In this study, 100 new employees were randomly divided into experimental group (AI-based personalized learning path) and control group (traditional skills training path) for a three-month comparative experiment. The experimental group collected learner data through AI technology, customized personalized learning plans, recommended learning resources, and provided immediate feedback and evaluation. The control group received traditional training with unified curriculum and fixed teaching resources. The results show that the experimental group is significantly better than the control group in comprehensive skills test scores, task completion rate, learning satisfaction, learning motivation and participation. Statistical analysis shows that there are significant differences in learning progress, achievements and attitudes between the experimental group and the control group, and the personalized learning path has a significant effect on improving the learning effect of employees. Correlation analysis further reveals the positive correlation between learning time, skill test scores and employee satisfaction and participation. This study confirms the potential of AI-based personalized learning path in improving the effect of skills training, and provides a useful reference for the further development and application of personalized learning in the field of education in the future.

Zhao Dongyan. Research on personalized learning path design and skill training effect improvement based on artificial intelligence. Frontiers in Educational Research (2025) Vol. 8, Issue 2: 168-173. https://doi.org/10.25236/FER.2025.080224.

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