Artificial Intelligence Enhanced Digital Learning for the Sustainability of Education Management System

Q1 Business, Management and Accounting
K.S. Suryanarayana , V.S. Prasad Kandi , G. Pavani , Akuthota Sankar Rao , Sandeep Rout , T. Siva Rama Krishna
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Abstract

Maintenance schedules are scheduled ahead of time and automatically based on the continuous monitoring of the equipment by statistical methods, thanks to artificial intelligence-enabled digital transformation and the best fit model based on Machine Management Index in a pedagogical system. One of the most important aspects of universities is the widespread use of machine learning methods to evaluate students' progress. Machine learning approaches are designed to speed up the learning process without sacrificing accuracy. The dynamics of teaching and learning have shifted since the introduction of modern technological tools. The educational system as a whole has changed and developed over time. These days, people can get an education outside of the classroom as well, thanks to the proliferation of online courses and resources. Everyone's professional life begins with their education. By analyzing past data, artificial intelligence methods can resolve existing problems. When applied properly, artificial intelligence can be a highly efficient method for solving problems with a predictable and repeatable solution space. The learner's personality can be predicted based on a number of factors using machine learning approaches. This article examines how AI may improve digital learning in education management systems to sustain the education ecosystem. AI in education improves student results, learning experiences, and administrative processes. This study discusses AI applications in education management systems and associated problems and opportunities. We also explore ethical issues and the roadmap for using AI to improve education. Educational institutions can provide individualized curriculum for students based on their unique personalities and areas of interest. Institutions of higher learning can benefit greatly from this instrument for personality prediction by recommending a course of study that will better prepare students to enter the field of their choice and achieve professional success.

人工智能增强数字化学习,促进教育管理系统的可持续性
由于在教学系统中采用了人工智能驱动的数字化转型和基于机器管理指数的最合适模型,因此可以根据统计方法对设备的持续监控,提前自动安排维护计划。大学最重要的方面之一是广泛使用机器学习方法来评估学生的进步。机器学习方法旨在加快学习过程,同时不牺牲准确性。自从引入现代技术工具以来,教与学的动态发生了变化。随着时间的推移,整个教育系统也在不断变化和发展。如今,由于在线课程和资源的激增,人们也可以在课堂外接受教育。每个人的职业生涯都是从教育开始的。通过分析过去的数据,人工智能方法可以解决现有的问题。如果应用得当,人工智能可以成为一种高效的解决问题的方法,具有可预测和可重复的解决方案空间。利用机器学习方法,可以根据多种因素预测学习者的个性。本文探讨了人工智能如何改善教育管理系统中的数字化学习,以维持教育生态系统。人工智能在教育领域的应用可提高学生成绩、改善学习体验和管理流程。本研究讨论了人工智能在教育管理系统中的应用以及相关问题和机遇。我们还探讨了伦理问题以及利用人工智能改善教育的路线图。教育机构可以根据学生的独特个性和兴趣领域为他们提供个性化课程。高等院校可以从这一个性预测工具中获益匪浅,为学生推荐更好的学习课程,帮助他们进入自己选择的领域并取得职业成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of High Technology Management Research
Journal of High Technology Management Research Business, Management and Accounting-Strategy and Management
CiteScore
5.80
自引率
0.00%
发文量
9
审稿时长
62 days
期刊介绍: The Journal of High Technology Management Research promotes interdisciplinary research regarding the special problems and opportunities related to the management of emerging technologies. It advances the theoretical base of knowledge available to both academicians and practitioners in studying the management of technological products, services, and companies. The Journal is intended as an outlet for individuals conducting research on high technology management at both a micro and macro level of analysis.
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