Enhancing Educational Systems with Machine Learning: Personalized Learning, Predictive Analytics, and Intelligent Resource Management

Antony Ronald Reagan Panguraj

doi:10.5281/zenodo.14673274

Enhancing Educational Systems with Machine Learning: Personalized Learning, Predictive Analytics, and Intelligent Resource Management

Author(s)	Antony Ronald Reagan Panguraj
Country	United States
Abstract	The growing themes in the area of ML consist in using potentially transforming educational systems, where people will receive more targeted training, and the use of predictive analytics to help prepare students for success and manage resources. Personalized learning is one of the key ideas discussed in the modern approach to education, which is based on the use of ML methods to bring the learning task and the materials, learning methods adapted to the performance of the student in order to increase the interest and, consequently, efficiency. MA, specifically predictive analytics, can help education stakeholders forecast the learners’ performance, spot struggling students on time, and adjust the necessary students’ support, resulting in higher retention and graduation rates. Furthermore, through the intelligent operation of resources, it helps educational institutions achieve a more reasonable distribution of resources in terms of classrooms, teachers, and curriculum planning, to improve efficiency in the operation of educational resources. However, there are many issues that are still discussed and remain the obstacles to apply ML in education, including data privacy, algorithmic bias, and the integration of these technologies into already existing learning systems. Solving such problems entails the need to set data standard, algorithm balances, carry out professional development for the teachers. Implementing a proper machine learning concept can improve learning in many ways through infrastructure and training and should always be equitable for all students.
Keywords	Machine Learning, Personalized Learning, Predictive Analytics, Resource Management, Data Privacy, Algorithmic Bias
Field	Engineering
Published In	Volume 2, Issue 10, October 2021
Published On	2021-10-06
Cite This	Enhancing Educational Systems with Machine Learning: Personalized Learning, Predictive Analytics, and Intelligent Resource Management - Antony Ronald Reagan Panguraj - IJLRP Volume 2, Issue 10, October 2021. DOI 10.5281/zenodo.14673274
DOI	https://doi.org/10.5281/zenodo.14673274
Short DOI	https://doi.org/g8z64z

View / Download PDF File

doi

CrossRef DOI is assigned to each research paper published in our journal.

IJLRP DOI prefix is
10.70528/IJLRP

Downloads

Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 5 Isu 12 Cover Page Vol 5 Isu 11 Cover Page Vol 5 Isu 10

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA

About IJLRP Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijlrp.com

International Journal of Leading Research Publication

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Enhancing Educational Systems with Machine Learning: Personalized Learning, Predictive Analytics, and Intelligent Resource Management

Share this