Abstract
Career selection is a vital decision which has a strong impact on the academic and professional future of a student. Traditional forms of career counseling methods offer generic advice and do not give appropriate regard to individual aptitude, personality traits and performances at school. This paper suggests a Personalized Career Guidance System which combines psychometric analysis and clustering methods for obtaining customized career guidance to school students. The system uses available academic information, cognitive capabilities and psychological characteristics as input parameters for assigning students into meaningful groups and for making specific career recommendations. Experimental evaluation showed better recommendation accuracy and better student satisfaction than traditional counseling methods. The proposed system is supportive to smart education by enabling structured, data-driven and personalized career planning.
Keywords
Career Guidance, Psychometric Analysis, K-Means Clustering, Educational Data Mining, Personalised Recommendation System.
Citations
IRE Journals:
Arti B. R., Narmadha M., P. M. C. Nisha "Personalized Career Guidance for School Students for Smart Education" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 926-929 https://doi.org/10.64388/IREV9I10-1716180
IEEE:
Arti B. R., Narmadha M., P. M. C. Nisha
"Personalized Career Guidance for School Students for Smart Education" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716180
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