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Journals / Turkish Online Journal of Distance Education / 2014 / Cilt: 15 - Sayı: 4

Educational Information Quantization For Improving Content Quality In Learning Management Systems

Alexander Aleksandrovich RYBANOV
Pages
303–321
Publication Date
2014-12-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The process of obtaining quantitative parameter values is focused on use of the phpMorphy morphological analysis library.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The article offers the educational information quantization method for improving content quality in Learning Management Systems.
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Key Findings & Data:The paper considers questions concerning analysis of quality of quantized presentation of educational information, based on quantitative text parameters: average frequencies of parts of speech, used in the text; formal text readability indexes; lexical and syntactic text variety factors.
💡
Conclusion & Impact:The process of obtaining quantitative parameter values is focused on use of the phpMorphy morphological analysis library.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:E-Learning · Distance Learning · Web-Based E-Learning System

Abstract

The article offers the educational information quantization method for improving content quality in Learning Management Systems. The paper considers questions concerning analysis of quality of quantized presentation of educational information, based on quantitative text parameters: average frequencies of parts of speech, used in the text; formal text readability indexes; lexical and syntactic text variety factors. The process of obtaining quantitative parameter values is focused on use of the phpMorphy morphological analysis library.

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Cite This Article

RYBANOV, A. A. (2014). Educational Information Quantization For Improving Content Quality In Learning Management Systems. Turkish Online Journal of Distance Education, Cilt: 15 - Sayı: 4, 303–321. https://ajindex.com/articles/140424

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