Educational data mining perspectives within university big data environment

Kamelia Stefanova, D. Kabakchieva
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引用次数: 5

Abstract

All organizations are working nowadays in a very dynamic and strongly competitive environment. In order to survive and remain competitive, they need to take timely, adequate and informed decisions that are based not only on intuition and past experience. The main challenges for data analysis are related with the specific characteristics of “big data” and the availability of suitable analytical tools for knowledge extraction that would support the processes of taking strategic management decisions. While “big data” are already widely available and used in business, there are only rare cases of utilizing “big data” in the educational sector. The main purpose of this paper is to focus on the challenges related to the analytical processing of “big data” generated and stored at higher education institutions. The paper discusses the unique opportunities that Big Data analysis could give for the educational sector development and the improvements that could scale from a single school, to governmental directions and satisfaction of the labor market. However, big data analytics confronts universities with great challenges as well, related to finding appropriate methods and tools for extracting knowledge and patterns from extremely rich and complex data sets, and integrating the insights into a coherent vision for strategic management decisions.
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高校大数据环境下的教育数据挖掘视角
如今,所有的组织都在一个充满活力和激烈竞争的环境中工作。为了生存和保持竞争力,他们需要做出及时、充分和明智的决定,而不仅仅是基于直觉和过去的经验。数据分析面临的主要挑战与“大数据”的具体特征有关,以及是否有合适的分析工具来提取知识,以支持采取战略管理决策的过程。虽然“大数据”已经广泛应用于商业领域,但在教育领域使用“大数据”的案例却很少。本文的主要目的是关注与高等教育机构生成和存储的“大数据”的分析处理相关的挑战。本文讨论了大数据分析可以为教育部门发展提供的独特机会,以及可以从单一学校扩展到政府指导和劳动力市场满意度的改进。然而,大数据分析也给大学带来了巨大的挑战,涉及到寻找合适的方法和工具,从极其丰富和复杂的数据集中提取知识和模式,并将这些见解整合到战略管理决策的连贯愿景中。
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