Predictive Analytics in Education

Kurni, Muralidhar; Mohammed, Mujeeb Shaik; Srinivasa, K G

doi:10.1007/978-3-031-32653-0_4

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6 Citations

Abstract

You can make better predictions by analyzing your current data. It is no secret that predictive analytics is changing the educational landscape. Foreseeing future problems or opportunities is made possible through historical data. Understanding the student experience and performance can be improved by using these models. Educators can make targeted improvements by identifying and addressing the most common roadblocks to student success, and existing processes for making strategic decisions can benefit from data-driven evidence and visualizations for stakeholders. Predictive analytics play a key role in driving improvements in efficiency across the institution as a whole. Predictive analytics is the focus of this chapter, which explains how it can improve educational outcomes.

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Predictive Analytics in Mining of Educational Data: A Research Travelogue

Predictive Analytics: Another Vision of the Learning Process

Analysis of Students Performance Using Learning Analytics—A Case Study

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Authors and Affiliations

Department of Computer Science & Engineering, Anantha Lakshmi Institute of Technology & Sciences, Anantapuramu, India
Muralidhar Kurni
Department of Computer Science & Engineering, Malla Reddy Institute of Technology & Science, Hyderabad, India
Mujeeb Shaik Mohammed
IIIT-Naya Raipur, Raipur, Chhattisgarh, India
K G Srinivasa

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Muralidhar Kurni
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Mujeeb Shaik Mohammed
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K G Srinivasa
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Kurni, M., Mohammed, M.S., Srinivasa, K.G. (2023). Predictive Analytics in Education. In: A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning. Springer, Cham. https://doi.org/10.1007/978-3-031-32653-0_4

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DOI: https://doi.org/10.1007/978-3-031-32653-0_4
Published: 29 June 2023
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-32652-3
Online ISBN: 978-3-031-32653-0
eBook Packages: Computer ScienceComputer Science (R0)

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