Utilization of Machine Learning for Students in Education Sector
Author(s):
Chiranjeevi Kommula, Dr. Balusupati Veera Venkata Siva Prasad
Keywords:
Educational Data Mining, artificial intelligence; machine learning; data analysis, Learning analytics, etc.
Abstract
The events of 2020 have taught us that culture is already fragile, and that it is vulnerable to events that shift the paradigms that rule it quickly. A pandemic like Coronavirus disease 2019 has shown this; this global emergency has transformed the way citizens connect, chat, learn, and function. The need to extract useful information from data becomes more pressing. In data mining and data analytics, methods and approaches that were once mostly seen in academic labs are now being adopted by forward-thinking businesses to produce market insight and improve decision-making. It's not easy to separate reality from fiction and recognize study opportunities and realistic implementations as analytics and data mining projects in education become more common. Learning analytics (LA) as a field stays in its earliest stages. Large numbers of the strategies now unmistakable from professionals have been drawn from different fields, including HCI, computer science, statistics, and learning sciences. Machine learning and data analytics are proposed methods that can help remove data and discover important examples inside the gathered data. In this work, the field of e-learning is researched regarding definitions and attributes. This Article dissects the Utilization of Machine Learning for Students in Education Sector.
Article Details
Unique Paper ID: 152110

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 1344 - 1347
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