REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS
Using of information technologies and e-learning systems increases opportunities of teachers and learners in reaching their studying process goals. It takes into account the individual characteristics of each and provides opportunities for e-learning. But e-learning systems using is limited despite...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Belarusian National Technical University
2016-07-01
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| Series: | Sistemnyj Analiz i Prikladnaâ Informatika |
| Subjects: | |
| Online Access: | https://sapi.bntu.by/jour/article/view/109 |
| _version_ | 1797873750475014144 |
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| author | Y. B. Popova A. I. Burakovski |
| author_facet | Y. B. Popova A. I. Burakovski |
| author_sort | Y. B. Popova |
| collection | DOAJ |
| description | Using of information technologies and e-learning systems increases opportunities of teachers and learners in reaching their studying process goals. It takes into account the individual characteristics of each and provides opportunities for e-learning. But e-learning systems using is limited despite of many researchers and the obvious advantages of such systems. One of the main reasons of such limitation is the usage of precise quantitative techniques in a hard-structured and fuzzy area as a learning process. In designing of information learning systems developers are faced with the problem of modeling knowledge which can be divided into two categories conventionally: personal and subject. Subject knowledge is defined education program and represents expert knowledge (the teacher) about the composition and structure of the subject. Personal knowledge can determine the level of the material studied by learner. This kind of knowledge is dynamic, changing in the educational process and designed to adapt e-learning systems to the particular learner. There are a large number of knowledge representation models. Commonly used models are logical, productional, network, frame-based and mathematical models. The main advantage of the mathematical model is the accuracy, abstraction processing, communication logically uniform way. Mathematical model of knowledge representation based on the theory of fuzzy sets take into consideration the semantic ambiguity expert assessment (teacher) degree of preparation to learner. |
| first_indexed | 2024-04-10T01:21:10Z |
| format | Article |
| id | doaj.art-dce392fc10134f098059ca9ec08965b7 |
| institution | Directory Open Access Journal |
| issn | 2309-4923 2414-0481 |
| language | English |
| last_indexed | 2024-04-10T01:21:10Z |
| publishDate | 2016-07-01 |
| publisher | Belarusian National Technical University |
| record_format | Article |
| series | Sistemnyj Analiz i Prikladnaâ Informatika |
| spelling | doaj.art-dce392fc10134f098059ca9ec08965b72023-03-13T09:47:40ZengBelarusian National Technical UniversitySistemnyj Analiz i Prikladnaâ Informatika2309-49232414-04812016-07-0102586593REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETSY. B. Popova0A. I. Burakovski1Белорусский национальный технический университет, г. МинскБелорусский национальный технический университет, г. МинскUsing of information technologies and e-learning systems increases opportunities of teachers and learners in reaching their studying process goals. It takes into account the individual characteristics of each and provides opportunities for e-learning. But e-learning systems using is limited despite of many researchers and the obvious advantages of such systems. One of the main reasons of such limitation is the usage of precise quantitative techniques in a hard-structured and fuzzy area as a learning process. In designing of information learning systems developers are faced with the problem of modeling knowledge which can be divided into two categories conventionally: personal and subject. Subject knowledge is defined education program and represents expert knowledge (the teacher) about the composition and structure of the subject. Personal knowledge can determine the level of the material studied by learner. This kind of knowledge is dynamic, changing in the educational process and designed to adapt e-learning systems to the particular learner. There are a large number of knowledge representation models. Commonly used models are logical, productional, network, frame-based and mathematical models. The main advantage of the mathematical model is the accuracy, abstraction processing, communication logically uniform way. Mathematical model of knowledge representation based on the theory of fuzzy sets take into consideration the semantic ambiguity expert assessment (teacher) degree of preparation to learner.https://sapi.bntu.by/jour/article/view/109знанияинформационные обучающие системыматематическая модельнечеткие множества |
| spellingShingle | Y. B. Popova A. I. Burakovski REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS Sistemnyj Analiz i Prikladnaâ Informatika знания информационные обучающие системы математическая модель нечеткие множества |
| title | REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS |
| title_full | REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS |
| title_fullStr | REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS |
| title_full_unstemmed | REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS |
| title_short | REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS |
| title_sort | representation of knowledge in learning systems based on the theory of fuzzy sets |
| topic | знания информационные обучающие системы математическая модель нечеткие множества |
| url | https://sapi.bntu.by/jour/article/view/109 |
| work_keys_str_mv | AT ybpopova representationofknowledgeinlearningsystemsbasedonthetheoryoffuzzysets AT aiburakovski representationofknowledgeinlearningsystemsbasedonthetheoryoffuzzysets |