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Expanding Educational Horizon to Accommodate All Individuals through Lens of Deep Data Analytics (Work in progress)

机译:通过深度数据分析的镜头扩展教育视野,以容纳所有个人(正在进行中)

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We have abundance of schools, colleges and universities around the world. Such institutions are backbone of any developed society and are core to growth and civilization. We provide almost every kind of educational areas in science and arts, broadly speaking. Basic schooling is everybody's right in any society regardless of their poverty or skill level. However, statistics show that not every individual will go through same level of education as of others. In addition to this, some of individuals don't get to area of education; their inner talent is made for. For example, it is not uncommon for a very technical person (by birth) ends up in non-technical education path and real world jobs. Such scenarios and examples are everywhere. This results in an inefficient distribution of education and skills to right individuals. To solve this problem, I pursue researching big and unstructured data from all sources that is related to education, career and talent. In such exploration, I also focus on social networking data and mine it to analyze hidden personality features that can contribute to understand different personalities. In this research, I explore various data and analysis techniques to implement algorithms and models through lens of cognitive computing and artificial intelligence. I aim to use a very huge data set, so machine learning and training data techniques can be implemented to correlate features. I believe such analysis and mining of data, identify new educational areas, curriculum and sectors, that we must introduce to ours schools and colleges, in order to provide very customized education to a very special individuals that normally don't fit in standard educational system and fail to retain normal journey. This research is in conjunction (and part of, result of) with our other research work/initiatives in data mining, personality prediction, educational data mining and artificial intelligence, which we are pursuing and sharing with community in journals and conference at present.
机译:我们在世界各地都有大量的学校,学院和大学。这些机构是任何发达社会的骨干,是增长和文明的核心。从广义上讲,我们提供几乎所有类型的科学和艺术教育领域。基础教育是任何社会中每个人的权利,无论他们的贫穷或技能水平如何。但是,统计数据表明,并非每个人都会接受与其他人相同的教育水平。除此之外,有些人还没有进入教育领域。他们的内在天赋是为。例如,技术水平很高的人(出生时)最终从事非技术教育和从事现实世界的工作并不少见。这样的场景和示例无处不在。这导致教育和技能无法正确地分配给正确的个人。为了解决这个问题,我寻求从与教育,职业和才能有关的所有来源研究大的非结构化数据。在这种探索中,我还将重点放在社交网络数据上并将其挖掘出来,以分析可能有助于理解不同个性的隐藏个性特征。在这项研究中,我探索了各种数据和分析技术,以通过认知计算和人工智能的视角来实现算法和模型。我的目标是使用非常庞大的数据集,因此可以实施机器学习和训练数据技术来关联功能。我相信对数据的这种分析和挖掘,确定了我们必须引入我们学校和学院的新的教育领域,课程和领域,以便为通常不符合标准教育系统的非常特殊的个人提供非常个性化的教育并且无法保持正常的旅程。这项研究是与我们在数据挖掘,性格预测,教育数据挖掘和人工智能方面的其他研究工作/倡议(部分或结果)结合在一起的,我们目前正在期刊和会议中与社区进行追求和共享。

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