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A new model for using data mining technology in higher educational systems

机译:在高等教育系统中使用数据挖掘技术的新模型

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摘要

Quality in higher educational systems has been placed squarely on the contemporary agenda. Nowadays, it can be observed that higher educational systems have encountered many challenges which prevent them to achieve their quality objectives. Some of these problems stem from the knowledge gap in higher educational operational and business processes. Knowledge gap is the lack of enough and deep knowledge at educational processes such as planning, evaluation and counseling. The main idea in This work is that the hidden patterns, associations, and anomalies that are discovered by data mining techniques can help bridging this knowledge gap in higher educational systems. We present and justify the capabilities of data mining technology in the context of higher educational system by proposing a model for improving the efficiency and effectiveness of the higher educational process. Higher educational institutes can use this model to identify which part of their processes can be improved by data mining technology and how they can achieve this goal.
机译:高等教育系统的质量已被置于当代议程的正当位置。如今,可以看出,高等教育系统遇到了许多挑战,阻碍了它们实现其质量目标。其中一些问题源于高等教育运营和业务流程中的知识鸿沟。知识鸿沟是指在规划,评估和咨询等教育过程中缺乏足够和深入的知识。本工作的主要思想是,数据挖掘技术发现的隐藏模式,关联和异常现象可以帮助弥合高等教育系统中的这一知识鸿沟。通过提出一种提高高等教育过程的效率和有效性的模型,我们在高等教育系统的背景下提出并证明了数据挖掘技术的功能。高等教育机构可以使用此模型来确定可以通过数据挖掘技术改进其过程的哪些部分,以及它们如何实现此目标。

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