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Neural network models for teaching multiplication table in primary school.

机译:小学乘法表教学的神经网络模型。

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A novel idea of merging the profound and comprehensive modeling of the most low brain functions with education process is proposed. The main objective of the proposed methodology is to create a computer education system based on low level simulation of the pupil learning process. Comprehensive models of the human memory are possible only for the most fundamental processes of memorizing. Teaching mathematical facts in primary school is one of strict examples. A detailed model of the memory allows creating a computer educational system for teaching the multiplication table. The system stores pupil's answers in a neural associative memory and tunes the neural model to simulate the pupil's behavior. The computer model helps to select the most promising tasks guiding the pupil to learn educational materials in the best way and making the learning process more effective. The first tests in real school teaching process show the potential of the concept and open doors for further study of the approach. Additionally, the results of computer model application to the teaching process can be used as an immense data bank for testing and adjusting known models of the human memory.
机译:提出了将最低脑功能的深刻而全面的建模与教育过程相结合的新思路。所提出的方法的主要目的是创建一个基于学生学习过程的低级模拟的计算机教育系统。人类记忆的综合模型只有在最基本的记忆过程中才有可能。在小学教授数学事实是严格的例子之一。存储器的详细模型允许创建用于教导乘法表的计算机教育系统。该系统将学生的答案存储在神经联想记忆中,并调整神经模型以模拟学生的行为。计算机模型有助于选择最有前途的任务,指导学生以最佳方式学习教材,并使学习过程更有效。实际学校教学过程中的首次测试表明了该概念的潜力,并为进一步研究该方法打开了大门。另外,将计算机模型应用于教学过程的结果可用作庞大的数据库,用于测试和调整人类记忆的已知模型。

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    《》||P.5212-5217|共6页
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    Tatuzov A.L.;

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  • 中图分类 工业技术;
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