• Exclusionary gendered language discourages women from pursuing graduate and professional training programs that lead to careers in statistics by excluding them from (1) the readership of statistical literature, (2) the characters portrayed in examples and problems, and (3) those people qualified to use statistical methods; and by (4) stereotyping women characters into nonscientific careers or careers that are not as prestigious and high paying as men's, (5) reinforcing the existing imbalance in the proportion of men and women engaged in scientific research and development, and (6) portraying professional women as incompetent. Thus this article challenges the continuing use of exclusionary gendered language in statistical literature, bringing this bias to the attention of the statistical community. Numerous examples are used to illustrate how the use of gendered language has symbolically excluded women from access to statistical advancements and careers both historically and now.

  • Statistics pervade our society, yet the understanding of statistics has remained the domain of a select few. Although the majority of the literature has focused on the adult learner, there is a movement toward teaching statistics to children. This article addresses the ways in which the study of statistics has been examined in the elementary and secondary schools in terms of content, readiness of children to learn, pedagogy, and assessment. A proposal is presented of how a cognitive apprenticeship model can be developed from the empirical research findings in order to build more effective instructional and assessment methods for statistics education.

  • While important efforts have been undertaken to advancing understanding of probability using technology, the research herein reported is distinct in its focus on model building by learners. The work draws on theories of Constructionism and Connected Mathematics. The research builds from the conjecture that both the learner's own sense making and the cognitive researchers, investigations of this sense-making are best advanced by having the learner build computational models of probabilistic phenomena. Through building these models, learners come to make sense of core concepts in probability. Through studying this model building process, and what learners do with their models, researchers can better understand the development of probabilistic learning. This report briefly describes two case studies of learners engaged in building computational models of probabilistic phenomena.

  • It is my philosophical position that post graduate success is highly associated with autonomous learning. The student needs practice in (1) teaching herself statistical theory and application, (2) self-diagnosis of conceptual strength and weakness, and (3) the process of transcribing a well-defined researchable problem into readable prose. As parents, we have lovingly attempted to instill the sense of pride and accomplishment which can only come from independent success. We don't advocate abandonment, that is, a sink or swim correspondence course approach. The instructor who clarifies, guides, challenges, and supports is worth her salt and has only fully completed her charge when--like the parent--she's obsolete. The purpose of this paper is to explore motivational strategies for motivating student commitment to this autonomous learning objective.

  • The purpose of the study reported herein was to identify important aspects of statistical knowledge needed for teaching in the middle school grades. A systematic study of the current literature, including state and national standards, was conducted to identify these important aspects and to measure the degree of emphasis or importance suggested for the content. Results show that state and national standards differ greatly in their expectations of what topics in data analysis and statistics students and teachers should master. The variation is also large in the degree of emphasis given to the content. The majority of the documents analyzed suggest giving greater emphasis to the selection and proper use of graphical data representation and measures of center and spread. Additionally teachers' standards also suggest as important the proper selection and use of teaching strategies and inference of students' understanding from their work and discourse.

  • This paper continues earlier studies about the teaching and learning of the arithmetic average and it is part of a broader research in progress at Santiago of Compostela University (Spain). We have analyzed a sample of six teaching manuals (textbooks) used for teaching mathematics at high schools in Salvador, Bahia. The study is based on theoretical ideas by Godino and Batanero (1994; 1998) and Godino and Recio (1997) who propose a semiotics perspective based on the functions of signs by Hjelmslev (1943), later known as "semiotic function".( Eco, 1979).

  • The aim of this paper is to present the concept of an 'instrumental' obstacle. In French agricultural education, the spreadsheet is often used as a tool or "artefact" in statistics teaching. Some obstacles to learning appear due to the use of this instrument. Difficulties appear during the learning of analysis of variance by students, who are not trained mathematicians. The concept of average however, which might have been regarded as unproblematic, caused surprising difficulties during one step in the algorithm for analysis of variance. The notion of 'instrumental' obstacle seems to be pertinent in order to analyse this phenomenon. This kind of obstacle is different from those presented by the internal constraints of the artefact. This study confirms that students have yet some problems with the notion of average, but that with spreadsheet use they become aware of this difficulty.

  • Teachers undertaking educational research for the first time usually begin their explorations by evaluating some aspect of their practice. By contrast, experienced researchers will start from an argued research question supported by a defined theoretical framework. In this paper, we use a critical discourse approach to explore various interpretive research paradigms that are commonly used to investigate aspects of statistics education. By considering the underlying epistemological positions and critiquing the approaches and methods used to explore human action in social situations, we become more critical in the design, implementation and reporting of research in statistics education.

  • In this paper we fix the institutional reference meaning of variation and its measures in university books for the first university courses, using the six elements of meaning of the "ontologic-semiotic approach of mathematical cognition." The elements of meaning in books are identified. The deficiencies and possible difficulties that students can find, are considered. From the descriptive point of view, the complexity of topic variation and their measures is established. We conclude by pointing out the usefulness of the results.

  • Design research projects can be characterized as iterative and theory based attempts simultaneously to understand and improve educational processes. To contribute to a framework for design in statistics education, this paper draws on two design research projects, one carried out by Cobb, Gravemeijer and colleagues in the United States and one by Bakker and Gravemeijer in The Netherlands, both focusing on distribution as a core concept in the instructional design. Both projects were inspired by the theory of realistic mathematics education, which includes design heuristics such as guided reinvention, historical and didactical phenomenology, and emergent modeling. Each of these heuristics is briefly illustrated with examples from these two projects.