Using Machine Learning to Predict Student Performance
Student retention remains one of the greatest concerns for higher education institutions worldwide. Retention rates are used as an indication of how many undergraduate students like B Tech who start their studies at a college will continue their studies at that college.
There are many factors that play a role in early withdrawal from Top Engineering Colleges in Rajasthan. Most of them are related to financial and personal reasons. Universities and colleges also lose students when they decide to study at other schools, or take online courses at other schools or decide to take their second year off.
How technologies improve performances?
Technology in the form of machine learning is being used by B Tech Colleges to improve their student support and retention rates. The value of machine learning for the improvement of retention rates lies in its predictive power. Machine learning algorithms can easily analyze vast data sets and identify students who are at risk of abandoning their studies.
For instance, it is a well-known fact that students who do poorly academically are less likely to graduate. It is also possible that poor grades in a specific class can be a precursor to a student dropping out of that particular class as well as the entire course. On the other hand, Top Engineering Colleges learned that nursing students who did poorly in Introductory Math did not succeed in completing their course. Only 10% of the students who got a C or lower in their math went on to graduate. Of the students who achieved B+ or better, 80% graduated.
If you want more information about the B tech courses and B tech admission then visit the website of Arya College.
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