Smartskill Mentor: Integrating AI for Personalised Student Skill Development

In the modern-day education device, there's a substantial hole among educational understanding and realistic capabilities required in professions. Smart Skill Mentor addresses this problem through assessing college students' academic performance, persona, and pastimes, and creating personalized ability improvement pathways. Using system getting to know algorithms, the platform analyzes scholar facts, predicts applicable talents, and adapts them to industry desires. It additionally consists of realglobal troubles solved by means of industry professionals to enhance realistic mastering. Data mining performs a key position within the training area, analyzing huge statistics sets to perceive insights that support higher decision-making. Techniques inclusive of the Random Forest (RF) set of rules assist teachers make informed choices that enhance instructional effects by way of figuring out patterns in pupil information consisting of grades, attendance, and remarks. Data mining additionally permits the advent of character learning plans, making sure that scholars get hold of personalized aid based totally on their specific strengths and weaknesses. By combining information-driven insights with personalized studying and actual-international packages, Smart Skill Mentor helps instructional institutions bridge the gap between idea and practice. This approach will increase student engagement, helps skill improvement, and improves common educational overall performance, thereby better making ready students for enterprise challenges. The end result is a extra dynamic, impactful, and enterprise-targeted getting to know revel in.

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Publication Details

Published
2025-04-17
DOI
https://doi.org/10.1109/icdsbs63635.2025.11031770
Primary Topic
Engineering Education and Technology
Type
article
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article

Smartskill Mentor: Integrating AI for Personalised Student Skill Development

Pauline Mary, A. Panasa Reddy, Anala Shanmukha Bhanumohan
Engineering Education and Technology
article

Smartskill Mentor: Integrating AI for Personalised Student Skill Development

Pauline Mary, A. Panasa Reddy, Anala Shanmukha Bhanumohan
article en

Abstract

In the modern-day education device, there's a substantial hole among educational understanding and realistic capabilities required in professions. Smart Skill Mentor addresses this problem through assessing college students' academic performance, persona, and pastimes, and creating personalized ability improvement pathways. Using system getting to know algorithms, the platform analyzes scholar facts, predicts applicable talents, and adapts them to industry desires. It additionally consists of realglobal troubles solved by means of industry professionals to enhance realistic mastering. Data mining performs a key position within the training area, analyzing huge statistics sets to perceive insights that support higher decision-making. Techniques inclusive of the Random Forest (RF) set of rules assist teachers make informed choices that enhance instructional effects by way of figuring out patterns in pupil information consisting of grades, attendance, and remarks. Data mining additionally permits the advent of character learning plans, making sure that scholars get hold of personalized aid based totally on their specific strengths and weaknesses. By combining information-driven insights with personalized studying and actual-international packages, Smart Skill Mentor helps instructional institutions bridge the gap between idea and practice. This approach will increase student engagement, helps skill improvement, and improves common educational overall performance, thereby better making ready students for enterprise challenges. The end result is a extra dynamic, impactful, and enterprise-targeted getting to know revel in.

Sathyabama Institute of Science and Technology (IN)
Openalex Percentile: Top 80%
Engineering Education and Technology
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Smartskill Mentor: Integrating AI for Personalised Student Skill Development — Pauline Mary, A. Panasa Reddy, et al. · (2025) | TGRS Research Map | TGRS