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首页> 外文期刊>Open Access Library Journal >On Comparative Study for Two Diversified Educational Methodologies Associated with “How to Teach Children Reading Arabic Language?” (Neural Networks’ Approach)
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On Comparative Study for Two Diversified Educational Methodologies Associated with “How to Teach Children Reading Arabic Language?” (Neural Networks’ Approach)

机译:关于与“如何教育阿拉伯语读取儿童的三种多样性教育方法的比较研究(神经网络的方法)

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摘要

This paper considered the increasingly sophisticated role of artificial neural networks (ANNs) after its applications at the interdisciplinary discipline incorporating neuroscience, education, and cognitive sciences. Recently, those applications have resulted in some interesting findings which recognized and adopted by neurological, educational, in addition to linguistic researchers. Accordingly,ANNmodels vary in relation to the nature of assigned brain functioning to be modeled. For example, as human learning that takes place autonomously according to received stimuli that are realistically simulated through self-organization modeling. This paper adopts the conceptual approach of (ANN) models inspired by functioning of highly specialized biological neurons specified in reading brain based on the organization the brain’s structures/substructures. Additionally, in accordance with the prevailing concept of individual intrinsic characterized properties of highly specialized neurons, presented models closely correspond to performance of these neurons for developing reading brain in a significant way. More specifically, introducedANNmodels herein concerned with the importance of reading brain’s cognitive goal in fulfillment of enhanced academic achievement. That’s to translate visualized (orthographic word-from) into a spoken voiced word (phonological word-form). In this context, the presented work illustrates viaANNsimulation and practical obtained results: How ensembles of highly specialized neurons could be dynamically involved in performing the cognitive function of developing reading brain. In more details, this paper presents an interdisciplinary approach adopting a fairly realistic approach of comparative academic performance assessment of two diverse educational methodologies. More specifically, this piece of research aims to improve conventional (classical) academic performance of Teaching How to Read Arabic Language using Methodology via application of a designed Computer Based Learning module. That’s shown to be in well agreement likewise the Artificial Neural Network (ANN), associative memories theories, cognitive multimedia, and classical conditioning. More specifically, coincidence detection learning process has been adopted for evaluation of brain reading performance. Interestingly, presented comparative study originated from the children’s brain response time till reaching learning process convergence that is mapped into academic achievement (outcome mark) values. Accordingly, there response time has been adopted as an appropriate ANN’s candidate parameter for assessment of both educational methodologies. Moreover, analysis of students’ individual differences has been presented after reaching desired output (correct) answer.
机译:本文认为人工神经网络(ANNS)在涉及神经科学,教育和认知科学的跨学科学科的应用后的人工神经网络(ANNS)的越来越复杂的作用。最近,这些申请导致了一些有趣的结果,除了语言研究人员之外,神经系统,教育还能认可和通过。因此,AnnModels涉及与被建模的指定大脑功能的性质有所不同。例如,作为根据接收到的刺激进行自主地进行的人类学习,这些刺激通过自我组织建模现实地模拟。本文采用了(ANN)模型的概念方法,其通过基于组织的大脑结构/子结构的阅读大脑中规定的高度专业生物神经元的运作的概念方法。另外,根据高度专业神经元的个体内在特征性质的普遍概念,所提出的模型与这些神经元以显着的方式发展读数脑的性能密切相关。更具体地说,在此介绍annmodels涉及阅读大脑认知目标在实现增强学业成就方面的重要性。这将将可视化的(正交词 - 来自)转化为口语词(语音字形)。在这种情况下,所提出的工作说明了维纳刺和实际获得的结果:如何动态地参与高度专业的神经元的合奏,以便进行发展读数脑的认知功能。在更多细节中,本文提出了一种跨学科方法,采用了两种不同教育方法的相对学术绩效评估的相当现实的方法。更具体地说,这段研究旨在通过应用于设计基于计算机的学习模块,改善如何使用方法读取现有方法的传统(经典)学术表现。这表明是在人工神经网络(ANN),关联记忆理论,认知多媒体和古典调理的同时。更具体地,已采用重合检测学习过程来评估大脑阅读性能。有趣的是,呈现的比较研究起源于儿童的大脑响应时间,直到达到学习过程融合,映射到学术成就(结果标记)值。因此,已采用响应时间作为适当的ANN候选参数,以评估两种教育方法。此外,在达到所需产出后,已经提出了对学生个人差异的分析(正确)答案。

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