AI-Enabled personalized learning ecology construction and its implications for prevocational education

This paper discusses the construction of AI-enabled personalized learning ecology and its implications for pre-professional prospective education. With the rapid development of AI technology, the field of education is undergoing profound changes. This study analyzes the problems of homogeneous teaching, low learning efficiency and lagging career planning in the current education field, and describes the current status of the application of AI technology in personalized learning. On this basis, the idea of constructing an AI-enabled personalized learning ecosystem is proposed, including the core elements of intelligent diagnosis and assessment, adaptive learning path planning, virtual tutor and intelligent tutoring, and learning data analysis and feedback. The study further explores the impact of this new type of learning ecosystem on pre-vocational education, including aspects such as early identification of career interests and abilities, dynamic career path planning, and practice-oriented learning experience design. Finally, the article proposes implementation strategies and challenges, providing new ideas and directions for future educational development.

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Publication Details

Journal
ITM Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/itmconf/20257701034
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Enabled personalized learning ecology construction and its implications for prevocational education

Qi Su
ITM Web of Conferences
Online Learning and Analytics
article

AI-Enabled personalized learning ecology construction and its implications for prevocational education

Qi Su
article en

Abstract

This paper discusses the construction of AI-enabled personalized learning ecology and its implications for pre-professional prospective education. With the rapid development of AI technology, the field of education is undergoing profound changes. This study analyzes the problems of homogeneous teaching, low learning efficiency and lagging career planning in the current education field, and describes the current status of the application of AI technology in personalized learning. On this basis, the idea of constructing an AI-enabled personalized learning ecosystem is proposed, including the core elements of intelligent diagnosis and assessment, adaptive learning path planning, virtual tutor and intelligent tutoring, and learning data analysis and feedback. The study further explores the impact of this new type of learning ecosystem on pre-vocational education, including aspects such as early identification of career interests and abilities, dynamic career path planning, and practice-oriented learning experience design. Finally, the article proposes implementation strategies and challenges, providing new ideas and directions for future educational development.

ITM Web of ConferencesVol. 77
Shandong Xiehe University (CN)
Openalex Percentile: Top 84%
Online Learning and Analytics
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