Data Science in Education – A much-awaited revolution
Today, we are going to learn about the various applications of Data Science in Education. But, before that first understand the concept of Data Science and its use in today’s world.
Data Science is a field that involves a number of methods and techniques to collect data from different sources, then process it in such a way that we can extract some meaningful insights from it to solve real-world problems.
Data Science is a multidisciplinary field that requires the skills of math, computer science, statistics, etc. The use of Data Science has grown rapidly in the past few years in almost every field, including Education.
In this article, we will walk through the different areas of the Education sector in which Data Science can be applied efficiently.
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Data Science in Education
The availability of a large amount of educational data has generated a number of opportunities for Data Scientists to discover some innovative applications of Data Science in Education. Also, the analysis of Big Data may help the education sector in solving their problems by understanding the different types of students.
Schools, colleges, and universities have an enormous amount of student data such as academic records, results, grades, personal interests, cultural interests, etc. to handle. The analysis of this data can help them in finding advanced methods for enhancing student learning.
Modern Data Science tools can do a big favor for the education sector.
Various Machine Learning algorithms such as Random forest, logistic regression, decision trees, support vector machines, etc. are used for this purpose. However, there are not many applications of Data Science in Education yet.
But, there are still many unexplored use cases of Data Science that might result in the success of the Education field.
Here is a list of some of the advantages of Data Science in Education.
Use Cases of Data Science in Education
Every student is unique in his own way and has a different way of learning things. Thus, it becomes quite a difficult task for educational organizations to select the methods to adapt in the classroom that will be best for all the students.
Adaptive learning is that the delivery of personalized learning experiences that address the unique needs of people through customized content, real-time feedback, and resources. It seeks to supply a singular yet personalized experience for every user.
Now, Big Data and Data Science can help teachers to employ adaptive learning techniques. Big data can help teachers to discover the abilities of the students and use optimal teaching techniques according to them.
2. Better Parent Involvement
The teachers can use a large amount of student data and apply various analytic methods for evaluating the performance of students. This helps to inform their parents about the issues that might affect their child’s performance in different areas such as academics, sports, etc. This information can help the parents to keep an eye on their child’s activities.
Having parents and teachers communicate more helps students feel more motivated in their classes; their self-esteem and attitudes in class improve The analysis not only helps the parents but also the institutions to take different initiatives for improving the educational system for enhancing the student learning experience.
3. Better Assessment of Teachers
Data Science in Education makes it easy for administrators to keep an eye on the activities and teaching methods of the teachers. This helps them in identifying the most effective teaching methodologies.
The data can be analyzed in different ways to draw some meaningful insights that show the strong and weak areas of the teachers. This helps them improve accordingly.
The analysis can be performed on the data collected from the student attendance records, results, feedback, etc.
Data Science in Education helps you to have central control over the complete student data for evaluating the performance of the students and take suitable actions.
This analysis will help you to make the changes that will benefit the students and will help them in all possible ways to solve their problems.
If the performance of a student is becoming poor day by day then, Big data and Data Science in Education can help teachers to identify the reason behind that and help him overcome his problems.
Data Science in Education can help educational institutions to improve the performance of the students.
By analyzing where they are lacking in their efforts and where they need to improve for producing better results of their students.
5. Better Organization
From the organizational perspective, the various Data Science techniques can help the Schools, Colleges, and Universities to better plan and organize their actions.
Being better organized will also help them to take some important decisions concerning business operations.
The different Data Science tools can help educational organizations to reshape their strategies.
6. Regular Updates in the Curriculum
Education is a very vast field and is only evolving with time. The main aim of the various educational institutions is to prepare their students to face the challenges of this competitive era. For this purpose, they need to keep themselves updated with the requirements of the market to design a better and efficient curriculum for their students.
Thus, Educational organizations are moving towards Data Science for gaining insights from the data and for predicting future market trends and demand to provide the necessary knowledge to the students.
The Educational Institutes can use the student data for discovering the educational programs that are best suited for the students for attracting a large number of students to their institute.
Data Scientists can help the institutions to understand the student requirements and provide the best possible facilities.
Data Science in Education Case Studies
A major role is played by Data Science in Education in the success of the classrooms worldwide.
For example, the University of Florida has successfully adapted the Data Science principles for gaining meaningful insights. They gain insights from the student data and utilizing it for monitoring and predicting the performance of their students. It has resulted in the rise of the performance of their students.
Another example is the University of Nevada which is also collecting and analyzing student data to identify trends and patterns for providing customized student experience.
Some other examples are:
1. Data Science Case Study – Georgia State University
Georgia State University (GSU) in the United States, has used various Data Science and Machine Learning tools for mining insights from the student data. This helps them to track the courses in which the performance of the students was not up to the mark. It leads to developing a backup program to deal with the cause behind this to improve student performance.
Taking the right decisions based on their analysis helped them in a remarkable way and they realized that their graduation rate has grown from 32% to 54% between the years 2003 and 2014. They also utilized the student data for dealing with the issues of student retention and course completion.
2. Data Science Case Study – Arizona State University
Another case is Arizona State University (ASU) which is considered to be one of the top American universities. The mathematics department of ASU has developed a system called “Adaptive Learning” based on the analysis of student data. So that they can take suitable actions for the improvement of student performance.
The developed system collected various data related to students such as their marks, strengths, weaknesses, cultural areas of interest as well as the scenarios in which they hesitate.
The Advisor of ASU combined the information extracted by the system with the registration details and other previous records of the student. This will help them in such a way that they will get a notification whenever the performance of the student starts going off track so that desired actions can be taken before any major harm.
After the implementation of this system, there was a considerable improvement in the success rate of the students and also the dropout rate of students got decreased by around 5.4%.
This Data Science in Education article helps us to understand that like many other sectors, Data Science is also helping the Education sector in achieving new heights.
The various advanced Data Science tools will help institutions to improve the learning outcomes, monitor the student as well as the teacher performance, etc. We have also seen how certain universities have applied Data Science in Education so that they can solve their problems for improving their success rate.