📞 +91-7667918914 | ✉️ ijarcce@gmail.com
IJARCCE Logo
International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 13, ISSUE 4, APRIL 2024

Artificial Intelligence Based IT System

Prof. A.J. Saindane, Avdhut Khot, Rushikesh Hegade, Rohan Datar, Shekhar Ghorwade

DOI: 10.17148/IJARCCE.2024.134110
Abstract: In order to improve learning outcomes for IT workers, this study describes the development and assessment of an AI based IT training system. The system makes use of machine learning algorithms to tailor training materials and dynamically modify the learning process according to the unique qualities and performance of each student. Significant gains in participants' information retention and skill learning were found in pilot research that evaluated the system's efficacy. The design and implementation of the AI-based training system, along with the data collecting and analysis of learner performance measures, comprised the methodology of the study. The outcomes show how the system may adaptively customize training sessions to improve learning outcomes. This work makes a valuable contribution to the development of AI-powered educational technology and has the potential to enhance professional IT training approaches. In order to improve learning outcomes for IT workers, this study describes the development and assessment of an AI- based IT training system. The system makes use of machine learning algorithms to tailor training materials and dynamically modify the learning process according to the unique qualities and performance of each student. Significant gains in participants' information retention and skill learning were found in pilot research that evaluated the system's efficacy. The design and implementation of the AI-based training system, along with the data collecting and analysis of learner performance measures, comprised the methodology of the study. The outcomes show how the system may adaptively customize training sessions to improve learning outcomes. This work makes a valuable contribution to the development of AI powered educational technology and has the potential to enhance professional IT training approaches.

Keywords: Adaptive Learning, AI-LMS (Artificial Intelligence – Learning Mechanism System), Personalized Learning, Intelligent Tutoring System, Virtual Assistant

How to Cite:

[1] Prof. A.J. Saindane, Avdhut Khot, Rushikesh Hegade, Rohan Datar, Shekhar Ghorwade, “Artificial Intelligence Based IT System,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2024.134110