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The education sector is an ever-growing sector given that it borrows a lot from other fields and thus it has a combination of ‘old knowledge’ and ‘new knowledge’. However, all this has to go through a sieve before it is given for use in the curriculum. Big data and data science have all been here for a long time, but truth be told, things are now changing. In the previous years, people used to take what is in the books as gospel truth but now with the internet and people creating content on a daily basis. Big data is as simple as it sounds. This is basically extremely large data sets that may be analyzed computationally to reveal trends, associations, and patterns, especially relating to human behavior and interactions. While on the other hand data science is broken down a bit and it is simply big data made easier by being broken down into different disciplines through statistics, scientific methods, and data science tools. However, what implication do these to fields have in the education industry? Let’s have a look.
- Wide database.
Big data is as big as it sounds. It is basically a poll of information depending on various disciplines. However it has not been grouped, neither has been classified by any algorithm. This kind of data gives an extensive database that is most needed for research purposes. However, it contains information that is both useful and others that are not. This means that they need to be filtered before they reach the students, otherwise, it might just spoil their focus. It is both useful and harmful at the same time. PhD students and high caliber can leverage on big data to produce quality manuscripts. At help with dissertation we harness the power of big data when writing literature reviews.
- Specialization
Data science is quite different from big data since data science is a more composed house that has everything figured out and allocated to various disciplines. In light of this, it will be very easy for a student to invest in a certain doctrine and follow it up to the end. This creates specialization and also eases when they are needed to make advancements in their respective fields. Big data, on the other hand, will give the platform for a student to be a jack of all trades and will only specialize by choice.
3.Enhanced student performance
Big data in any field has one major effect that it rubs off on that field and that is enhancing the performance. The logic behind this is that it has a wide variety of information that can be used both for referencing and for making innovations. Big data gives students all the info that they need. This means that as a student, you are in a very good position to analyze disciplines and understand them to the core.
- for analyzing systems and their functionalities
The education field is the backbone of most of the other world systems. In this light, it is only fair to say that education has a really huge role that it plays in the running of all other fields. It is important to realize that all inventions did and discoveries in many fields are all referenced from education. With big data giving unlimited information both in specific fields and fields combined, it will be easy to evaluate and assess systems. This is the kind of scrutiny that not only governments but also economies have been looking for, for their systems.
- Holistic development
Big data is on the spotlight when it comes to holistic development. The science behind this is that since it provides all kinds of information, people are in a very good position to invest in knowledge in a variety of disciplines at a time. It also gives the students no chance to fully depend on the professor or lecturer for all they know. As human nature is, most lectures will push their theories as they see fit and they will really get agitated at a student who asks too many questions. But with this in play they are in no position to limit the knowledge base of students and also this gives room for growth for the students.
- Data errors
However despite all these goodies that accompanies unlimited data, there comes with its errors. These errors can come in the form of unproven doctrines or ideologies. Despite the fact theta, they were presented in good faith; they end up conflicting and messing up the students. However, this is filtered when it comes to data science thanks to the tech-filters that they have. This guarantees us that we can still deliver quality and quantity at the same time.
To this end, I still, hold that the human race should highly invest in knowledge more than anything else that they do. In this retrospect, it is very important that we grow our education field and invest more and more in equipping it, trust me the effect will be felt in all other industries as well.
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