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Контекстно-зависимые мобильные обучающие системы

Контекстно-зависимые мобильные обучающие системы

Abstract

Предлагается сценарий обучения и модель открытой архитектуры контекстно-зависимой системы мобильного обучения. Разрабатывается структура системы управления контентом на основе семантического веба. Структура системы управления контентом включает четыре основных элемента: онтологии метаданных, онтологии конкретной предметной области, которая описывает структуру индексации ресурсов, а также модели сценариев обучения и адаптивного выбора учебных ресурсов. При построении системы управления контентом предлагается использовать модель на основе вероятностных автоматов. Контекстно-зависимая система обучения должна уметь персонализировать наилучший стиль обучения. С этой целью предлагается использовать аппарат байесовских сетей и эволюционных вычислений.

The paper proposes a scenario model of learning and the open architecture of context-based mobile learning system. Developed structure of a content management system is based on semantic web. The structure of the content management system contains four main elements: the ontology metadata, ontologies particular domain, which describes the structure of indexing resources, and, finally, models of training scenarios and adaptive selection of learning resources. The model based on probabilistic automata is proposed for building a content management system. Context-sensitive learning system should be able to personalize the best learning style. For this purpose we propose to use the apparatus of Bayesian networks and evolutionary computation.

Keywords

АДАПТИВНОЕ ОБУЧЕНИЕ, КОНТЕКСТНО-ЗАВИСИМАЯ СИСТЕМА, УПРАВЛЕНИЕ КОНТЕНТОМ, ВЕРОЯТНОСТНЫЙ АВТОМАТ, СЦЕНАРИЙ, БАЙЕСОВСКАЯ СЕТЬ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average