Improving the prediction accuracy in blended learning environment using synthetic minority oversampling technique

GabrijelaDimic; DejanRancic; NemanjaMacek; PetarSpalevic; VidaDrasute

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Improving the prediction accuracy in blended learning environment using synthetic minority oversampling technique

机译：用合成少数群体过采样技术提高混合学习环境中的预测精度

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PurposeThis paper aims to deal with the previously unknown prediction accuracy of students activity pattern in a blended learning environment.Design/methodology/approachTo extract the most relevant activity feature subset, different feature-selection methods were applied. For different cardinality subsets, classification models were used in the comparison.FindingsExperimental evaluation oppose the hypothesis that feature vector dimensionality reduction leads to prediction accuracy increasing.Research limitations/implicationsImproving prediction accuracy in a described learning environment was based on applying synthetic minority oversampling technique, which had affected results on correlation-based feature-selection method.Originality/valueThe major contribution of the research is the proposed methodology for selecting the optimal low-cardinal subset of students activities and significant prediction accuracy improvement in a blended learning environment.

机译：目的涉及在混合学习环境中处理学生活动模式的先前未知的预测准确性.Design/methodology/approachto提取最多相关的活动功能子集，应用了不同的特征选择方法。对于不同的基数子集，在比较中使用分类模型.FindingSexperation评估反对特征载体维度降低导致预测精度的假设增加。研究限制/含义在所描述的学习环境中的预测精度是基于应用合成少数群体过采样技术的预测准确性影响了基于相关的特征选择方法的结果。研究的主要贡献是该研究的主要贡献是选择学生活动的最佳低次数子集的方法论和混合学习环境中的显着预测准确性改进。

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《Interlending & document supply》 |2019年第2期|76-83|共8页
作者
GabrijelaDimic; DejanRancic; NemanjaMacek; PetarSpalevic; VidaDrasute;
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正文语种 eng
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Machine learning; Educational data mining; Naïve Bayes classifier; Learning management system; Feature selection; Oversampling technique;

机译：机器学习;教育数据挖掘;天真贝叶斯分类器;学习管理系统;特征选择;过采样技术;

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1. Improving the prediction accuracy in blended learning environment using synthetic minority oversampling technique [J] . GabrijelaDimic, DejanRancic, NemanjaMacek, Interlending & document supply . 2019,第2期

机译：使用合成少数过采样技术提高混合学习环境中的预测精度
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Improving the prediction accuracy in blended learning environment using synthetic minority oversampling technique

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