VOLUME 12, NUMBER 2, APRIL 1999

Secretary and Editor: Carmen Batanero

Departamento de Didáctica de las Matemáticas

Facultad de Ciencias de la Educación, Universidad de Granada

e-mail: batanero@goliat.ugr.es, http://www.ugr.es/local/batanero/

Associate Editor: John Truran

Mathematics Education

Graduate School of Education,University of Adelaide

e-mail: jtruran@arts.adelaide.edu.au

The bibliography on association included in this issue suggests that doing research into statistical education requires a varied background and knowledge, including statistics, education, psychology, pedagogy, philosophy and research methodology. John has written some reflections on the problems of being updated in this varied statistics education bibliography. We hope that this Newsletter may reduce this problem, although we need your cooperation in sending us the summaries of your publications, and information on the conferences held in your countries. Bringing other colleagues to the Study Group is also an effective way to make our work more complete and productive.

We are again approaching the northern hemisphere Summer, and a number of conferences with statistical education components are being organised around the world, including the Study Group Research Forum organised by Dani Ben-Zvi and Joan Garfield. Information on this and other conferences are included in this issue.

Brian Phillips is also offering a note on Andrejs Dunkels, a wonderful person and an enthusiastic statistics and mathematics educator, who died very recently. In Brian's words many members have been privileged to meet, listen to, work with, discuss ideas and have fun with Andrejs. The list of selected references include at the end of the note is a modest homage to his work in mathematics and statistics education.

In this announcement a summary of the Newsletter (including the Table of Contents) is being sent by e-mail to all subscribers. The whole text may be found on the Web at http://www.ugr.es/local/batanero/

We hope to introduce further changes in publication later in the year, but the present methods will continue to remain in place.

Universidad Autónoma de Querétaro, México.

E-mail: vil@sunserver.uaq.mx

Víctor is a lecturer at theUniversidad Autónoma de Querétaro (México). He is developing a web site on statistical education, which is based on a course for training secondary mathematics teachers . He would be glad of receiving suggestions and comments about the material included at the site: (http://www.uaq.mx/matematicas/estadisticas).

Dione Lucchesi de Carvalho

Universidade Estadual de Campinas,

Rua Carop 519, CEP: 05447-000, Sao Paulo, Brazil.

E-mail: dione@obelix.unicamp.br

The CEMPEM (Círculo de Estudos, Mémoria e Pesquiza em Educaçao Matemática) at the Faculty of Education, University of Campinas, Brazil, is responsible for teaching mathematics education to students majoring in Mathematics, Pedagogy, post graduates in Mathematics Education and in-service teachers (kindergarten, primary and secondary school levels). A National Documentation Centre and the mathematics education journal Zetetiké are also managed from the group.

Within CEMPEM the group PRAPEM (Prática Pedagógica em Matemática) was started in 1995 and is devoted to research and teaching, curricular development and teachers' professional development, with a subgroup working in Statistics, Stochastics and Combinatorial Analysis. Permanent members of this group are Anna Regina Lanner de Moura, Dario Fiorentini and Dione Luchessi de Carvallo at the Faculty of Education and Joao Frederico Meyer and Vera L. Figueiredo at the Institute of Statistics and Computer Sciences. There are about 40 additional temporary members, including doctoral and master students, secondary teachers and undergraduates.

The idea of establishing the group arose from teachers and students dissatisfaction with two dominant tendencies in mathematics education research and practice: The technical. instrumental bias towards objective causal scientific explanations, following a model of technical rationality in empiric analytical sciences, and the practical-pragmatical tendency without a theoretical-epistemological and ethical-political reflection where pedagogical practice is superficially described.

Consequently the starting of the group was devoted to the extensive work of organisation and to reading national and international bibliography on topics such as research-practice relationships, relationships among students' and teachers' beliefs, conceptions and social representations, the role of theory in education research, and new methodological alternatives. Research on the epistemology of pedagogical practice in mathematics, that is about the process of emergence of school and didactic- pedagogical knowledge is also a focus of their interest. Members of the group are currently developing the following research:

• Professor Celi Aparecida E. Lopes has carried out a Master Thesis on Probability and Statistics in Compulsory Education: A curricular analysis and is starting her doctoral dissertation on the topic Theoretical and practical training of teachers to teach probability and statistics at Primary Education.
• Professor Wilton Sturn is finishing his Master Thesis on Some alternatives for teaching Combinatorial Analysis.
• Professor Paulo César Oliveira is starting his Doctoral Dissertation on the topic: Teachers' representations on the teaching and learning of statistics.
• Professor Dione Luchesi de Carvallo is starting her doctoral dissertation on the topic: The use of statistics projects related to their class mates profile as a means to recover the indentity of migrant students.

Virginica Rusu

Dept. of Economics, North University of Baia Mare, Romania

(chrisalex@excite.com)

Virginica is assistant professor at North University of Baia Mare, Romania, where she teaches statistics at the Department of Economic. She is also developing a PhD on "An informatic view on some forecasting alghoritms". She graduated in Economics at the Babes-Bolyai University of Cluj-Napoca, Romania, in Marketing at the University of Baia Mare, Romania, and in Geophisics at University of Bucharest, Romania. She has worked in marketing,, statistics, forecasting, data processing, and computers for different compnies. Her publications include papers in Romanian and international journals and conference proceedings.

César Sáenz Castro

Instituto de Ciencias de la Educación, Universidad Autónoma de Madrid,

Ciudad Universitaria de Cantoblanco, 28049 Madrid, Spain.

(cesar.saenz@uam.es)

César is a lecturer at the Department of Mathematics Education, Universidad Autónoma de Madrid, Instituto de Ciencias de la Educación. He is working in pre-service and in-service secondary teachers training. He has publihsed over 30 papers in Spanish and international journals. He is currently editing a book on the interdisciplinary study of weather and statisticas, which includes an educational software and teaching materials. We are including in this issue the summary of his PhD. on Intuition and mathematics in probabilistic reasoning and learning. He is also interested in the psychology of statistical education and in the teaching and learning of inference with the help of new technologies.

Maria Inés Rodríguez

Facultad de Ciencias Exactas, Fisico-Química y Naturales, Universidad Nacional de Rio Cuarto Ruta 8 - Km.608 (5800) Rio Cuarto, Córdoba, Argentina.

E-mail: mrodriguez@exa.unrc.edu.ar

Inés has got a Master in Biostatistics and is teaching mathematics, statistics and experimental design to students in Mathematical Sciences, Biology, Microbiology, Chemistry, and Agronomy. In her Department there is also a Master Program in Mathematics Education, Applied Mathematics and a Master program in Statistics. This is the first time these masters programs are bein held and the students are starting to carry out their theses. There are 6 lecturers teaching statistics out of a total of 36 leacturers in this department.

Ann Watkins
California State University, Northridge
Northridge, CA 91330-8313
E-mail: ann.watkins@csun.edu

Ann teaches statistics at her university and writes and edits probability and statistics curricular materials. She most enjoys working with secondary teachers who wish to teach statistics. She is chair of the College Board's Advanced Placement (AP) Statistics Development Committee.

Theodore Chadjipadelis: chadji@eled.auth.gr

Some readers will have seen the film "Shine" about David Helfgott, a brilliant, but severely disturbed, pianist. The film shows him waiting backstage before a competition and talking to Roger Woodward, also a brilliant pianist and one who achieved considerable success. Helfgott observes, "It’s a Jungle out there, Roger." The film goes on to show just how much of a jungle it can be for some. "Shine" was mainly filmed here in Adelaide where I work, partly on our university campus. From the outside, academia looks as neat and tidy as does our campus, but if we scratch the surface we can find quite a lot of jungle.

In particular, even after fifteen years in academic research, I still feel that the world of locating and using of previous academic work is a jungle, and does not seem to be getting better as technology improves and micro-chips become more powerful. With pressures on academics increasing yearly, the maxim "publish or perish" is seen as more and more critical. As a result, more and more papers are being published in more and more places. Electronic publishing means that this can be done more and more cheaply.

We all know how hard it is to keep up with this ever-increasing literature, even with the assistance of abstracting services like ERIC and ZDM and of select lists such as we publish in this Newsletter. Yet it also seems to be the case that referees will reject submitted papers on the grounds that "the author has not read the works of XXX and YYY," even though XXX and YYY have not even written in a language the author can read. The Tower of Babel is itself a jungle. I have even been told that I had not read the works of a person with a name as common as "Jones" and with no further indication of which "Jones" this might happen to be. In the course of following up such claims I have found one case of a cited article which simply did not exist at all in the stipulated publication, and another of an article whose title was quite different from that actually cited. Such problems do not make hacking away at the jungle any easier.

But, putting aside these examples of human frailty, the reality is that in our field it is no longer possible for journal and conference articles to refer to all relevant previous work in any meaningful sense. If we are to prevent undesirable fragmentation of research efforts our academic community needs to find new sets of criteria for assessing papers which retain academic standards, but which face the reality of the size of the publication jungle within which we have to work. I do not have any idea what the best solutions to this problem will be, but I am sure that this is an issue, which we need to address carefully in the next few years. Letters to the editors on this topic will be welcome.

The best part of being involved with an International Organisation such as the IASE is the opportunity of meeting wonderful people from around the world. I am sure that many will agree with me, that Andrejs Dunkels was on the top of the list of people we have been privileged to meet, listen to, work with, discuss ideas and have fun with.

Andrejs was born in Riga, Latvia, in 1939. With his family, he escaped to Sweden in 1944, but was unable to return to Latvia for many years because of the Russian occupation. From 1959 he studied Mathematics and Physics at Uppsala University then worked as a teacher and university lecturer. While working he continued his studies and obtained a MSc(Ed) in 1965. From 1966/1968 he established the Mathematics Department at the Kenya Science Teachers College in Nairobi, a Swedish Government foreign aid project, which trained teachers for lower secondary school. On returning to Sweden in 1969 he took up a position in the Mathematics Department at the Umeä University. Along with his teaching and further studies in mathematics, (obtaining a Licentiate in 1972, equivalent to a US PhD and a Diploma of Education (Honors) in 1973.

From that time on he worked at Luleå University, Sweden. He spent half his time teaching engineering students, the other half-teaching student teachers, specialising in mathematics for grades 1-7. In 1986 he was awarded Teacher of the Year at his University. Over a period of more than 20 years from the mid 1970's, Andrejs delighted conference delegates round the world with many invited conference papers in mathematics and statistics education, wrote many articles and was author and co-author of numerous text books especially for primary school children. He was also the illustrator and translator for a number of texts and was heavily involved with many associations and publications in a number of countries with wide ranging interests including "Mathematics in a Multi-cultural Society" and "Women in Mathematics". Despite his health problems he completed his PhD titled 'Contributions to mathematical knowledge and its acquisition' in 1996, was able to attend ISI in Beijing in 1995 and later do an international study tour. He had planned going to ICOTS-5, but had to pull out near the end.

At the start of this year we were devastated to hear that Andrejs died of a heart attack on the 30 December 1998. Many of his friends have the warmest memories of Andrejs. With his wife Kerstin Vännman he formed a wonderful partnership. They both showed a passion for the teaching of statistics and Kerstin was one of the leading forces in establishing the IASE. He was a most warm and caring person who made anyone in his company feel special. He will be remembered for his enthusiasm for living and particularly his gift for teaching mathematics and statistics. Whoever met him or heard him talk came away more enthusiastic about education. We will all miss Andrejs.

Below we include a selection of Andrejs's works in statistics education and mathematics education. An extended version of this note will appear in the next edition of the ISI newsletter. A more extended paper about Andrejs with comments from many friends has been put on the web under:

http://www.swin.edu.au/maths/icots5/andrejs2.html

This article draws attention to the fact that the mean is only one measure of central tendency among others, and that it should always be linked with a measure of dispersion such as the standard deviation. After summarising the definitions, properties and disadvantages of these two parameters, an example is used to present other measures of central tendency and dispersion.

GIRARD J. C., & PARZYSZ, B.(1998). Les maths, c'est pas la réalité ou de la modélisation en mathématiques (Maths, neither reality nor mathematical modelling). Bulletin de l'Association des Professeurs de Mathématiques de l'Enseignement Public (APMEP), 418.

This article aims to emphasise that between a real problem and its mathematical solution lies the process of modelling. This essential step is often implicit at school, which can lead to students' choosing a model by chance or as part of a "didactic contract". Two examples are used to illustrate the argument: proportionality problems at both primary and tertiary levels, and probability problems at secondary level.

Perry, B., JONES, G., THORNTON, C. A., Langrall, C. W., Putt, I. J., & Kraft, C. (1999). Exploring visual displays involving beannie baby data. Teaching Statistics, 21(1), 11-13.

This article describes the learning experiences of young children meeting stem-and-leaf plots for the first time.

ROSSMAN, A. J., Short, T. H., & Parks, M. T. (1998). Bayes estimators for the continuous uniform distribution. Journal of Statistical Education, 6(3).

Classical estimators for the parameter of a uniform distribution on the interval are often discussed in mathematical statistics courses, but students are frequently left wondering how to distinguish which among the variety of classical estimators are better than the others. We show how classical estimators can be derived as Bayes estimators from a family of improper prior distributions. We believe that linking the estimation criteria in a Bayesian framework is of value to students in a mathematical statistics course, and we believe that the students benefit from the exposure to Bayesian methods. In addition, we compare classical and Bayesian interval estimators for the parameter and illustrate the Bayesian analysis with an example.

SÁENZ, C., & León, Orfelio, G. (1998). El sistema de ideas probabilísticas de los adolescentes (Probabilistic ideas of adolescents). Infancia y aprendizaje, 59, 25-44.

In this paper we analyse the thinking of high school students (14-18 years old) about probability and randomness, following Fischbein's framework about intuitions. A questionnaire with 28 items was built, which covers all the probabilistic concepts taught at high school. In addition to answering the question, we asked the students to provide an estimate of their confidence in their response. We describe the students' ideas that were classified according to the level of intuitive acceptance.

WATSON, J. M. (1998). Professional development for teachers of probability and statistics: Into an era of technology. International Statistical Review, 271-290.

The focus of this paper is the professional development of teachers of probability at school level. Within a world where the statistics curriculum is changing at school level, the professional development needs of teachers of statistics are changing and the technology to meet these needs is changing as well. This paper reviews the work in the filed, describes the development of a multimedia package for professional development of statistics teachers and looks to the future.

WATSON, J. (1997). Chance and data for LUDDITES. The Australian Mathematics Teacher, 53(3), 24-29.

Workers destroying machinery in Northern England at the time of the Industrial Revolution were called luddites: hence the term is used to describe those who oppose technological innovation. This title was used to attract attention for a teacher development project conveying the opposite to the original meaning: "Learning the Unlikely at Distance Delivered as an Information Technology Enterprise". Throughout the three phases of the project there were two central concerns: the provision of essential content for teacher of chance and data, and the evaluation of various technologies for delivering the content to teachers across Australia.

WATSON, J., Collis, K. F., & MORITZ, J. (1997). The development of chance measurement. Mathematics Education Research Journal, v. 9(1), 60-82.

This paper presents an analysis of three questionnaire items, which explore students' understanding of chance measurement in relation to the development of ideas of formal probability. The items were administered to 1014 students in Grades 3, 6 and 9 in Tasmanian schools. The analysis, using the NUDIST text analysis software, was based on the multimodal functioning SOLO model. An analysis of the results and a developmental model for understanding chance measurement are presented, along with implications for curriculum and teaching practice.

In this project I investigate university students' orientations to learning statistics. The students who participated in my research were studying statistics as a compulsory component of their psychology course. My central thesis is that learning develops in the relationship between the thinking, feeling and acting person and the social, institutional and cultural contexts surrounding him or her. How students orient themselves or position themselves to learn statistics is reflected in their engagement with the learning task - their activities. These activities determine the quality of their learning and emerging knowledge. To understand student learning I draw on the powerful theories of Vygotsky (1962, 1978) and Leont'ev (1978, 1981). In particular, I extend and apply Leont'ev's construct of activity (Leont'ev, 1981). This suggests that individuals act in accordance with their purposes and needs which are shaped by and reflect histories and resources, both personal and cultural.

My investigation consists of two studies. Study One is a qualitative exploration of the orientations to learning statistics of five older students. These students sought help with statistics at the Mathematics Learning Centre where I work. My case studies of these students are inseparable from my efforts to help them learn statistics. Study Two is grounded in Study One. The main source of data for this broader study is a survey, which was completed by 279 psychology students studying statistics. In addition, I interviewed selected students and teachers of statistics. My findings suggest relationships among students' affective appraisals; their conceptions of statistics; their approaches to learning it; their evaluations and the outcomes of their actions. In Study One the relationships emerge from the students' descriptions. In Study Two I quantify the ways in which variables relate to each other. Structure for the data is provided by means of correlations, factor analysis and cluster analysis. The results support the systemic view of teaching and learning in context afforded by my theoretical perspective. Learning statistics involves the whole person (Semenov, 1978) and is inseparable from the arena of his or her actions.

The goal of statistics education is surely to enable students to develop useful, meaningful knowledge. My findings suggest that for many of the participants in my investigation this goal was not being met. Most of these students reported their reluctance to learn statistics and described adopting primarily surface approaches to learning it. A range of conceptions of the subject was expressed, but for many of the students statistical meaning was evidently reduced to performance on assessment tasks. Such orientations to learning statistics may lead to it becoming irrelevant and inert information. For a few students, however, the experience of learning statistics led to self-development and enhanced perspectives on the world in which we live. My project indicates the diversity of students' experiences. It raises issues as to why we teach statistics today and how the teaching and learning of statistics is being supported at university.

ORTIZ DE HARO, J.J. (1999). Significado de los conceptos proabilísticos elementales en los libros de texto de Bachillerato (The meaning of elementary probabilistic concepts in secondary school text books). PhD. University of Granada. Supervisors: Carmen BATANERO, & Luis SERRANO.

In this thesis we study the elementary probabilistic concepts from the theoretical and experimental points of view. The theoretical study is aimed to show the systemic nature of the meaning of mathematical concepts and their different type of elements, as well as the institutional and personal dimensions of knowledge. Our analysis of the elements of meaning for each probabilistic concept, the comparison of its presence or absence in the text books, and the diversity of ways in which they are presented point to the various meanings given by the text books to the same concept at the same teaching level.

The experimental study consisted of a detailed analysis of the presentation of probability in a representative sample of secondary school textbooks published in the period 1975-1991. This study has been carried out at two different levels. A first qualitative analysis of the intensional and extensional elements of meanings identified in the theoretical study has been carried out in the whole sample of books. This is complemented by a quantitative study of the task variables in the exercises and examples and by a qualitative analysis of representational elements of meaning in two textbooks.

A first result is the theoretical analysis and the list of elements of meaning identified for each probabilistic concept, which can serve in the analysis of other textbooks, in building assessment instruments and in designing didactic materials for teaching probability. Our study also serves to characterise the result of didactic transposition of probabilistic concepts in secondary education, emphasising its strong points, as well as its biases and limitations. Other results are the characterisation of task variables in elementary probabilistic problems, the empirical study of its distribution in two books, the analysis of the curricular framework in this period and the survey of research concerning mathematics textbooks.

SÁENZ-CASTRO, C. (1995). Intuición y matemáticas en el razonamiento y aprendizaje probabilístico. (Intuition and maths in probabilistic reasoning and learning). PhD. Universidad Autónoma de Madrid. Supervisor: Ofelio León García.

The two main goals in this research were: 1) to analyse and categorise secondary school students' ideas about chance and probability; 2) to design and test efficient teaching methods that take into account students' alternative ideas. Our aim was to improve the research framework regarding students' alternative conceptions, which is usually intended to determine the students' wrong ideas about a particular scientific field. This is a useful but limited goal. Even when teachers are provided with these lists, they do not usually have a specific teaching proposal to deal with these alternative ideas.

Two empirical studies related to the first objective were carried out. A first pilot, exploratory study was carried out with University students. A second empirical study, based on Fischbein's theory of intuitions, was focused on secondary school students (13- 18 year- olds). This was done because there is a scarcity of studies related to adolescents' probability understanding, even when researchers such as Green, Piaget and Inhelder, and Shaughnessy, have suggested that adolescence is a crucial period in the stochastic conceptual development. This research allowed us to establish: a) A "conceptual ecology" system of adolescents' personal ideas about chance nature, language and measurement, and about assigning probabilities, in the sense of Posner, Strike, Hewson and Gertzog's (1982); b) The contingent and constructive nature of students' probabilistic reasoning, which depends on task and subject factors. Instruction in probability was the most influential factor among the different subject variables.

Our second aim was to design and test a didactic teaching method regarding probability. We found three different approaches in previous studies of probabilistic reasoning and learning: mathematical-historical, psychological and didactical. The lack of relationship between these three approaches strongly attracted our attention and, therefore we tried to relate and integrate the different perspectives of the problem. Our didactic proposal has a double theoretical inspiration: 1) Hakata's epistemology regarding the quasi-empirical nature of mathematical theories; 2) Poser et al.'s conceptual Change Approach to the teaching -learning process. It was also articulated around seven elements derived from the three aforementioned approaches.

To answer the question "Is our didactic proposal more efficient than a traditional methodology?" we designed three achievement indicators: knowledge of probability calculus, quality of probabilistic reasoning and change produced in attitude. Experimental students performed better with knowledge of probability calculus and quality of probabilistic reasoning, with a smaller presence of wrong ideas about probability and chance. There was not significant progress in students' attitudes towards mathematics as compared with the control students.

Some methodological questions arose in view of Borovcnick and Bentz (1991) critiques to empirical research on probabilistics understanding. Assuming that the problem structure and wording might affect students' answers, we applied the range of tasks to unambiguous random situations and to unexplored research fields (chance language, chance measurement, etc). Moreover, the task structure was based on probabilistic judgement rather than on choice. Students had to decide whether a probabilistic reasoning was correct or not, assigning a confidence degree to their judgement. This degree, taken from the Calibration Paradigm, within the conductive decision theory, provides information about the intuitive strength of the subject's ideas, whether it is correct or not. This task structure serves to categorise three levels of probabilistic concepts: intuitive, counterintuitive and internally contradictories, which were used to compare the conceptual change level in experimental and control students. One main problem in our research was the teachers' scientific and didactic training. A seminar of 100 hours was organised with two objectives: a) to reflect on the teacher's probabilistic conceptions; b) to reflect on the correct way of teaching probability. Finally, the following unsolved questions, which require a more extended and urgent study were enumerated: 1) the role of metacognitive strategies and affective factors in learning probability; the role of computers in learning probability; and 3) adolescents' probabilistic thinking outside school.

LOPES, C. E. Probability and statistics in compulsory education: A curricular analysis. (Probability and Statistics in Compulsory Teaching: A curricular analysis). Masters Thesis. Universidade de Campinas.

The aim of this study was to investigate and analyse probability and statistics teaching within the mathematics curriculum in compulsory education. The question in this research was the following: Which are the objectives of probability and statistics in the proposed mathematics curriculum in the states of Minas Gerais, Sao Paulo, Santa Catarina and the National Curriculum Parameters, taking some international curricula as referents?

To carry out this analysis the following criteria were followed: The statistics and probability conceptions underlying these proposals; the selection of probability and statistics notions to be "transposed" to the school level; the way in which these proposals suggest the treatment of these notions with the students and the explicit or implicit aims of teaching these notions to the students. From these criteria we considered some aspects emerging from the analysis and we pointed out to the importance of these topics in the students' training to produce a break with the deterministic vision of mathematics.

The teaching of probability and statistics can be a wide space of interdisciplinary work and provide an exploration of the idea of chance, using experiments. By carrying out observations, recording and representing data, students would be able to read and interpret differentiated information. Statistical concepts are important tools to solve problems and to help students to take decisions. We therefore underline the necessity to provide learning situations that enable to develop statistical thinking and from here to form critical citizens.

This book, with a Foreword by the outstanding philosopher of science and mathematical psychologist Patrick Suppes of Stanford University, is the outgrowth of the work developed within the "Groupe Mathématiques et Psychologie", a research unit of the University René Descartes and CNRS (the French National Center for Scientific Research). New ways in statistical methodology are presented, which complement the familiar significance tests by new methods better suited to the researchers' objectives, in the first place, Bayesian methods. In mathematical statistics, Bayesian methods have made a breakthrough in the last few years, but those developments are still ignored by the current statistical methodology and practice. The present book is really the first one to fill this gap.

This book is written for a large audience of researchers, statisticians and users of statistics in behavioural and social sciences, and contains an analysis of the attitude of researchers toward statistical inference, and concrete proposals for improving statistical practice. The statistical consulting experience of the authors is centred around psychology and covers a broad range of subjects from social sciences to biostatistics. All methods developed by the authors are implemented in software.

1. Foreword by Patrick Suppes
2. Rouanet, H. - Statistics for researchers, 1-27.
3. Rouanet, H. - Statistical Practice revisited, 29-64.
4. Lecoutre, M.-P. - And...What about the researcher's point of view, 65-95.
5. Rouanet, H., & Bert, M.-C. - Introduction to combinatorial inference, 97-122.
6. Lecoutre, B. - From significance tests to fiducial Bayesian inference, 123-157.
7. Bernard, J.-M. - Bayesian inference for categorized data, 159-226.
8. Rouanet, H., Le Roux, B., Bernard, J.-M., & Lecoutre, B. - Geometric data: From euclidean clouds to Bayesian MANOVA, 227-254.

Editorial Note: This quarter’s extremely thorough bibliography has been prepared by two colleagues, each of whom has prepared two dissertations in the field. Between them their interests cover, pedagogy, understanding, technology and textbooks. We are all aware of weaknesses in students’ understanding, but these researchers have gone further, and have examined how we can use computers and textbooks actually to improve this understanding. So this bibliography may be seen as the result of studies which have been deeply based. While they are confined to Spain, it is likely that they have wide application, and we hope that this bibliography will inspire others to undertake similar studies.

Some of the references are of particular interest because they address issues outside the main stream of research studies. Several come from the Journal of Abnormal Psychology and look at responses outside those to be expect from "average" people. One of these looks at "illusory correlation", which is probably not a pathological response, and in fact gets several references in other journals as well. Some papers look at scatter plots, and others at contingency tables. From this bibliography it does seem that more work needs to be done on how people make links between the two. Finally, we may note that this bibliography contains no references from Teutonic languages. Many stochastics research workers seem to be able to cross the boundaries set up by the various romance languages, but we do not seem to be as good at reaching across the Teutonic boundary. We would be most grateful if one of our German, Dutch or Scandinavian members could supplement this list with some relevant work in their language.

Information is provided on how to gather the necessary pieces to write, compile, and execute a Java program. Monte Carlo estimation and simple linear regression are used as tutorial examples of the versatility of Java.

Clarke, G. M. (1999). What is the Royal Statistical Society? Teaching Statistics, 21(1), 2-3.

This is the first of a short series of articles briefly describing the organisations that sponsor Teaching Statistics.

Conners, F. A., Mccown, S. M., & Roskos, E. B. (1998). Unique challenges in teaching undergraduate statistics. Teaching of Psychology, 25(1), 40-42.

The statistics instructor faces four major challenges unique to this course: motivating students to study material they think is uninteresting, handling math anxiety, dealing with performance extremes, and making the learning memorable. We discuss each challenge along with solutions offered in the literature.

Gatti, G. G., & Harwell. M. (1998). Advantages of computer programs over power charts for the estimation of power. Journal of Statistics Education, 6 (3).

Statistics and research design textbooks routinely highlight the importance of a priori estimation of power in empirical studies. Unfortunately, many of these textbooks continue to rely on difficult-to-read charts to estimate power. That these charts can lead students to estimate power incorrectly will not surprise those who have used them, but what is surprising is that textbooks continue to employ these charts when computer software for this purpose is widely available and relatively easy to use. The use of power charts is explored, and computer software that can be used to teach students to estimate power is illustrated using the SPSS and SAS data analysis programs.

Gibson, B. (1999). Industrial visits work. Teaching Statistics, 21(1), 4-7.

This paper describes how visiting industry help students to see how statistical methods are used in practice.

Lan, W. Y. (1998). Teaching self-monitoring skills in statistics. In D. H. Schunk, B. Zimmerman, et al. (Eds.), Self-regulated learning: From teaching to self-reflective practice (pp. 86-105). New York: Guilford Publications.

This chapter presents findings of studies the author conducted with 69 students in a college statistics course and shows how self-monitoring (SM) affected various aspects of college students' learning. Analyzing the reasons for students' SM deficits in the class, the author decided that the deficits were primarily caused by cognitive factors and that it was the challenging learning tasks and students' state-oriented thinking that used up their information-processing capacity and prevented them from SM their own learning. An external cue triggering a SM process was needed to help students to engage in SM when studying statistics. The cues used were protocols designed to direct students' attention to their own learning activities or the instructor's teaching activities. Students were randomly assigned into SM, instructor-monitoring, or control conditions. As predicted, students in the SM condition outperformed their counterparts in the instructor-monitoring and control conditions on the course examinations and increased the frequency with which they use other self-regulated learning strategies.

Magel, R. C. (1998). Using cooperative learning in a large introductory statistics class. Journal of Statistics Education, 6(3).

This article discusses one active learning technique, cooperative learning, that can be used in large classes. This technique requires that students be divided into learning teams. A method for quickly dividing a large class of students into learning teams is presented. Two examples of cooperative learning exercises used in an introductory statistics class are given. These serve as illustrations of the type of cooperative learning exercises that can be assigned in a large class. In particular, these exercises were used in a class of 195 students. Preliminary findings by the instructor of the advantages of using cooperative learning exercises are discussed.

Sgoutas-Emch, S. A., & Johnson, C. J. (1998). Is journal writing an effective method of reducing anxiety towards statistics? Journal of Instructional Psychology, 25(1), 49-57.

This paper examines the efficacy of journal writing in reducing perceived anxiety and physiological reactivity towards a statistics course required for a major in psychology. Subjects were 44 undergraduates. Their performance, attitudes, and anxiety towards the course were compared with a control group who did not keep a journal. Results show that the journal group showed improvement in their grades, lower anxiety before exams, and lower physiological reactions. Research suggests that journal writing may be an effective tool in curtailing feelings and responses to exams in statistics and possibly other related courses.

Smith, G. (1998). Learning statistics by doing statistics. Journal of Statistics Education, 6(3).

To help students develop statistical reasoning, a traditional introductory statistics course was modified to incorporate a semester-long sequence of projects, with written and oral reports of the results. Student test scores improved dramatically, and students were overwhelmingly positive in their assessment of this new approach.

West, R. W., & Ogden, R. T. (1998). Interactive demosntrations for statistics education on the World Wide Web. Journal of Statistics Education, 6(3).

The World Wide Web (WWW) is a tool that can be used in many ways for basic statistics education. Using the latest WWW technology, educators can now include interactive demonstrations in the form of Java applets within their WWW materials. Six example applets developed by the authors are introduced and discussed. Suggestions for class use are made, and instructions for incorporating the applets within a WWW document are given.

13. 2. MATHDI database is now available via the www

MATHDI (MATHematical DIdactics) is the most comprehensive and up-to-date computerized information service in the fields of mathematics education and computer science education, elementary mathematics and its applications as well as psychological and pedagogical issues for mathematics and science education. MATHDI is the online-version of the well-known international abstracting service in mathematical education: ZDM. Important features of this new service are:

• worldwide unique access to literature on research and practice in mathematics education from 1976 to present: more than 76.000 entries.
• on screen TEX or Postscript view of full review text
• easy menu search
• hypertext links to authors, and classification, ....
• links to the EMIS (European Mathematical Information System) server with access to the database MATH and free e-journal access, conference calendar, and other services offered by FIZ Karlsruhe.
• Free access to the snupper version (Sneak preview with only three items for any question)

All a user needs to do is to open the URL: http://www.emis.de/MATH/DI.html. More information is available from ZDM Gerhard Koenig, managing editor ( gk@fiz-karlsruhe.de). For a list of more events and other information in the area "technology in mathematics teaching" visit the webpage at http://www.kutzler.com

• Statistical Education and the Significance Tests Controversy, organised by C. BATANERO. The following papers will be presented: Beyond the significance test controversy, by Bruno LECOUTRE, Students' difficulties and errors in the learning of statistical tests, by Angustias VALLECILLOS, and Teaching hypothesis testis. Can it still be useful? by Henrik DAHL. Reactors will be Paul K. ITO, and Michael CAPOBIANCO.
• Issues Involved in the Assessments and Evaluation of Student Learning of Statistics, organised by J. GARFIELD. The following papers will be presented: How to assess large groups with the minimal amount of resources but serving quality, by Susan STARKINS, A morel of classroom assessment in action: using assessment to improve student's learning and statistical reasoning, by Beth Chance, and Assessment in statistics using the personal computer, by Giuseppe Cichitelli. Reactors will be Dani BEN-ZVI, and Gilberte SCHUYTEN.
• Teaching and Training Multivariate Data Analysis, organised by H. BACELAR-NICOLAU. The following papers will be presented: Teaching data analysis to statistics students, by A. Rizzi, Introduction á la classification en sciences humaines, by George Le Calvé, Discussion, debate and disagreement teaching multiple regression to business students, by Peter G. Bryant, and Teaching multivariate data analysis in the fields of biology and ecology, by Hans-Peter Baeumer. Reactors will be Gilbert Saporta, and F. Costa Nicolau.
• Visualisation as an Educational Tool, organised by L. Weldon. The following papers will be presented: Graphical excellence: the importance of sound principles and practices multimedia, by Thomas E. Bradstreet, Emphasising activities and visualisation in teaching introductory statistics by interactive multimedia, by Hans-Joachim Mittag. Clovis Pérez is presenting another paper. The reactor will be Andrejs BLEJEC.
• Statistical Education Using Flexible Learning Approaches, organised by A. Di Ciaccio. The following papers will be presented: A toolkit for an interactive learning environment, by Deborah Nolan and Duncan Temple Lang, Teaching statistics with internet: a survey of available resources and the Statnet project, by Gilbert Saporta, and Why do students find statistics so difficult by James B. Ramsey. Reactors will be Gainfranco GALMACCI, and Juha Puranen,
• Statistical Training for People Working in and with Official Statistics, organised by C. BLUMBERG (IASE) and R. Smulders (IAOS). The following papers will be presented: The dissemination of statistical literacy among citizens and public administration directors by Luigi Biggeri, Training official statisticians in communicating with users: a review of current practice and possible improvement by Rudols Teekens, and New and emerging demands for statistical training in response to user needs in the 21^st century by Linda Hewitt. Reactors will be Jayanta K. Ghosh, Mario Palma Rojo and Paul Cheung.
• Statistical Education for Life, organised by Brian PHILLIPS and Anne HAWKINS. The following papers will be presented: Justice by the numbers: educating judicial decision makers, by Mary Gray, Official statistics and the outside world, by Vincenzo Lo Moro, and Helping the public to understand risk by Amanda Burls. Reactors will be Helena BARCELAR-NICOLAU, and Geoff Laslett.

Other sessions of interest for statistical education are: Session 3, History of ideas in statistics and probability in Scandinavian countries, Session 6, Panel discussion on Statistical literacy, Session 11, Critical issues for statistics in the next two decades, Session 13, Statistics in art, Session 14, Information revolution and statistics in developing countries, Session 15, Opportunities for statisticians in business, industry and public service, Session 19, Panel discussion on Statistics, science and the media, Session 50, Official statistics in the 20^th century, historical perspective, and Session 74, The role of women in statistics in the new millennium, The indicative list of topics for contributed papers drawn up by the Local Programme Committee contains the following topics: Teaching basic statistics; Educating statistical majors; Statistical education; Teaching statistics for non-statisticians; Statistical Literacy and Statistical consulting. More instructions and information can be found at http://www.stat.fi/isi99

You will find the complete 1st announcement via

http://wwwmath.uni-muenster.de/math/inst/didaktik/u/meissne/WWW/complete1.htm. More information is available from Prof. Dr. Hartwig Meissner (meissne@uni-muenster.de).

The 51st conference of International Commission for the Study and Improvement of Mathematics Education (Commission Internationale pour l'Etude et l'Amélioration de l'Enseignement des Mathématiques), (CIEAEM) will take place in Chichester, Sussex, England, 21-26 July 1999. The general theme of the conference is Productive Collaboration in Mathematics (Education) across Cultures. For further information, please contact CIEAEM 51, The Mathematics Centre, Chichester Institute of Higher Education, Upper Bognor Road, Bognor Regis PO21 1HR, England. Email: maths@chihe.ac.uk

The annual Conference of 1999 is scheduled in Haifa, Israel, from July 25 to July 30.Information may be obtained from the Conference Secretariat (pme@netvision.net.il) or the home page of the conference: http://edu.technion.ac.il/conference/pme23. Information about the PME Project Group activities may be get from John Truran (jtruran@arts.adelaide.edu.au).

The 9th International Conference on the Teaching of Mathematical Modelling and Applications, ICTMA 9, will be held in Lisbon, Portugal, 30 July - 3 August 1999. For further information, please consult the Chair of the Programme Committee, Professor João Filipe Matos, Departamento de Educao, Faculdade de Ciencias, Universidade de Lisboa, Portugal (joao.matos@fc.ul.pt),

The 4th International Conference on Technology in Mathematics is being held in Plymouth, England from 9th to 13th August 1999. The conference is being organised jointly by the Centre for Teaching Mathematics at the University of Plymouth and the University College of St. Mark and St. John, Plymouth. Information can be obtained from Karen Eccles (keccles@plymouth.ac.uk) or at the web address: http://www.tech.plym.ac.uk/maths/CTMHOME/ictmt4.html

In 1999, in Argentina the CLATSE 4. Congreso Latinoamericano de Sociedades de Estadistica, will be held in Mendoza, from July 26 to July 30 organised jointly by the Sociedad Argentina de Estadistica (SAE) and the Sociedad Chilena de Estadistica (SOCHE). Sessions on teaching statistics at all levels will be organised by Ana Silvia Haedo, Vice-President of the SAE in collaboration with the IASE. More information may be obtained from Ana Silvia Haedo (haedo@qp.fcen.uba.ar) and from the Web site: http://fce.uncu.edu.ar/clatse4.htm

The five-year interuniversity co-operation PRESTA Programme was set up in 1994 by the Laboratoire de Méthodologie du Traitement des Données of theUniversité Libre of Brussels, Belgium in co-operation with other European Universities, and with the support of the European Union. PRESTA is now
organising a Conference on the Teaching of Statistics with the help ofASE, which will be held at the Universidade Federal de Santa Catarina (UFSC), Florianópolis, Brazil in September, 1999. The International Programme Committe is formed by:

Prof. Brian Phillips, IASE President-Elect, Swinburne, Australia (bphillips@swin.edu.au);

The Mathematics Education Into The 21st Century Project, co-ordinated by Dr. Manmohan S. Arora, Associate Director, Mathematics Resources & Technology Centre, Clark Atlanta University, USA, is planning a series of International Conferences to be held throughout the World leading into the next millennium. The first of these will be in Egypt in co-operation with the Third World Forum. It will be chaired by Prof. Ismail-Sabri Abdalla - Former Director of The Institute of National Planning and former Minister of Planning (Egypt). The Local Organising Committee is Chaired by Prof. Fayez M. Mina, Professor of Curriculum and Instruction, Faculty of Education- Ain Shams University, Cairo. The conference will include contributions already made to the project by leading mathematics educators world-wide. Individual papers are also welcomed from those planning to attend on the themes:

• The impact of new developments in knowledge on mathematics education (e.g. multiple intelligence, limits to problem solving, mathematics of complexity modelling)
• Societal Conditions (e.g. mathematics in and for different cultures, linguistical limitations, examples from life and from the environment)
• Information Technology and Society (e.g. interactive solving of problems, self-learning, modelling and simulating system dynamics)
• Classroom Practice (e.g. curriculum development, psychological aspects, the teacher of the 21-Century, creativity).

For further information and a copy of the First Announcement please email your contact details to arogerso@mgs.vic.edu.au (or write to Dr. A. Rogerson, 22 Violet Grove, Hawthorn, Vic 3122, Australia).

The forthcoming ICME-9 Conference will be held in Tokyo/Makuhari (Japan), since July 31 to August 6, in the year 2000. Prof. Hiroshi Fujita, Chair of ICME-9 IPC, has invited Dr Susan Starkings, the ICME-9 contact facilitator, to be the chief organiser of the Topic Study Group No. 4 on: The Teaching and Learning of Statistics. The Topic Theme is: Statistics and Statistical Education for the year 2000 plus. Papers are particularly invited on statistical education from for children aged 11-18, students in higher education, and also for adults, and which fall into one of the following categories:

If you want to submit an abstract for a paper, then please contact to organiser:Susan Starkings, Head of Mathematics Support, Caxton House, South Bank University Borough Road,London SE1 OAA, England.

Since 1968, a number of Round Table Conferences have been organised on statistical educational topics, initially by the Education Committee of the International Statistical Institute and, since 1988, by IASE (the International Association for Statistical Education). It has been usual for these conferences to be held as satellite meetings to each ICME (International Congress on Mathematics Education). Next Round Conference will be held in the year 2000 at Meiji University (Tokyo), after ICME 9 (International Congress on Mathematics Education). An IASE publication on the theme of the conference will follow. Please remember that the first deadline for receiving proposals is June, 30, 1999. The following are possible topics and issues to be discussed at this the Round Table Conference:

• Statistical competencies that researchers in different disciplines should acquire in their postgraduate training;
• Statistical training of researchers in specific fields;
• Assessing/ identifying frequent errors in the use of statistics;
• Consultation as a teaching/ learning process;
• Researchers' attitudes towards statistics and its effect on the role of data analysis in experimental research;
• Informal statistical learning from reading research literature;
• Effects of technology on the statistical training of researchers;
• Design/ evaluation of courses for training researchers in particular statistical topics and learning problems.

Suggestions should be sent to Lionel PEREIRA MENDOZA.

Plans to held ICOTS-6 in the Summer of 2002 are already under way. The venue is Durban, in South Africa, during mid July. The IASE will make a concerted effort to attract participation from African developing nations, in part offering funds to delegates as was the case at ICOTS-5. The International Programme Committee (IPC) is formed at present by:

• Maria-GABRIELLA Ottaviani, Italy, Chair
• Brian PHILLIPS (Australia), International Organiser
• Dani BEN-ZVI (Israel), IPC Secretary
• Delia North, (South Africa), Chair of the Local Organising Committee