Benefits of Data Analytics in Education sector
Data Analytics is also used for modifying the education system so that students are offered a wholesome learning plan.
Digital learning has become mandatory and crucial in the distance learning process. Smart classroom systems, e-learning, virtual classrooms, online examinations, onscreen marking systems, and other such innovative digital education platforms have been devised which has transformed the traditional education system into an online/digital education system.
What data could be used?
In particular, educators can use data analytics to record and analyze the following data sets:
- Student Data: Demographics like age, ethnicity and gender; whether they are full-time or part-time; if they take classes online, on campus or a mix of the two. In particular, the student data consists of course details, enrollment year, student ID, exam grades and marks obtained in individual subjects. Analyzing this data can be extremely beneficial for nurturing their careers.
- Course Data: Enrollment headcounts, grades and completion rates by program or section.
- Instructor Data: Demographics like age, ethnicity and gender; salary information; productivity levels.
- Facility Data: Classroom utilization and resource allocation, like how many hours a week each room is being used.
1. Customized Programs
Educators can create customized programs for students based on their grades and after understanding their attention span. Also, students can be offered blended learning that includes opportunities for offline and online learning. Through customized programs, students can access the study material online along with lectures.
2. A better Grading System
Data Analytics helps educators to track the performance of students. The analysis helps in understanding the performance of an individual and a collective level. The statistical analysis of individual grades will help educators to understand the areas of interest among students.
The grading system can be enhanced to highlight the key areas where the student has excelled. This system will also allow teachers to give valuable feedback to students and assist them in choosing the right career path.
3. Predicting Success
When determining which students to accept to your institution, looking at certain academic analytics can tell you which candidates are the most likely to succeed and which may be more likely to drop out or fail their classes. This can help you make a judgment call before they even walk onto your campus.
Say a student was accepted to your institution and wants to study engineering. By using data you already have about this student — like their SAT scores, high school GPA and individual class grades — you can assess whether or not they would be likely to succeed in the engineering program. Did they struggle with math? If so, the engineering track might require additional math support for this particular student. In this instance, the student can meet with their advisor to review other options, like exploring a different program or beginning with remedial math courses.
4. Track Enrollment Trends
Your data sets will tell you everything you need to know about students who are applying, enrolling and graduating from your institution, which is essential when it comes to planning and recruiting.
If you can easily see that prospective students from certain cities or towns are applying, being accepted and graduating from your institution, you can better tailor your marketing efforts to students in the same areas. You may also have the flexibility to increase offerings at strategically located satellite campuses.
5. E-learning App Development
Using data analytics and various coding languages, applications that support e-learning can be created. Personalized learning, augmented learning, game-based learning and other such digital learning innovations can be implemented to improvise the interaction between the teacher and the student. Numerous features such as screen sharing, video calling, chatting, data analysis, student information management, virtual assistance, live feedback and offline learning can be developed which can enhance the quality of learning. Applications such as Udemy, Goodreads, Wikipedia, or Quora use the latest technology available to provide innovative e-learning facilities.
6. Enhancing Student Results
The most common methods of analyzing a student’s performance are by their grades obtained in exams, projects and assignments. But all these grades can be accumulated to observe a unique data trail left by the student throughout their lives.
Analyzing these data trails will help educators to understand the behaviour and performance of students. With Data Analytics, it is possible to monitor their actions, such as:
- Response time for exam questions
- Sources they choose to educate themselves
- Questions they skip
- Questions they have answered successfully
The real-time analysis will help in providing students with much more enhanced feedback on their performance. The feedback can significantly improve results. This is because students will be able to understand the areas they have aced and where they lag behind.
7. Reducing The Number of Dropouts
Data Analytics applications in education also include curbing the number of students who drop out of schools and colleges. It can be used for performing predictive analysis for understanding how students might perform in the near future. This analysis will look at the performance of students throughout the year, and predict if they might drop out.
Such an analysis will also help the institute authorities to execute a scenario analysis on a particular course before it is introduced. This will vastly help teachers to guide their students towards the course that will suit them the best.
In addition, Data Analytics is so powerful that it is also being used for analyzing how students will perform after college or university – when they are employed in a firm.
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