Proceedings

  • The Turkish system of education is undergoing great structural changes. The centralized system is becoming more flexible, giving schools and students the opportunity to develop and select new courses based on the needs and interests of the students and the environment at the secondary level. Statistics appears for the first time as a separate four-hour per week elective course in the secondary programs. The changes require the development of new curricula on different subject areas and the revision of the present curricula. The mathematics curricula at all grade levels (K-11) have been revised by the National Mathematics Curriculum Development Committee established by the Ministry of Education in February 1990 and the revised curricula are being implemented in the 1991-92 school year. The place of statistics has not changed much in the revised mathematics curricula. Being a member of the above mentioned Committee, the researcher has observed that the mathematicians and the mathematics teachers do not seem to consider statistics as an area to be taught in mathematics. They mainly concentrate on algebra and geometry. It can easily be concluded that since those people do not have the necessary background and training in statistics, they view statistics topics, which interfere with their conception of mathematics, critically. Many modes of teaching and interpretation which are particular to statistics, as compared to traditional mathematics, are viewed skeptically by the mathematicians and the mathematics teachers. Considering the above situation, the researcher undertook a survey of the place of statistics in general education in Turkey. The results of this study show that the mathematics teachers who are presently responsible for teaching statistical topics at the primary and secondary levels do not have necessary background in statistics and do not possess the necessary skills for teaching statistics.

  • Because of the direct link between a country's socio-economic conditions and its system of education, there exist enormous differences between the educational systems of the developed and the underdeveloped countries. Consequently, the quality of statistical education in developing countries varies, both in courses and teaching methods. As such, there cannot be a uniform strategy for educational improvement in various parts of the world. Efforts to improve the quality of education in any country will necessarily have to take into account its economic and socio-cultural realities and, as such, there is a need for developing an in-depth understanding of the socio-economic conditions of various countries of the world. This paper presents a review of the existing situation of statistical education in Pakistan. Various problems have been highlighted, the objective being to assist the International Statistical Institute in developing a deeper understanding of difficulties associated with statistical education in some of the underdeveloped countries.

  • This paper elucidates the way Data Analysis was introduced through Mathematics in the schools of Indonesia prior to 1994, and what approach could be used in the 1994 curriculum to make Indonesian Middle School students of the turn-of-the-century quantitatively literate.

  • In France, data analysis is a part of the curriculum of primary schools (students younger than 11 years old). In primary schools, one teacher teaches all the subjects in the curriculum. In secondary schools (students from 11 to 18 years old) the style of education is very different and there is a different teacher for each subject. However, data analysis is still part of the curriculum in mathematics, economics, geography, biology, etc. with each teacher developing his/her own methods for data analysis. We will emphasize this point later. This paper offers a definition of data analysis, states goals for teachers and describes what is appropriate for the schools.

  • In 1989, the UK National Curriculum in Mathematics (Department of Education and Science, 1989) was introduced and the philosophy that statistics is a subject for all gained ground. Within the UK National curriculum, statistics (or "handling data" as it is known) now features throughout the years of compulsory education, i.e. it applies to all students between the ages of 5 and 16. For the purposes of this paper, "statistics" may be considered to be synonymous with "all the activities which pertain to data analysis", in which the role of uncertainty, or "probability", would be considered to be necessary for a full understanding of data analysis. At the 1988 ISI Round-table Conference Training teachers to teach statistics (Hawkins, 1990), the delegates concluded that there was a shortage of trained teaching personnel, both in the UK and throughout the world. Therefore, before addressing the question, "Who should teach statistics?" the 1992 Round-table delegates might have to consider the question, "Who is equipped to teach statistics?" When we attempt to answer this question, it may well be that views will emerge about the sort of person who would be most appropriately qualified (with a small "q") to teach statistics. However, if it were to be shown, for example, that only certain teachers have received any training at all in statistics, then, at least until this balance is redressed, these are presumably the teachers who "should" teach statistics.

  • With the increasing availability of computers, it is important that the educational community develops data-based computer packages for use in schools. Such packages should be more than data bases, per se. In order for them to be used effectively they should contain ideas for activities that can be integrated into the classroom. Statistics Canada has developed an electronic learning package exclusively for the education market. This electronic learning tool, called E-STAT, is based on Compact Disc Read Only Memory technology (CD-ROM) which allows storage of vast amounts of data. On one CD-ROM disc, E-STAT becomes two of Statistics Canada's most popular CD-ROM products. This report gives an overview of the potential applications of E-STAT to the high school curriculum. It is easy to see that the potential goes beyond the scope of the samples given here. One of the strengths of this tool is its adaptability to the needs and approaches of the individual teacher. The examples illustrate that E-STAT is a valuable computer-aided learning tool to support education as well as a reliable and current reference tool to support research in school resource centers. It has the advantage that the information/data is/are more current and comprehensive than most text books. Furthermore, through periodic updates, the information can be kept current.

  • The aim of this paper is to attempt an answer to the questions posed in the title. Geographically or economically speaking, countries vary from developing to developed, from the North to the South, and from East to West. Within each geographical context, let alone amongst them, there is a wide range of jobs, occupations, positions, etc., each of which has its own data analysis requirements. These requirements vary to suit macro versus micro levels; high management and executive levels versus middle, low and other managerial levels; and research and policy making levels versus administrators and clerks. Consequently, given the complexity of situations in which data analysis will be used there cannot be unique approaches to teaching data analysis. Such is the situation in the world of work. However, the situation is not much different in the world of education. The variety of audiences who can, or wish to, be taught data analysis include parents, teachers and business people in different sectors, government employees who, in turn, are scattered among different ministries and departments which certainly are not unique. What are the implications of this diversity for teaching data analysis? The remainder of the paper is organized into five sections: (a) The teaching/learning load and the teacher's role; (b) School children and the future; (c) A framework for a course on data analysis for schools; (d) A course on data analysis for schools: and (e) Conclusion

  • The aim of this paper is to draw attention to the main areas where data analysis is currently being taught, namely: (i) mathematics containing a data analysis element; (ii) specific courses in statistics; (iii) data analysis taught specifically in other subject areas and (iv) courses which make an inherent assumption of statistical knowledge. Furthermore, the paper and presentation are designed to promote discussion on appropriate teaching methods of data analysis within our educational establishments.

  • Statistical methods are widely used in everyday life and research. Users are very different in their abilities and skills. Given the diversity of users every statistical educator must find a way to teach statistics and to decide what is important and understandable for a specific group of users. We shall try to present some views of the teaching of statistics.

  • The need for mathematically literate students who can function on a technology driven society, together with the demonstrated lack of success of the current mathematics curriculum, has paved the way for major reform efforts in mathematics in the United States. One of the reform documents, Reshaping School Mathematics, a philosophy and framework for curricular change published by the National Research Council (1990), suggests, "Most obvious, perhaps is the need to understand data presented in a variety of different formats.... Citizens who cannot properly interpret quantitative data are, in this day and age, functionally illiterate" (p. 8). Leading proponents of change to school mathematics, including the National Council of Teachers of Mathematics (NCTM) and the Mathematics Science Education Board, emphasize that data analysis must be a key component of a revitalized curriculum if mathematics is to relate to the practical world of the student and if it is to provide the necessary skills for living in an information age. This paper describes the NSF funded project: " A Data Driven Curriculum," for students in grades 9 - 12. The project addresses two needs: how to use data analysis to motivate some of the essential topics of a restructured mathematics curriculum, and how to identify and teach those data analysis skills that are required for effective participation in society.

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