AI-Driven Big Data Platforms for Personalized Learning Analytics in Education
Abstract
Advances in Artificial Intelligence (AI) and Big Data Computing have transformed learning analytics, shifting focus from individual-traditional Learner-Analytical techniques toward personalized learning analytics based on advanced machine-learning. AI tools automatically generate rich personal influence models for each learner, enhancing education and experiencing personalized predictive guidance and dynamic learning. The paradigm can serve all education fields. An AI-driven personalized learning analytics platform for higher-education is detailed, generating learning activity characteristics data in a Big Data learning environment. Features affecting progression and performance are constructed using Applied Bayesian Learning with sufficient training volume, deployed within a mobile social network learning software to evaluate adaptive resources, progression pathways, and support systems. Results imply effective personalized learning guidance can be achieved. Recent years have also increased personalization demand in primary and secondary education, prompting these analytics adapted for a K-12 environment.
Although the big data of education generates factors capable of acting at the macro-level of learning, it is the individual that experiences and benefits from the relevant lattice augmented by the real-time modeling and prediction of personal learning traits, capacities, and behavioral impact on progression, performance, and experience quality. If personalized learning-analytic platforms are constructed and positioned properly, they could guide students’ progress and also provide feedback on resourceworth and system-support reliability. There are multiples current attempts to construct and validate such platforms, mainly in higher education, but also in K-12, where the adaption of Persuasive Technology Natural Network principle leads to personalized pedagogical support by Lawren and Jian.The operation of the proposed platform-not yet positioned on the mobile social network for the K-12 area-and the first experimental results, indicating a successfully established individual-adaptive influence model, are elaborated.
Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 7 No. 6 (2024): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
13166-13179 |
Published |
December 11, 2024 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Vikram Boga (%2024). AI-Driven Big Data Platforms for Personalized Learning Analytics in Education. International Journal of Science, Research and Technology , Vol. 7 No. 6 (2024): International Journal of Science, Research and Technology (IJSRAT) , pp. 13166-13179. https://doi.org/10.15662/IJSRAT.2024.0706005 |
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