Jean-Paul Doignon - Böcker

Sometime in the late sixties, one of the editors of this volume realized that the mathematica psychologists in Europe-an odd lot mostly concentrated in Germany, the Netherlands, France, England and Belgium-were suffering from an acute sense of isolation. The papers that they presented at meetings of their national or regional societies had to be 'sanitized' to the point of misrepresentation. They were misunderstood. The mood was grim, depression was lurking. He decided that urgent action was required: a European gathering of mathematical psychologists was called in April 1971. Not being foolhardy, however, he took the precaution of choosing Paris as the meeting place. Around thirty mathematical psychologists received an invitation. They all came, justifying at least Paris's reputation. The meeting took place at the 'Maison des Belges' of the Cite Universitaire, Boulevard Jourdan, in front of the Parc Montsouris. As far as everyone remembers, the meeting was a full success. A happy birth had taken place. This editor then irresponsibly accepted a position in a university in the US, leaving an infant to the whims of the passers-by. Fortunately, a godfather came along. The next meeting took place in Nijmegen, in November 1971, under the loving care of Eddy Roskam. A tradition was established. The third meeting was in Oxford (1972); then in Marseilles (1973), Regensburg (1974), Stirling (1975), Stockholm (1976) . . . The infant became a toddler, then a vigorous child. This annual meeting is now an important event in the field.

Knowledge spaces offer a rigorous mathematical foundation for various practical systems of knowledge assessment. An example is offered by the ALEKS system (Assessment and LEarning in Knowledge Spaces), a software for the assessment of mathematical knowledge. From a mathematical standpoint, knowledge spaces generalize partially ordered sets. They are investigated both from a combinatorial and a stochastic viewpoint. The results are applied to real and simulated data. The book gives a systematic presentation of research and extends the results to new situations. It is of interest to mathematically oriented readers in education, computer science and combinatorics at research and graduate levels. The text contains numerous examples and exercises and an extensive bibliography.

Learning spaces offer a rigorous mathematical foundation for practical systems of educational technology. Learning spaces generalize partially ordered sets and are special cases of knowledge spaces. The various structures are investigated from the standpoints of combinatorial properties and stochastic processes. Leaning spaces have become the essential structures to be used in assessing students' competence of various topics. A practical example is offered by ALEKS, a Web-based, artificially intelligent assessment and learning system in mathematics and other scholarly fields. At the heart of ALEKS is an artificial intelligence engine that assesses each student individually and continously.The book is of interest to mathematically oriented readers in education, computer science, engineering, and combinatorics at research and graduate levels. Numerous examples and exercises are included, together with an extensive bibliography.