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IT-education USING INTELLIGENT LEARNING ENVIRONMENTS

ИТ-ОБРАЗОВАНИЕ С ПРИМЕНЕНИЕМ ИНТЕЛЛЕКТУАЛЬНОЙ ОБУЧАЮЩЕЙ СРЕДЫ
Authors: Pavel D. Basalin; Elena A. Kumagina; Elena A. Neumark; Aleksei E. Timofeev; Irina A. Fomina; Natal'ja N. Chernyshova;

IT-education USING INTELLIGENT LEARNING ENVIRONMENTS

Abstract

Предлагается системный подход к решению проблемы структурирования и представления содержания, методологии и дидактики преподавания ИТ-дисциплин в формате продукционно-фреймовой модели знаний интеллектуальной обучающей среды, реализующей интерактивные формы обучения. В качестве основы, определяющей состав и взаимосвязь ИТ-дисциплин, дающих синергетический вклад в формирование профессиональных компетенций, предлагается обобщенное многоуровневое представление архитектуры вычислительной системы. Данное представление включает десять уровней детализации системы, с позиций которых она может рассматриваться конечными пользователями, прикладными программистами, системными программистами или специалистами по ее аппаратной части, включая теоретиков от естественных и точных наук, использующих законы и явления окружающего мира для создания новых базовых принципов организации вычислений. С последними можно связать появление нейрокомпьютеров, эксперименты по созданию квантовых и молекулярных компьютеров. A new systematic approach for structuring of content, methodology and didactics for IT courses is proposed. A mixture of frame-based and production systems is used to represent the knowledge and organize the interactive learning. A general multilevel representation of the computer architecture is considered as a base, which defines structure and interconnection between subjects. The representation consists of ten specification levels of the computer. By means of these levels computer architecture can be studied by end users, applied software programmers, system software programmers or hardware specialists, including natural science theoreticians, which use natural laws, phenomena and effects to create and research new ways of computing. Last one can be mentioned in relation to neurocomputers invention and putting them into practice, experiments with creation of quantum- and biocomputers

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Keywords

интеллектуальная система, продукционно-фреймовая модель, Interactive learning, computational system, вычислительная система (ВС), Electronic computers. Computer science, QA75.5-76.95, многоуровневое представление, Интерактивное обучение, intelligent system, production system, frame-based system, multilevel representation

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    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.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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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!
1
Average
Average
Average
gold