Komputerowe środki aktywizujące w nauczaniu problemowym

Abstract

An active learning system is one that can influence the training data it receives by actions or queries to its environment. Properly selected, these actions can drastically reduce the amount of data and computation required by a machine learner. Active learning has been studied independently by researchers in machine learning, neural networks, computational learning theory, experiment design, information retrieval. Current evidence suggests that some technology applications are more effective than traditional instructional methods in building complex problem solving capabilities for synthesizing information. The effects are achieved in part by permitting alternate methods of "reaching" and motivating learners. Development and implementation of networked distributed interactive simulation in distance education allows dispersed learners to engage in collaborative problem solving activities in real time, is now ready for transfer to schools. Both conceptual and practical problems will sometimes resist solution because problem-solvers are unable to frame their questions in original ways; collective problem solving exercises encourage small groups of students to take a problem.