AI-Augmented Skill Development Roadmaps: Tailoring 12-Month Learning Paths for Future-Ready Careers in Education 4.0 and Industry 4.0

In fact, rapid convergence between Education 4.0 and Industry 4.0 demands adaptive learning models that would equip people with future-ready skills in the dynamically changing workforce. This work introduces AI-augmented skill development roadmaps, underlining how to design and implement personalized 12-month learning paths. The proposed framework is based on data-driven learner profiling, machine learning algorithms, and continuous adaptive assessments for optimization of building individual learning pathways toward emerging technology trends alignment. This review will be predicated on existing AI applications in competency development, identifying gaps in conventional models. It also involves the holistic roadmap structure: milestones, phases, and progression metrics. Case studies of real-world examples would then be delivered where AI-powered learning pathways have resulted in targeted competency development, employability, and lifelong learning. The key performance indicators will be defined to provide the effectiveness of the framework for scalability and adaptability. The findings bring to the fore that AI can cause a paradigm shift in skill gaps through enabling personalized learning at scale and furthering strategic goals related to Industry 4.0. This research makes a substantial contribution to the development of scalable education models for essential competencies that are part of the fast-evolving facets of digitalization.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/smart63812.2024.10882483
Citations
37
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
28.83
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article

AI-Augmented Skill Development Roadmaps: Tailoring 12-Month Learning Paths for Future-Ready Careers in Education 4.0 and Industry 4.0

Rahul Vadisetty, Anand Polamarasetti
37 citations
Engineering Education and Technology
28.83
article

AI-Augmented Skill Development Roadmaps: Tailoring 12-Month Learning Paths for Future-Ready Careers in Education 4.0 and Industry 4.0

Rahul Vadisetty, Anand Polamarasetti
article en
37 citations

Abstract

In fact, rapid convergence between Education 4.0 and Industry 4.0 demands adaptive learning models that would equip people with future-ready skills in the dynamically changing workforce. This work introduces AI-augmented skill development roadmaps, underlining how to design and implement personalized 12-month learning paths. The proposed framework is based on data-driven learner profiling, machine learning algorithms, and continuous adaptive assessments for optimization of building individual learning pathways toward emerging technology trends alignment. This review will be predicated on existing AI applications in competency development, identifying gaps in conventional models. It also involves the holistic roadmap structure: milestones, phases, and progression metrics. Case studies of real-world examples would then be delivered where AI-powered learning pathways have resulted in targeted competency development, employability, and lifelong learning. The key performance indicators will be defined to provide the effectiveness of the framework for scalability and adaptability. The findings bring to the fore that AI can cause a paradigm shift in skill gaps through enabling personalized learning at scale and furthering strategic goals related to Industry 4.0. This research makes a substantial contribution to the development of scalable education models for essential competencies that are part of the fast-evolving facets of digitalization.

Andhra University (IN), Wayne State University (US)
Openalex Percentile: Top 0%
Engineering Education and Technology
28.83
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