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SmartData Collective > Big Data > Data Mining > Challenges of Big Data in Education
Big DataData MiningKnowledge Management

Challenges of Big Data in Education

Sarah Smith
Sarah Smith
5 Min Read
Challenges of Big Data in Education
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How can educators use effectively use big data, and what can be accomplished with it? What are the downsides and challenges of big data, if any?

To start with, what is big data as it applies to education? Big data in education can refer to the use of data to analyze what educational tools do and do not improve learning, which personalized learning approaches work for which types of students, and the most effective settings for testing, to name a few. This information can make it easier for educational administrators to make strong policy decisions and improve the outlook and effectiveness of education.

Many educational institutions are also very concerned with benchmarking their performance in comparison to similar institutions. Schools are in competition with one another for funding, grants, student enrollment, and a wide range of significant resources. Big data can help institutions provide evidence of their success or identify areas for improvement. It can be useful for thesis edit and organize the paper in a way that presents clearly point of view.

There are many challenges of big data, including cost. Not all IT systems are capable of processing, organizing, and presenting large amounts of data in useful ways. Administrators have to determine which software solutions to implement and how much of their budgets can be allocated toward this area. In addition, policymakers must determine whether to make use of a third party company for big data solutions and if yes, are tasked with the challenge of determining which companies can provide valuable information. Many administrators may meet resistance in attempting to use funds for big data, as not everyone may agree with or understand the value.

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In addition, a challenge that goes hand in hand with obtaining and analyzing large amounts of information involves privacy and security. Whether implementing new software internally, outsourcing big data solutions and sending large amounts of information to an external third party or simply obtaining information that was not previously tracked, there are privacy and security concerns inherent in each of those actions. Administrators must ensure they are doing their due diligence to properly safeguard the large amounts of personal information at their disposal.

Another of the several big data research challenges in education is the fact that many of the things educators are interested in learning more about are extremely difficult to measure in a clear, quantifiable way. For example, schools might be interested in knowing how well their students are learning to apply critical thinking skills, or how strongly they relate to and feel connected to the campus culture.

Finally, a significant challenge in big data is that the information provided may point to correlations, but does not provide information about causation. For example, big data may indicate that students who were allowed to regularly have class outside are more creative, and policymakers may look at this information and decide to implement outdoor classes. However, the correlation does not necessarily mean that being outside causes creativity. It could be that the students included in this data set were already more creative than the norm, and perhaps that was why they pushed to study outside in the first place. This is a hypothetical example, but if administrators do not keep in mind that the existence of a relationship does not prove cause, they are at risk of wasting resources to implement solutions that prove ineffective.

In conclusion, big data is a relatively new concept that educators are still in the process of learning to use effectively. It may provide extremely useful information that can help improve education, thus improving retention rates, student engagement and success, and a number of other highly important areas, but it is also important to use big data wisely.

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