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A Method for Improving Paired Collaborative Learning Through Approaches of Computational Intelligence

机译:一种通过计算智能方法改进配对协作学习的方法

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Tn school education there are many kinds of learning styles, and it is known that group learning (collaborative learning) is more effective than individual learning. Tn collaborative learning it is very important how to determine the optimal combination of students in order to improve the learning effect. Tn this paper we propose a method to improve the learning effect of collaborative learning. A neural network model is first applied for predicting learning results of pairs of students in collaborative learning. Then, in order to determine the optimal pairs of students, a genetic algorithm is applied with the prediction results obtained from the neural network. Based on this combination of students, we carried out an experiment of collaborative learning at a college in Japan. Tt was confirmed from the experimental results that the proposed method was effective.
机译:TN学校教育有很多学习风格,众所周知,集团学习(协作学习)比个体学习更有效。合作学习是如何确定学生的最佳组合是非常重要的,以提高学习效果。本文提出了一种提高协作学习学习效果的方法。首先应用神经网络模型,以预测协作学习成对的学习结果。然后,为了确定最佳对学生对,应用了从神经网络获得的预测结果应用遗传算法。基于这些学生的组合,我们在日本的一所学院进行了协作学习的实验。从实验结果中证实了TT,所以提出的方法是有效的。

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