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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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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
- Muralidhar Kurni
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- Mujeeb Shaik Mohammed
Search author on:PubMed Google Scholar
- 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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