Machine learning (ML) provides a powerful framework for the analysis of high-dimensional datasets by modelling complex relationships, often encountered in modern data with many variables, cases and potentially non-linear effects. The impact of ML methods on research and practical applications in the educational sciences is still limited, but…

There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…

Discusses various aspects of scientific software, including evaluation and selection of commercial software products; program exchanges, catalogs, and other information sources; major data analysis packages; statistics and chemometrics software; and artificial intelligence. (JN)

The computer can be incorporated into educational assessment at two levels: clerical work such as scoring, converting scores, administering test items, and organizing data into manageable profiles; and expanding horizons and deepening the understanding of what is important to measure and how best to measure it through expert systems and new…

The nine articles in this collection were selected because they represent concerns central to computer science, emphasize topics of particular interest to mathematicians, and underscore the wide range of areas deeply and continually affected by computer science. The contents consist of: "Introduction" (S. V. Pollack), "The…