• This paper asks various questions concerning the relevance of Exploratory Data Analysis (EDA) ideas for teaching 16-19 year old's, and reports on a workshop which considered these questions. Four key questions can be posed which are pertinent to the question of preparing EDA materials for use at school level: (a) are EDA ideas relevant at this level? (b) if so, then which ideas and techniques should be taught? (c) which data sources are sufficiently motivating for this age group? (d) how should or could such material be prepared?

  • The teaching of basic statistics course can be greatly enhanced with the use of widely available statistical software. Pocket calculators can relieve some of the computational drudgery of statistics but are of little help with data plotting, one of the key steps in the statistical analysis process. By using computers in basic statistics courses, we can present students with real data sets and problems and teach them how to approach and analyze data. In this paper, the basic steps in the statistical analysis process are listed, and this paper, the basic steps in the statistical analysis process are listed, and the important role that computers can play in some of these steps is emphasized.

  • Computers were invented and constructed to compute. Since statistical analyses are computing intensive it is natural that computers are widely used in statistical research and applications. Statistical applications, such as census with its problems of sorting, counting and tabulating, were among the motives for constructing the ancestors of modern computers. It was always clear that students have to be taught how to use computers, because they will use them in their later careers. With the development of modern technology, computers evolved from large mainframes to personal computers, available for individual use. Availability of personal computers changed the way of computer usage and allowed computers to be incorporated into the teaching process in various disciplines. In particular, can computers be useful in teaching of statistics? If yes, to what extent? What changes in the teaching process are needed if we want to apply computers efficiently? There are many other questions related to the usage of computers in teaching. I would like to present some of my views about computers in teaching of statistics.

  • Video, in the form of broadcast television, is the most popular medium for entertainment and news in the developed world. A television set is one of the first substantial purchases made by households in developing areas as their wealth increases. These phenomena testify to the power of video to hold attention, a power which can also be applied to formal teaching. Video can be used for teaching in several settings: learning at a distance for geographically scattered students, as a supplement in traditional classroom settings, and as a component of new technological learning systems. In each case, wise use of video requires an understanding of both the strengths and weakness, drawing both on practical experience and on cognitive research. We will then suggest appropriate uses of video for teaching statistics in the three settings just mentioned.

  • The teaching of statistics from kindergarten to graduate university levels is of great importance, and everyone here is concerned with aspects of that teaching. The present talk deals with a less structured side of our statistical outreach: presenting statistical thinking to the several great publics that are out there beyond the classroom and beyond formal education. What of statistics can we transmit to nonstudents in legislatures, courts, factories, the military, the nursery, and so on? How to transmit it? That outreach is important not only for its own direct sake; it also is important indirectly, for, in one way or another, the broad publics out there strongly influence what is done statistically in schools and colleges. I have three broad themes. First, I discuss the natural desire of statisticians to be understood and encouraged by society at large. (Along with that, I discuss parallel natural desires by other groups.) Second, I make suggestions about kinds of statistical lessons for the public . . . which differ from statistical lessons in school. Third, I end with a speculative analysis of the unfortunate near-absence of song, story, and rousing myth that might underlie statistics.

  • The so-called operative method has its roots in the work of J. Piaget. His concept of the "operation", both concrete and formal operation, and the psychological approach. We have learned from psychology that the learning of operational concepts has to be linked with the attributes of the operative method above mentioned. It is the experience of many teachers that pupils accept and make use o the operative attributes when problems are posed according to the operative principles, that pupils deal - sometimes - consciously with these attributes of tasks or problems, and that a special sort of active behavior is developed during a long term learning process according to this didactical design. Pupils between 12 and 15 years of age - especially the "slow-learners" - have to solve a large number of assignments before they can begin and carry out a process of generalization. One of the goals is to concretize learning through discovery; therefore formal solutions remain somewhat in the background, whereas more emphasis is placed upon the activities of the pupils and their dealing with variation in situation and tasks.

  • The following paper will present some tentative ideas for the discussion on how the further evolution of curricula may react to changes in statistics which have become visible by the emergence of EDA. The emergence of Exploratory Data Analysis (EDA) presents a challenge to more traditional views, attitudes and value systems of statistics, which are often also the implicit basis of curricula and teaching approaches to statistics and probability. Simple examples, ideas and techniques of EDA are sometimes considered to be a new curriculum content, because it is hoped that they may replace the rather boring teaching of techniques of descriptive statistics by more interesting examples of real data analysis, where the students may become more actively involved in processes of discovering relevant features of the systems the data refer to.

  • The theoretical basis of this paper is the modeling of students' conceptions about a specific topic as a qualitative and systemic construct. Following therefrom, a discussion about the role of multivariate analysis for studying the structure of these conceptions and for building explanatory models relating this structure to task, cognitive and instructional variables. An empirical study of students' intuitive conceptions referring to statistical association is used as an example.

  • I have picked out four areas in which computers are changing the teaching and learning of statistics and I have illustrated them with screen dumps from programs that are currently available in the UK. The four areas are: Content, Approach, Emphasis and Understanding.

  • We will present and discuss the outlines of a curriculum for stochastics instruction in the middle grades. Four criteria for a sequence of study are analyzed, and six phases of learning are described.