning of relevant statistical knowledge? How do we enrich our understanding of statistical literacy and methods by which it can be attained and sustained? These invited sessions seek to explore and enrich a variety of effective practices and interventions.
Session 7A: Statistical literacy beyond the classroom
7A1: Odyssey: a journey to lifelong statistical literacyMilo Schield Augsburg College, United States
Statistical literacy is the ability to read and interpret everyday statistics in tables, charts, statements, surveys and studies. This skill needs to be developed in college so it can be sustained after college. This skill is more about evaluation and critical thinking than about calculation, derivation and proof. Forums can be used to help students develop this statistical literacy skill online. This paper introduces Odyssey: a new kind of forum where all participants are anonymous, everyone grades everyone, and the system tabulates average scores for each participant. This super-forum has two big advantages. (1) Students like Odyssey: They think it is easy to use; they like being anonymous, seeing how others think and getting immediate feedback and grading; (2) Odyssey is scalable to large-lecture classrooms. Results from using this unique forum are presented. By dealing repeatedly with everyday statistics in the news, students take their first step toward lifelong statistical literacy.
7A2: Teaching statistics for engagement beyond classroom wallsLawrence Lesser University of Texas at El Paso, United States
Statistics education organizations have recently increased efforts to help broader audiences view statistics as a ubiquitous and positive domain. At the same time, educators increasingly seek to maximize student motivation or engagement by using supplements or alternatives to physical textbooks and face-to-face classroom instruction. These endeavors of organizations and individual instructors can be served well by leveraging opportunities to connect statistical concepts to the world beyond classroom walls. These endeavors can span varied ages (from elementary education through adult education) as well as varied modalities (e.g., podcasts, field trips, museum/library events, radio/TV, songs, culture, virtual worlds, AR, service learning, etc.). We overview varied examples and note potential benefits and next steps for statistics education.
7A3: Taking statistical literacy to the masses with YouTube, blogging, Facebook and TwitterNicola Ward Petty Statistics Learning Centre, Christchurch, New Zealand
Social media enables us to connect with the world. Statistics Learning Centre YouTube channel has short friendly videos about statistics and receives over 1000 views a day from all over the world, accompanied often by grateful thanks. The blog, Learn and Teach Statistics and Operations Research, receives 2000 hits per week, which has grown through email lists, Twitter, Facebook and judicious choice of topics, keywords and tags. In this session I will describe the growth of each of these endeavors, explaining how to get started and providing pointers for reaching out with the message of statistical literacy to a wider society.
Session 7B: Statistical literacy requirements for teachers
7B1: Statistical literacy requirements for teachersBrian Beaudrie Northern Arizona University, United States
Jeffrey Hovermill Northern Arizona University, United States
Barbara Boschmans Northern Arizona University, United States
This paper examines the relationship between statistical literacy in a broad sense and international teacher preparation and student learning standards pertaining to statistics. This paper begins with a discussion of why statistical literacy is essential in today’s society and the consequences, on an individual and societal level, of not being statistically literate. Since teachers should play a primary role in developing statistical literacy, the authors present an examination of teacher preparation and student learning guidelines from multiple countries in the area of statistics. The authors present conclusions regarding the alignment between societal statistical literacy requirements and teaching and learning guidelines. Recommendations for meeting teacher statistical literacy requirements are offered based in this analysis.
7B2: Developing statistical knowledge for teaching of variability through professional developmentHelena Wessels University of Stellenbosch, South Africa
This paper reports on a professional development programme focusing on statistical literacy, more specifically the development of in-service teachers’ awareness of and reasoning about variability in multiple trials under uncertainty, and their ability to transfer their understandings to related tasks. Variability and uncertainty are key concepts in statistics, but are under-emphasised in many school curricula. These topics formed part of the focus of the intervention. Analysis of post intervention tasks revealed a growth in teachers’ levels of reasoning about variability and their ability to transfer these competencies to related tasks. The results emphasise the value of well-designed learning experiences and rich discussions in teacher professional development programmes in statistical literacy.
7B3: Teachers’ views related to goals of the statistics classroom – from global to content-specificSebastian Kuntze Ludwigsburg University of Education, Germany
When teachers design learning opportunities in the statistics classroom, they should be aware of specific goals related to statistical literacy – and they should be able to refer to these goals when evaluating the learning potential of tasks. Consequently, possessing corresponding professional knowledge can be seen as a key requirement for teachers. However, as empirical research into these professional knowledge components is still scarce, this study focuses on this area and aims at identifying needs for professional development. The results suggest that many teachers did not see fostering students’ understanding of statistical variation as a prominent goal and that they hardly acknowledged the learning potential of corresponding tasks.
Session 7C: Assessment of statistical literacy
7C1: Towards statistical literacy - relating assessment to the real worldPenelope Bidgood Kingston University, United Kingdom
Students have different strengths and different approaches to learning so the assessment process should give opportunities for them to demonstrate their abilities and achieve the relevant learning outcomes. Reforms in statistical education at all levels place increasing emphasis on students’ abilities to think and reason statistically using real data in appropriate contexts. The huge expansion in technology has given access to various data sources and advances in statistical software have greatly expanded the range of analyses that can be conducted almost instantaneously. Hence there are varied assessment strategies in statistics, whether in specialist or service courses, in which students can be set realistic problems to solve. This talk will discuss some issues in the assessment of statistics, drawing upon the author’s experience in various projects over the years.
7C2: Establishing the validity of the LOCUS assessments through an evidenced-centered design approachTim Jacobbe University of Florida, United States
Douglas Whitaker University of Florida, United States
Steve Foti University of Florida, United States
Catherine Case University of Florida, United States
This paper presents the systematic process utilized by the Levels of Conceptual Understanding in Statistics (LOCUS) project to establish content validity for assessments measuring students’ statistical understanding in grades 6-12 (ages 11-18). Evidence Centered Design (ECD) was used to develop assessments aligned with the United States’ Common Core State Standards in Mathematics (CCSSM) as well as the Guidelines for Assessment and Instruction in Statistics Education (GAISE). The ECD process began with a domain analysis based on CCSSM, GAISE, and learning trajectories from statistics education research and subsequently added layers articulating claims about student proficiency and observable evidence to support those claims. The ECD approach formalized the evidentiary reasoning by which performance on LOCUS can be used to support valid inferences about the larger domain of statistical understanding.
7C3: Sufficiently assessing teachers’ statistical literacyRoger Wander University of Melbourne, Australia
Robyn Pierce University of Melbourne, Australia
Helen Chick University of Tasmania, Australia
Teachers are inundated with data, including reports from mandated testing. Interpreting these requires professional statistical literacy, involving technical statistical knowledge and the capacity to interpret data meaningfully in the context of teachers’ professional work. For a study investigating teachers’ data use, the authors developed instruments for assessing statistical literacy based on typical reports and the critical components of statistical literacy required to understand them. Designing an instrument that assessed workplace-relevant statistical knowledge, and did not take too long to complete, involved design choices through a process of beginning with an initial pen-and-paper design and then designing an online version with automated marking. This paper will examine some of these design issues and their impact on assessing teachers’ statistical literacy prior to providing appropriate professional learning.
Session 7D: Developing statistical literacy: Case studies and lessons learned
7D1: Students’ beliefs about the benefit of statistical knowledge when perceiving information through daily mediaAlexandra Sturm University of Freiburg, Germany
Andreas Eichler University of Kassel, Germany
One general aim of developing students’ statistical literacy is to achieve students’ critical stance referring to statistically-based decision making in modern society reported in daily media like newspapers or TV. However, research shows that adults are predominately struggling with statistical information proposed by daily media. Therefore, we focus on the relation between students’ statistical knowledge and their beliefs. Our research approach consists of developing and conducting an intervention study aiming to connect statistical knowledge with the application of this knowledge. With mixed methods (tests & interviews), we investigate the development of both students’ statistical knowledge and students’ beliefs about the benefit of statistical knowledge when perceiving information through daily media. In our report, we outline the development of the intervention, the method of our investigation and first results.
7D2: Changing the course: from boring numeracy to inspiring literacyKimmo Vehkalahti University of Helsinki, Finland
The course “Introduction to Statistics” was run at the University of Helsinki for nearly 40 years basically unchanged. I experienced it as a student in 1990 and shared the common impression: the course was boring, out of context and seriously out of date with its focus on mechanical calculations. Nearly 20 years later, in 2008, I became the responsible teacher of the course. The bad reputation of the course, together with 300 uninterested students provided me with a challenging opportunity. I changed the course quite completely: the contents, the focus, and the pedagogical practices. Instead of mathematical numeracy it now focuses on statistical literacy. As a result, the course has become popular, attracting 600 interested students from all over the University. In this paper, I reflect on my experiences with this course.
7D3: A numeracy infusion course for higher education (NICHE): strategies for effective quantitative reasoning (QR) instructionEsther Isabelle Wilder The City University of New York, United States
Elin Waring The City University of New York, United States
Frank Wang LaGuardia Community College, United States
Dene Hurley The City University of New York, United States
Our Numeracy Infusion Course for Higher Education (NICHE) teaches best practices for effective Quantitative Reasoning (QR) instruction to faculty in a wide range of disciplines. NICHE is a predominantly online course that consists of 8 separate units of relevance to the development of statistical literacy as well: (1) QR and Making Numbers Meaningful; (2) QR Learning Outcomes; (3) The Brain, Cognition and QR; (4) QR and Writing; (5) Discovery Methods; (6) Representations of Data; (7) QR Assessment; and (8) QR Stereotypes and Culture. This paper describes the key components of NICHE and shows how we employ the same strategies recognized as effective methods for teaching QR to our training of faculty as QR instructors. Examples from course activities, interactive discussions, and assessment data are presented.
7D4: Implementing a quantitative literacy core competency requirement in the College of Arts and Science at Miami UniversityJohn Bailer Miami University, United States
Issues involved in a process of revising university learning requirements with the goal of enhancing students’ Quantitative literacy (QL) are reviewed. QL is often characterized as a habit of mind that is demonstrated by breadth of application in different disciplinary contexts. QL includes statistical literacy along with number sense and an appreciation of models of functional relationships. The implementation of a QL core competency requirement is described, and the use of a faculty learning community to develop and promote QL is discussed as is the importance of securing central administrative support. Developing a constituency of early QL promoters and a review structure with broad background is critical. Ultimately, a well-articulated collection of QL learning outcomes with examples of each is needed to help win over the skeptical and reluctant.
Session 7E: Factors that affect statistical literacy
7E1: Critical thinking as an impact factor on statistical literacy – theoretical frameworks and results from an interview studyEinav Aizikovitsh-Udi Beit Berl Academic College, Israel
Sebastian Kuntze Ludwigsburg University of Education, Germany
The theoretical frameworks of Critical Thinking (CT) and Statistical Thinking (ST) suggest an overlap – however, the quality of the connectedness of CT and ST has still not been described empirically in a satisfactory way. As elements of ST are a key prerequisite of statistical literacy, CT impacts on statistical literacy as well. This study hence focuses on the role of CT in the process of solving problems which require statistical literacy. A case analysis based on interview data provides insight into thinking processes and affords focusing such connections between CT and ST. The results support the hypothesis that thinking skills in both areas are interdependent and help to describe key intersection areas from a theoretical point of view: For instance, the interviewees’ use of strategies of evaluating claims has a high explanatory power and provides a combined framework from the CT and ST perspectives.
7E2: A multilevel perspective on factors influencing students’ statistical literacyUte Sproesser Ludwigsburg University of Education, Germany
Sebastian Kuntze Ludwigsburg University of Education, Germany
Joachim Engel Ludwigsburg University of Education, Germany
Over the last two decades statistics has been recognized as an important part of the school curriculum worldwide. As a result, questions related to impact factors on statistical literacy merit focused attention in empirical research. For instance, interdependencies with individual factors such as general cognitive abilities, reading comprehension or specific elements of mathematical content knowledge is still scarce. We report empirical results from two studies on relationships between statistical literacy and potential influencing factors. The findings provide insight into the role of such covariates and support the validity of the competency measure we used to assess a key aspect of statistical literacy. The evidence further suggests that statistical literacy also depends on class variables beyond individual dispositions.
7E3: Sustaining communication of the value of statistics in the humanitiesNicole Mee-Hyaang Jinn Virginia Tech, United States
The value or utility of statistical inference has not been well-understood among researchers in the humanities. To clarify, the approaches and methodologies of the humanities are primarily interpretative. With appropriate emphasis on interpretation, I argue that a good starting point for effective statistics education in the humanities is in highlighting controversy that continues to exist, such as investigating when statistical inferences are valid, and how to interpret results from statistical methods. Specifically, I present one way of defining a genuine principle of evidence, as well as reasons why principles of evidence are far-reaching. The import of evidence as a concept is accepted in the humanities, and the humanities are similar to sciences in that both involve the analysis and interpretation of evidence.
Session 7F: Factors that affect statistical literacy II
7F1: Reconceptualizing statistical literacy: Developing an assessment for the modern introductory statistics courseLaura Ziegler University of Minnesota, United States
In light of changes to the introductory statistics course, namely the move to include simulation-based methods, new assessments are needed. The Basic Literacy In Statistics (BLIS) assessment was created to measure students’ ability to read, understand, and communicate statistical information. The assessment was designed for students enrolled in introductory statistics courses at the postsecondary level that include some coverage of simulation-based methods in the curriculum. This paper describes the development of the instrument, including the validation of the test blueprint, pilot testing, and analysis of assessment data.
7F2: Improving statistical literacy through supplemental instructionAlexandra Kapatou American University, United States
Supplemental Instruction (SI) is an academic support system designed to increase retention of students in typically difficult classes, such as mathematics and statistics. Unlike other programs, SI is open to all students who feel they need help in a particular course. The help is given by a student leader who has taken the course previously and did well. In addition to the students who benefit from the support, the student leaders also benefit, because of the training that helps retain them in the field. In this study, the performance of students in courses with SI support will be compared to those without SI support. This program is currently offered in 1400 US colleges and universities, as well as other countries. It can easily be applied to many educational settings to improve the education of students all over the world.
7F3: Interpreting variation of data in risk-context by middle school studentsAntonio Orta Centro de Investigación y de Estudios Avanzados del IPN, Mexico
Ernesto Sánchez Cinvestav-IPN, Mexico
The aim of this research is to explore students’ reasoning concerning variation when they compare groups and have to interpret dispersion like/as a risk. In particular, we analyze in this paper the responses to one problem of a questionnaire administered to 80 ninth-grade students. The problem consists of choosing between two groups of data by comparing them; each one consisting of losses and winnings coming from a hypothetical game. The results show the difficulty students had in interpreting variation in a risk context. Although they identify the data group with more variation, it is not enough for interpreting the variation in terms of risk and making a rational decision. The psychological categories of risk-seeking and risk-aversion are used to explain the behavior of students who choose one game or another when they identify correctly the risk in each game. As a conclusion, it is suggested that more risk context situations should be studied.