Education and Computing最新文献

After sketching the basic concepts of informatics, a schedule is presented that allows the teaching of these concepts using current technology. Throughout the course, the usage of formalized notations for the specification and the solution of problems is emphasized. The work in the computer labs includes applications of standard software as well as problem solving using HyperCard and Object-Pascal. Even with inexperienced students, object-oriented programming has proved to be a perfect means for design and implementation.

The Norwegian educational system has been through a systematic, experimental period with computers in schools and vocational training. Teacher training has been an additional activity in this field, particularly with in-service training. Several R&D projects have related higher education to practical school work at lower levels. This lays a platform for revision of pre-service and post graduate teacher training, indicating also a need for higher degree studies directed towards new educational methods and contents, as a natural consequence of new information technology. Some of these thoughts are now being put into action by the Norwegians.

The Joint Curriculum Task Force of the acm and the ieee Computer Society has proposed a new flexible collection of curricula which provides the basis for broad-based undergraduate computing programs. In order to have the curricula applicable to as many types of undergraduate institutions as possible, the curricula have been designed around a collection of “knowledge units” which can be put together in a variety of ways to form a coherent set of courses leading to a major in computing. In order to help provide connections between these knowledge units, the task force has also identified a number of “recurring concepts” which tie together seemingly disparate parts of the curriculum. The purpose of this article is to provide an informal discussion of the considerations that went into the creation of these curricular guidelines, and provide insight into the reasons behind many of the decisions that were made.

The use of computer simulations in education and training can have substantial advantages over other approaches. In comparison with alternatives such as textbooks, lectures, and tutorial courseware, a simulation-based approach offers the opportunity to learn in a relatively realistic problem-solving context, to practise task performance without stress, to systematically explore both realistic and hypothetical situations, to change the time-scale of events, and to interact with simplified versions of the process or system being simulated.

However, learners are often unable to cope with the freedom offered by, and the complexity of, a simulation. As a result many of them resort to an unsystematic, unproductive mode of exploration. There is evidence that simulation-based learning can be improved if the learner is supported while working with the simulation. Constructing such an instructional environment around simulations seems to run counter to the freedom the learner is allowed to in ‘stand alone’ simulations. The present article explores instructional measures that allow for an optimal freedom for the learner.

An extensive discussion of learning goals brings two main types of learning goals to the fore: conceptual knowledge and operational knowledge. A third type of learning goal refers to the knowledge acquisition (exploratory learning) process.

Cognitive theory has implications for the design of instructional environments around simulations. Most of these implications are quite general, but they can also be related to the three types of learning goals. For conceptual knowledge the sequence and choice of models and problems is important, as is providing the learner with explanations and minimization of error. For operational knowledge cognitive theory recommends learning to take place in a problem solving context, the explicit tracing of the behaviour of the learner, providing immediate feedback and minimization of working memory load. For knowledge acquisition goals, it is recommended that the tutor takes the role of a model and coach, and that learning takes place together with a companion.

A second source of inspiration for designing instructional environments can be found in Instructional Design Theories. Reviewing these shows that interacting with a simulation can be a part of a more comprehensive instructional strategy, in which for example also prerequisite knowledge is taught. Moreover, information present in a simulation can also be represented in a more structural or static way and these two forms of presentation provoked to perform specific learning processes and learner activities by tutor controlled variations in the simulation, and by tutor initiated prodding techniques. And finally, instructional design theories showed that complex models and procedures can be taught by starting with central and simple elements of these models and procedures and subsequently presenting more complex models and proced