A brief report is presented on the consultancy and the one-week course “Expert systems in education”, given in four training centres (Homs, Alleppo, Lattakia and Damascus) in Syria. This was part of a United Nations Development Programme project SYR/86/12 in the Arab Republic of Syria, called “Introduction of Informatics in Secondary Education”.
After some general comments about computer arithmetic consideration is given to a number of branches of mathematics to see what topics are relevant to courses in computer science and to applications of computers.
The overall conclusion is that the key material might be covered in a minimum of about 40 lectures which could be given either as a dedicated single course, or in two shorter courses or even as a series of carefully co-ordinated “injections” into specialised computer science courses, but if more time is available, so much the better.
Various shortcomings of the current computer science/engineering education are identified and analysed. They are seen as being to a large degree due to various currently prevailing misconceptions concerning aims, scope, methods, impacts, long-term rôle and history of the scientific base underlying computing and information processing in general. An attempt is reported to develop a new compelling view of the underlying science — Informatics1. This science is seen here not as an engineering science that should primarily serve technology but as a fundamental science (with similar scientific aims as physics) that also affords a new very fundamental and broad methodology (with similar impacts as mathematics has). A new view is presented on aims, maturity, and breadth of the current Informatics as fundamental science and on the history of Informatics. In addition, some developments indicating deeper relations between Informatics and physics are discussed as well as some implications for Informatics from views on science developed in mathematics. All that is then used to derive some general and also more specific conclusions concerning aims and methods of the computer science/engineering education, as well as of the education in Informatics within other educational programmes.
The use of advanced computer graphics techniques to help visualize large volumes of multivariate information has become increasingly important. Most of the research in this area has been in the area of scientific visualization, and visualization has become one of the most important tools of modern computational science. It should be noted that computational science has become the third supporting methodology for the physical and biological sciences, alongside the more traditional theoretical and laboratory science areas. It is receiving considerable emphasis from the National Science Foundation in the United States.
This development has raised the issue of providing visualization education for both computer science students and students in the physical and biological sciences. The computer graphics community has started to examine the question of incorporating visualization concepts and techniques into undergraduate and graduate computer science curricula. The author co-chaired, with Steve Cunningham, an Educators' Seminar on “Education for Visualization” at SIGGRAPH '90 and the ACM SIGGRAPH Education Committee has recently formed a subcommitte (currently consisting of the author, Steve Cunningham, and Norman Soong of Villanova University) to address these educational issues. Steve Cunningham has just been elected to the Board of Directors of ACM SIGCSE (Special Interest Group on Computer Science Education) and intends to work to support the development of computational science studies in computer science programs.
There are many issues in visualization education. Students need to be familiar with a wide range of tools, because visualization environments typically include many networked hardware and software tools that support particular aspects of visualization. Equipment in a visualization center typically includes high-performance computing and specialized codes for numerical experiments, specialized rendering machines with accelerated graphics, individual workstations for scientists' viewing, and specialized devices for making video or film images for study and publication. Many commercial visualization tools, such as the Silicon Graphics, Wavefront and Alias software systems, are now available for different computer platforms. In addition, a substantial amount of public domain visualization software is available, such as the set of image tools from the National Center for Supercomputer Applications (NCSA) at the University of Illinois and the Khoros system from the Vision Lab at the University of New Mexico. Finally, some visualization software is developed, especially for special projects.
Some of the educational questions to be considered are as follows:
Should all computer science students learn some visualization concepts?
What computational environment should be offered to visualization students?
It is clear to everyone involved in the field of software engineering that our instruction lags well behind research. Conservative thinkers do not want to leap onto a given bandwagon too early, while even the most progressive thinkers face a profound challenge in incorporating worldwide research into the curriculum.
Based on a discussion of current trends in software engineering, this presentation sketches the emphases that need to be placed in the software engineering curriculum.
This paper argues that good human-computer interaction is an essential part of the design of modern computer systems. Consequently, university computing courses must teach students the skills and knowledge necessary to recognise and design systems which are safe, easy and enjoyable to learn and to use, as well as fulfilling the necessary functional requirements. A number of career profiles has already been identified (Mantei et al., 1991 and Preece, 1991) and these will be used as a basis for discussing the content and needs of the HCI curriculum.
The Portable AI Lab is a joint research project concerned with the design and implementation of an integrated environment to support teaching of Artificial Intelligence at University level. The system is composed of several modules implementing basic. AI techniques in a uniform way. The final section of the paper focuses primarily on the modules dealing with Automated Theorem Proving (ATP) and Natural Language Processing, and shows how relationships between the two might typically be explored within the system.
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