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What is Predictive Analytics (PA)

Emergent Practices of Learning Analytics in K-12 Classrooms
The use of statistics and modeling techniques to determine future performance based on current and historical data.
Published in Chapter:
Integrated Model for Asynchronous Learning and Predictive Analytics for Enhanced Learner Experience
Ankit Dhamija (Amity University, Gwalior, India) and Deepika Dhamija (Amity University, Gwalior, India)
Copyright: © 2024 |Pages: 31
DOI: 10.4018/979-8-3693-0066-4.ch003
Abstract
Organizations of every size and industry are embracing data analytics to extract insightful information from the data with the goal of enhancing decision-making, boosting productivity, streamlining workflows, and reducing costs. The adoption of data, more especially learning analytics, which is the act of obtaining, measuring, and analyzing data on learners in order to better understand their requirements and learning preferences, is an excellent possibility for the education industry. Predictive learner analytics can be used to gain a variety of insights that can help institutions improve learner retention, engagement, and performance measurement, particularly in asynchronous online learning where students feel helpless and distracted. In light of this, the chapter suggests a methodology and model for integrating asynchronous learning and predictive analytics.
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