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Systematic Review of Common Factors Used to Measure Individuals’ Career Choice

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Advances in Visual Informatics (IVIC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13051))

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Abstract

Many individuals are faced with the challenge of a career choice that is appropriate for them. This is due to the fact that decisions are made up of a variety of subjective judgments. As a result, selecting a career path without first assessing an individual’s suitability as a foundational step can result in an unfavorable outcome. This paper aims to investigate and summarize the evidence of common factors used in the domain of career guidance. This study adapts Systematic Literature Review (SLR) techniques by utilizing research questions and Boolean search strings to identify prospective studies from three established databases that are related to the research area. In this study, 28 articles, consisting of 17 journals and 11 conference proceedings, were selected through a systematic process. All articles underwent a rigorous selection protocol to ensure content quality according to formulated research questions. We categorize and document the common factors in career selection which can benefit in the development of a career decision-making system that helps individuals visualize their future career path.

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References

  1. Abe, E.N., Chikoko, V.: Exploring the factors that influence the career decision of STEM students at a university in South Africa. Int. J.STEM Educ. 7(1), 1–14 (2020). https://doi.org/10.1186/s40594-020-00256-x

    Article  Google Scholar 

  2. Akosah-Twumasi, P., Emeto, T.I., Lindsay, D., Tsey, K., Malau-Aduli, B.S.: A systematic review of factors that influence youths career choices—the role of culture. Front. Educ. (2018). https://doi.org/10.3389/feduc.2018.00058

    Article  Google Scholar 

  3. Poh Li, L., Aqeel, K., Abdullah, H.S., Fong Peng, C.: The effectiveness of career exploration program for high school students. Int. Conf. Humanit. Soc. Cult. IPEDR 20, 226–230 (2011)

    Google Scholar 

  4. Dodd, V., Hanson, J., Hooley, T.: Increasing students’ career readiness through career guidance: measuring the impact with a validated measure. Br. J. Guid. Couns. (2021). https://doi.org/10.1080/03069885.2021.1937515

    Article  Google Scholar 

  5. Balogun, V.F., Thompson, A.F., State, O.: Career master : a decision support system (DSS) for guidance and counseling in Pacific. J. Sci. Technol. 10, 337–354 (2009)

    Google Scholar 

  6. Castellano, E.J., Martínez, L.: A web-decision support system based on collaborative filtering for academic orientation. Case study of the spanish secondary school. J. Univers. Comput. Sci. 15, 2786–2807 (2009)

    Google Scholar 

  7. Kinanee, J.B.: Factors in the career decision-making of nurses in rivers state of Nigeria : implications for counselling. J. Psychol. Couns. 1, 134–138 (2009)

    Google Scholar 

  8. Razak, T.R., Hashim, M.A., Noor, N.M., Halim, I.H.A., Shamsul, N.F.F.: Career path recommendation system for UiTM perlis students using fuzzy logic. In: ICIAS2014: 2014 5th International Conference on Intelligent and Advanced Systems (ICIAS) (2014)

    Google Scholar 

  9. Gupta, M.V., Patil, P., Deshpande, S., Arisetty, S., Asthana, S.: FESCCO: Fuzzy expert system for career counselling. Int. J. Recent Innov. Trends Comput. Commun. 5, 239–243 (2017)

    Google Scholar 

  10. Sahu, R., Dash, S.R., Das, S.: Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory. Dec. Mak. Appl. Manag. Eng. 4(1), 104–126 (2021). https://doi.org/10.31181/dmame2104104s

    Article  Google Scholar 

  11. Yuan, B., Li, J.: Social-economics, community, campus and family: a nationwide empirical investigation on the association between adverse childhood experiences and early career choice of youths and adolescents. Int. J. Adolesc. Youth 25, 221–239 (2020). https://doi.org/10.1080/02673843.2019.1608274

    Article  Google Scholar 

  12. Girouard, H.S., Kovacs, A.H.: Congenital heart disease: education and employment considerations and outcomes. Int. J. Cardiol. Congenit. Hear. Dis. 1, 100005 (2020). https://doi.org/10.1016/j.ijcchd.2020.100005

    Article  Google Scholar 

  13. Shankhdhar, A., Agrawal, A., Sharma, D., Chaturvedi, S., Pushkarna, M.: Intelligent decision support system using decision tree method for student career. In: 2020 International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2020, pp. 140–142 (2020). https://doi.org/10.1109/PARC49193.2020.246974

  14. Sampson, J.P., Toh, R.: Improving career decision-making of highly skilled workers: designing interventions for the unemployed and discouraged. Br. J. Guid. Couns. 49, 228–241 (2021). https://doi.org/10.1080/03069885.2021.1892589

    Article  Google Scholar 

  15. Bennett, D., Knight, E., Dockery, A.M., Bawa, S.: Pedagogies for employability: understanding the needs of STEM students through a new approach to employability development. High. Educ. Pedagog. 5, 340–359 (2020). https://doi.org/10.1080/23752696.2020.1847162

    Article  Google Scholar 

  16. Ryba, T.V., Zhang, C.-Q., Huang, Z., Aunola, K.: Career adapt-abilities scale – dual career form (CAAS-DC): psychometric properties and initial validation in high-school student-athletes. Heal. Psychol. Behav. Med. 5, 85–100 (2017). https://doi.org/10.1080/21642850.2016.1273113

    Article  Google Scholar 

  17. Batool, S.S., Ghayas, S.: Process of career identity formation among adolescents: components and factors. Heliyon 6, e04905 (2020). https://doi.org/10.1016/j.heliyon.2020.e04905

    Article  Google Scholar 

  18. Udayar, S., Fiori, M., Thalmayer, A.G., Rossier, J.: Investigating the link between trait emotional intelligence, career indecision, and self-perceived employability: the role of career adaptability. Pers. Individ. Dif. 135, 7–12 (2018). https://doi.org/10.1016/j.paid.2018.06.046

    Article  Google Scholar 

  19. Lee, P.C., Xu, S., Yang, W.: Is career adaptability a double-edged sword? The impact of work social support and career adaptability on turnover intentions during the COVID-19 pandemic. Int. J. Hosp. Manag. 94, 102875 (2021). https://doi.org/10.1016/j.ijhm.2021.102875

    Article  Google Scholar 

  20. Bargsted, M.: Impact of personal competencies and market value of type of occupation over objective employability and perceived career opportunities of young professionals. J. Work Organ. Psychol. 33, 115–123 (2017). https://doi.org/10.1016/j.rpto.2017.02.003

    Article  Google Scholar 

  21. Kiselev, P., Kiselev, B., Matsuta, V., Feshchenko, A., Bogdanovskaya, I., Kosheleva, A.: Career guidance based on machine learning: social networks in professional identity construction. Procedia Comput. Sci. 169, 158–163 (2020). https://doi.org/10.1016/j.procs.2020.02.128

    Article  Google Scholar 

  22. Meroni, E.C., Vera-Toscano, E.: The persistence of overeducation among recent graduates. Labour Econ. 48, 120–143 (2017). https://doi.org/10.1016/j.labeco.2017.07.002

    Article  Google Scholar 

  23. Ebner, K., Thiele, L., Spurk, D., Kauffeld, S.: Validation of the German career decision-making profile—an updated 12-factor version. J. Career Assess. 26, 111–136 (2018). https://doi.org/10.1177/1069072716679996

    Article  Google Scholar 

  24. Alhomoud, F.K., AlGhalawin, L., AlGofari, G., AlDjani, W., Ameer, A., Alhomoud, F.: Career choices and preferences of Saudi pharmacy undergraduates: a cross sectional study. Saudi Pharm. J. 27, 467–474 (2019). https://doi.org/10.1016/j.jsps.2019.01.009

    Article  Google Scholar 

  25. Shahbazian, R.: Under the influence of our older brother and sister: the association between sibling gender configuration and STEM degrees. Soc. Sci. Res. 97, 102558 (2021). https://doi.org/10.1016/j.ssresearch.2021.102558

    Article  Google Scholar 

  26. Situmorang, D.D.B., Salim, R.M.A.: Perceived parenting styles, thinking styles, and gender on the career decision self-efficacy of adolescents: how & why? Heliyon 7, e06430 (2021). https://doi.org/10.1016/j.heliyon.2021.e06430

    Article  Google Scholar 

  27. Wei, L., Zhou, S., Hu, S., Zhou, Z., Chen, J.: Influences of nursing students’ career planning, internship experience, and other factors on professional identity. Nurse Educ. Today 99 (2021)

    Google Scholar 

  28. Halim, L., Abd Rahman, N., Zamri, R., Mohtar, L.: The roles of parents in cultivating children’s interest towards science learning and careers. Kasetsart J. Soc. Sci. 39, 190–196 (2018). https://doi.org/10.1016/j.kjss.2017.05.001

    Article  Google Scholar 

  29. Desnelita, Y., Rukun, K., Syahril, S., Nasien, D., Gustientiedina, G., Vitriani, V.: Intelligent decision support system using certainty factor method for selection student career. In: Proceedings – 2018 2nd International Conference on Electrical Engineering and Informatics: Toward the Most Efficient Way of Making and Dealing with Future Electrical Power System and Big Data Analysis, ICon EEI 2018, pp. 18–23 (2018). https://doi.org/10.1109/ICon-EEI.2018.8784143

  30. Damayanti, A.S., Wibawa, A.P., Pujianto, U., Nafalski, A.: The use of adaptive neuro fuzzy inference system in determining students’ suitable high school major. In: 2018 4th Int. Conf. Educ. Technol, ICET 2018, pp. 1–4 (2018). https://doi.org/10.1109/ICEAT.2018.8693933

  31. Irwan, G., Sunarti, Y.D.: Counseling model application: a student career development guidance for decision maker and consultation. IOP Conf. Ser. Earth Environ. Sci. 97, 012045 (2017). https://doi.org/10.1088/1755-1315/97/1/012045

    Article  Google Scholar 

  32. Rangnekar, R.H., Suratwala, K.P., Krishna, S., Dhage, S.: Career Prediction model using data mining and linear classification. In: Proceedings – 2018 4th International Conference on Computing, Communication Control and Automation, ICCUBEA 2018, pp. 1–6. IEEE (2018). https://doi.org/10.1109/ICCUBEA.2018.8697689

  33. Chen, Y.T., Peng, W.C., Yu, H.Y.: Identify key factors for career choice by using TOPSIS and fuzzy cognitive map. In: Proceedings – 17th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2018, pp. 104–109. IEEE (2018). https://doi.org/10.1109/ICIS.2018.8466384

  34. Tulus, N., Situmorang, Z.: Analysis optimization k-nearest neighbor algorithm with certainty factor in determining student career. In: MECnIT 2020 – International Conference on Mechanical, Electronics, Computer, and Industrial Technology, pp. 306–310 (2020). https://doi.org/10.1109/MECnIT48290.2020.9166669

  35. Jamal, K., Kurniawan, R., Husti, I., Zailani, Nazri, M.Z.A., Arifin, J.: Predicting career decisions among graduates of tafseer and hadith. In: 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020 (2020). https://doi.org/10.1109/ICCIS49240.2020.9257663

  36. Cruz, A.F., Orozco, L., Gonzales, C.: Intelligent web platform for vocational guidance. In: Proceedings – 2019 Int. Conf. Virtual Real. Vis. ICVRV 2019. 205–207 (2019). https://doi.org/10.1109/ICVRV47840.2019.00049

  37. Satu, MS, Ahamed, S., Chowdhury, A., Whaiduzzaman, M.: Exploring significant family income ranges of career decision difficulties of adolescents in Bangladesh applying regression techniques. In: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019, pp. 1–6. IEEE (2019). https://doi.org/10.1109/ECACE.2019.8679415

  38. Vilhjálmsdóttir, G.: Young workers without formal qualifications: experience of work and connections to career adaptability and decent work. Br. J. Guid. Couns. 49, 242–254 (2021). https://doi.org/10.1080/03069885.2021.1885011

    Article  Google Scholar 

  39. Spurk, D.: Vocational behavior research: Past topics and future trends and challenges. J. Vocat. Behav. 126, 103559 (2021). https://doi.org/10.1016/j.jvb.2021.103559

    Article  Google Scholar 

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Acknowledgment

This study was funded by BOLD Research Grant 2021 Universiti Tenaga Nasional (J510050002/2021042). We would like to thank UNITEN Innovation & Research Management Centre (iRMC) for fund management.

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Authors and Affiliations

  1. Institute of Informatics and Computing in Energy (IICE), Universiti Tenaga Nasional, 43000 Putrajaya Campus, Jalan Ikram-Uniten, 43000, Kajang, Selangor, Malaysia

    Feninferina Azman, Azimah Abdul Ghapar, Masyura Ahmad Faudzi, Hasventhran Baskaran & Fiza Abdul Rahim

  2. Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100, Kuala Lumpur, Malaysia

    Fiza Abdul Rahim

Authors
  1. Feninferina Azman
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  2. Azimah Abdul Ghapar
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  3. Masyura Ahmad Faudzi
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  4. Hasventhran Baskaran
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  5. Fiza Abdul Rahim
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Corresponding author

Correspondence to Feninferina Azman .

Editor information

Editors and Affiliations

  1. Universiti Tenaga Nasional, Selangor, Malaysia

    Halimah Badioze Zaman

  2. Dublin City University, Dublin, Ireland

    Alan F. Smeaton

  3. National Central University, Jhongli, Taiwan

    Timothy K. Shih

  4. Queen Mary University of London, London, UK

    Sergio Velastin

  5. Toyo University, Tokyo, Japan

    Tada Terutoshi

  6. University of Southern Denmark, Odense, Denmark

    Bo Nørregaard Jørgensen

  7. Universiti Tenaga Nasional, Selangor, Malaysia

    Hazleen Aris

  8. Universiti Tenaga Nasional, Selangor, Malaysia

    Nazrita Ibrahim

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Azman, F., Abdul Ghapar, A., Ahmad Faudzi, M., Baskaran, H., Rahim, F.A. (2021). Systematic Review of Common Factors Used to Measure Individuals’ Career Choice. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2021. Lecture Notes in Computer Science(), vol 13051. Springer, Cham. https://doi.org/10.1007/978-3-030-90235-3_10

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  • DOI: https://doi.org/10.1007/978-3-030-90235-3_10

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  • Publisher Name: Springer, Cham

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