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1716180 Vol 9 · Issue 10 Download Paper

Personalized Career Guidance for School Students for Smart Education

Arti B. R. Narmadha M. P. M. C. Nisha

Subject area: Science,Engineering and Technology  ·  Area of research: Computer Science

DOI: https://doi.org/10.64388/IREV9I10-1716180

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.

References

[1] L. Ding, T. Li, S. Jiang, and A. Gapud, Students perceptions of the use of AI-based tools in education in International Journal of Educational Technology in Higher Education, vol. 20, no. 1, 2023.

[2] The study by C. C. Tossell et al. (2024) demonstrates that learners perceive the use of AI in assignments as a competitive advantage of artificial intelligence over human instruction.

[3] The article by Y. Niu and H. Xue describes the manner in which cognitive ability modelling and AI-based recommendation can be applied to the education domain, with the article being published in IEEE Access, Volume 11,2023.

[4] R. Ren et al., “Artificial intelligence-based educational supportive systems in educational institutions IEEE Access, vol. 10, 2022.

[5] R. Roy et al., “The implementation of the artificial intelligence technologies in higher education institutions 10 eds. by IEEE, vol. 10, 2022.

How to cite this paper

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
Arti B. R., Narmadha M., P. M. C. Nisha "Personalized Career Guidance for School Students for Smart Education" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026, doi: https://doi.org/10.64388/IREV9I10-1716180
Arti B. R., Narmadha M., P. M. C. Nisha (2026). Personalized Career Guidance for School Students for Smart Education. Iconic Research And Engineering Journals, 9(10). doi: https://doi.org/10.64388/IREV9I10-1716180
Arti B. R., Narmadha M., P. M. C. Nisha "Personalized Career Guidance for School Students for Smart Education" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026. Crossref, https://doi.org/10.64388/IREV9I10-1716180
@article{1716180,
      author = {Arti B. R., Narmadha M., P. M. C. Nisha},
      title = {Personalized Career Guidance for School Students for Smart Education},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {926-929},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716180.pdf},
      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.},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716180}
  }