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  Published Paper Details:

  Paper Title

LEARNING STYLE FORECASTING SYSTEM WITH FUZZY LOGIC

  Authors

  HARTHESH M,  Mrs.V. BAKYALAKSHMI

  Keywords

LEARNING STYLE FORECASTING SYSTEM WITH FUZZY LOGIC

  Abstract


By recommending suitable e-contents from e-learning servers based on an analysis of the learners' preferred learning modes, the quality of e-learners can be raised.. Because psychological balance is variable in nature, and e-learners differ based on their learning patterns, environment, time, and mood, the learning styles had to be carefully predicted. Furthermore, the knowledge about the learners used for learning style prediction is inherently uncertain. This research suggests using survey guidelines to manage the uncertainty in learning style predictions and finds the Felder-Silverman learning style model as a good model for learning style prediction, particularly in web contexts. Fuzzy logic using a Gaussian membership function has been tried in evaluations with students learning the C programming language, and it has been found that the proposed model greatly increased prediction accuracy.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2303972

  Paper ID - 233695

  Page Number(s) - i189-i202

  Pubished in - Volume 11 | Issue 3 | March 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  HARTHESH M,  Mrs.V. BAKYALAKSHMI,   "LEARNING STYLE FORECASTING SYSTEM WITH FUZZY LOGIC", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 3, pp.i189-i202, March 2023, Available at :http://www.ijcrt.org/papers/IJCRT2303972.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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