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An Analysis of Big Data in Educational Sector

By: Contributor(s): Material type: TextPublication details: Nawabshah: QUEST, 2015.Description: 54pOnline resources:
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Thesis and Dissertation Research Section Available MP/8-82
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ABSTRACT

Big Data refers to the data that is often so large in volume, moving at an unforeseen velocity, and having very high variation in structure and quite veracious in nature that conventional methods fail to fully explore and exploit its potential for intelligent decision making. Three characteristics define big data volume, velocity, and variety. These characteristics are also called as 3 V's of big data. It is often said that big data is going to be a big game changer in the way we will perform actions in the future, gain insight from the data, and to make future decisions intelligently.


Educational institutes can have immense power at their disposal as the amount of data being collected through the introduction of interactive learning systems in combination with a variety of other software applications have been used to improve learning of the students. With such increased access to technology and connectivity, we need to find efficient approaches to get value and insight from the data.


In order to improve decision-making, accelerate learning, optimize productivity, and maximize usage of learning systems, educational institutes and governmental and non-governmental agencies working in the education sector need to manage the big data generated by a learning system. Therefore, it is essential to suggest a comprehensive solution to solve complex problems with undefined structures that can support better decision-making from these massive amounts of data.


In this thesis we have designed and developed an online interactive learning system.

The system is essentially stable, scalable, and manageable for educational institutes.
and governmental and non-governmental agencies that intend to use learning systems for improving quality and effectiveness of educational material for the students. After that, we have used Apache Storm for analyzing the data generated by the users of the learning system. Moreover, we have carried out an experimental study in which the users have evaluated the quality of the system and its impact on their learning. The results show that our system has a significant impact on the learning of the users \J ho participated in this research work.

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