Adaptive Model of Classification of Professions in Vocational Guidance Systems
Abstract
Vocational guidance is part of psychosocial development and is understood as a method that helps to determine the most appropriate profession according to the aptitudes and abilities of the student. The processes of vocational guidance are dynamic and focus on educating and favoring the decision-making process in the professional choice for a learning pathway throughout the student's life, which will benefit society in the long run. Most of the current solutions, both theoretical and applied, from Europe and North America differ when used in the Colombian context, mainly for adults, since the process of classifying professions is not accurate nor precise. In addition, there are various educational projects and evaluation systems in secondary education level institutions. At this level, the students have a changing vocational choice which implies taking into account specific characteristics of the context, also, the student profile vocational guidance determinants. The objective of this article is to describe the adaptive model of occupational classification integrated into the Intelligent Web Platform used in educational institutions in the Department of Cauca. The use of the CRISP-DM methodology allowed finding the Naive Bayes and Deep learning algorithms as those with the best performance in the classification of professions.
Keywords
adaptive intelligent, datamining, vocational guidance, web platform
Author Biography
Andrés-Felipe Cruz-Eraso
Roles: Investigation, Methodology, Writing-original draft, Software.
Carolina González-Serrano
Roles: Investigation, Methodology, Writing-review & editing.
References
- I. Gati, N. Levin, S. Landman-Tal, “Decision-Making Models and Career Guidance,” in International Handbook of Career Guidance, 2019, pp. 115–145. https://doi.org/10.1007/978-3-030-25153-6_6
DOI: https://doi.org/10.1007/978-3-030-25153-6_6
- S. Whiston, N.Mitts, Y. Li, “Evaluation of Career Guidance Programs,” in International Handbook of Career Guidance, J. A. Athanasou and H. N. Perera, Eds. Cham: Springer International Publishing, 2019, pp. 815–834. https://doi.org/10.1007/978-3-030-25153-6_38
DOI: https://doi.org/10.1007/978-3-030-25153-6_38
- S. Niles, R. Vuorinen, A. Siwiec, “Training Career Practitioners for the Current Context,” in International Handbook of Career Guidance, J. A. Athanasou and H. N. Perera, Eds. Cham: Springer International Publishing, 2019, pp. 529–553. https://doi.org/10.1007/978-3-030-25153-6_25.
DOI: https://doi.org/10.1007/978-3-030-25153-6_25
- Y. Zambrano, Desarrollo de una aplicación web para la orientación vocacional y promoción de carreras STEM implementando técnicas de Data Mining, Grade Thesis, Universidad del Norte, Colombia, 2021. http://hdl.handle.net/10584/9857
- F. W. Vondracek, E. J. Porfeli, D. H. Ford, Living Systems Theory: Using a Person-in-Context Behaviour Episode Unit of Analysis in Career Guidance Research and Practice. 2019. https://doi.org/10.1007/978-3-030-25153-6_23
DOI: https://doi.org/10.1007/978-3-030-25153-6_23
- O. Zahour, E. H. Benlahmar, A. Eddaouim, O. Hourrane, “A comparative study of machine learning methods for automatic classification of academic and vocational guidance questions,” International Journal of Interactive Mobile Technologies, vol. 14, no. 8, pp. 43–60, 2020. https://doi.org/10.3991/ijim.v14i08.13005%0AOmar
DOI: https://doi.org/10.3991/ijim.v14i08.13005
- H. El-Sofany, S. El-Seoud, “A cloud-based educational and career guidance model using fuzzy logic concepts,” ACM International Conference Proceeding Series, pp. 167–172, 2019. https://doi.org/10.1145/3328833.3328846
DOI: https://doi.org/10.1145/3328833.3328846
- H. Youssef, A. Moumen, D. Gretete, “Fuzzy Logic for Academic Orientation and Its Impact on Success: Content Analysis,” in Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML, pp. 546–551, 2022. https://doi.org/10.5220/0010742200003101
DOI: https://doi.org/10.5220/0010742200003101
- R. M. Acerado, R. C. Morco, J. R. Santos, J. J. Carpio, H. A. Isanan, “Predict: A mobile application for predicting the students’ career using naïve bayes algorithm,” in Proceedings of the 2nd International Conference on Software Engineering and Information Management, 2019, pp. 119–123. https://doi.org/10.1145/3305160.3305169
DOI: https://doi.org/10.1145/3305160.3305169
- H. Botello Peñaloza, “Incidencia de los programas de orientación vocacional en Colombia,” Horizontes Pedagógicos, vol. 1, no. 16, pp. 89–97, 2014. https://doi.org/10.33881/0123-8264.16108.
- C. M. Gonzalez Diaz, L. Ortegón, A. M. Diaz, Rutas de Vida. Manual de acompañamiento en orientación socio ocupacional, Bogotá D.C., 2015. https://www.mineducacion.gov.co/1759/w3-article-356514.html?_noredirect=1
- T. Pérez, J. Contreras, A. Puentes, Orientación vocacional aplicando sistemas basados en conocimiento, 2017.
- D. Marcela, P. Morales, A. Celmira, G. Gualteros, Red neuronal artificial para orientación profesional UDProfession, 2009.
- F. Téllez, E. Pineda, T. Meneses, J. Medina, “Sistemas expertos y orientación vocacional en educación a distancia virtualmente mediada,” Aibi, vol. 8, no. S1, pp. 186-195, 2021. https://doi.org/10.15649/2346030X.2424
DOI: https://doi.org/10.15649/2346030X.2424
- Y. Nieto, V. García-Díaz, C. Montenegro, R. G. Crespo, “Supporting academic decision making at higher educational institutions using machine learning-based algorithms,” Soft Computing, vol. 23, no. 12, pp. 4145–4153, 2019. https://doi.org/10.1007/s00500-018-3064-6
DOI: https://doi.org/10.1007/s00500-018-3064-6
- A. Cruz, L. Orozco, C. Gonzales, “Intelligent web platform for vocational guidance,” in Proceedings International Conference on Virtual Reality and Visualization, pp. 205–207, 2019. https://doi.org/10.1109/ICVRV47840.2019.00049
DOI: https://doi.org/10.1109/ICVRV47840.2019.00049
- A. Shipepe, A. Peters, “The hard struggle: A co-designed interactive career guidance online game,” in ACM International Conference Proceeding Series, 2018, pp. 314–317. https://doi.org/10.1145/3283458.3283512.
DOI: https://doi.org/10.1145/3283458.3283512
- E. Guardiola, S. Natkin, “A Game Design Methodology for Generating a Psychological Profile of Players,” in Serious Games Analytics: Methodologies for Performance Measurement, Assessment, and Improvement, C. S. Loh, Y. Sheng, and D. Ifenthaler, Eds. Cham: Springer International Publishing, 2015, pp. 363–380. https://doi.org/10.1007/978-3-319-05834-4_16
DOI: https://doi.org/10.1007/978-3-319-05834-4_16
- I. Dunwell, P. Lameras, S. de Freitas, P. Petridis, K. Star, M. Hendrix, S. Arnab, “Metycoon: A game-based approach to career guidance,” in 5th International Conference on Games and Virtual Worlds for Serious Applications, 2013, pp. 1-6. https://doi.org/10.1109/VS-GAMES.2013.6624237
DOI: https://doi.org/10.1109/VS-GAMES.2013.6624237
- O. Garcia, J. Serra, J. Membrives, J. Juarez, “Waypass: A Gamified Self-Knowledge Quest for Teenagers,” in 8th International Conference on Games and Virtual Worlds for Serious Applications, 2016, pp. 1–4. https://doi.org/10.1109/VS-GAMES.2016.7590380
DOI: https://doi.org/10.1109/VS-GAMES.2016.7590380
- D. Calvo, L. Quesada, G. López, L. Guerrero, “Multiplatform Career Guidance System Using IBM Watson, Google Home and Telegram,” in International Conference on Ubiquitous Computing and Ambient Intelligence, 2017, pp. 689–700. https://doi.org/10.1007/978-3-319-67585-5_67
DOI: https://doi.org/10.1007/978-3-319-67585-5_67
- H. Mrabet, A. Moussa, “Smart school guidance and vocational guidance system through the internet of things,” in ACM International Conference Proceeding Series, 2019. https://doi.org/10.1145/3320326.3320404
DOI: https://doi.org/10.1145/3320326.3320404
- N. Suresh, N. Mukabe, V. Hashiyana, A. Limbo, A. Hauwanga, “Career Counseling Chatbot on Facebook Messenger using AI,” in ACM International Conference Proceeding Series, pp. 65–73, 2021. https://doi.org/10.1145/3484824.3484875
DOI: https://doi.org/10.1145/3484824.3484875
- T. Razak, M. Hashim, N. Noor, I. Halim, N. Shamsul, “Career path recommendation system for UiTM Perlis students using fuzzy logic,” in 5th International Conference on Intelligent and Advanced Systems, pp. 1–5, 2014. https://doi.org/10.1109/ICIAS.2014.6869553
DOI: https://doi.org/10.1109/ICIAS.2014.6869553
- A. S. Rao, B. S. Kamath, R. R, Shreya Chowdhury, S. A Pattan, R. K. Kundar, “Use of Artificial Neural Network in Developing a Personality Prediction Model for Career Guidance: A Boon for Career Counselors,” International Journal of Control and Automation, vol. 13, no. 4, pp. 391–400, 2020.
- H. I. Bülbül, Ö. Ünsal, “Comparison of classification techniques used in machine learning as applied on vocational guidance data,” in Proceedings - 10th International Conference on Machine Learning and Applications, 2011, pp. 298–301. https://doi.org/10.1109/ICMLA.2011.49
DOI: https://doi.org/10.1109/ICMLA.2011.49
- M. Nawaz, A. Adnan, U. Tariq, F. Salman, R. Asjad, M. Tamoor, “Automated Career Counseling System for Students using CBR and J48,” Journal of Applied Environmental and Biological Sciences, vol. 4, no. 7S, pp. 113–120, 2015.
- A. Mundra, D. S. Chauhan, A. Soni, S. K. Sharma, P. Kumar, “Decision support system for determining right education career choice,” in ICC 2014-Computer Networks and Security, pp. 8–17, 2014.
- C. Zhenyu, “The Application of Big Data in Higher Vocational Education Based on Holland Vocational Interest Theory,” in Proceedings - 2017 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration, 2017, pp. 37–40. https://doi.org/10.1109/ICIICII.2017.59
DOI: https://doi.org/10.1109/ICIICII.2017.59
- W. C. Lu, “Future work-self salience and proactive career behavior among college student-athletes in Taiwan: A career construction model of adaptation,” Journal of Hospitality, Leisure, Sport & Tourism Education, vol. 27, e100259, 2020. https://doi.org/10.1016/j.jhlste.2020.100259
DOI: https://doi.org/10.1016/j.jhlste.2020.100259
- L. I. Jimenez-Raygoza, A. S. Medina-Vazquez, G. Perez-Torres, “Proposal of a computer system for vocational guidance with data mining,” in IEEE International Conference on Engineering Veracruz, 2019. https://doi.org/10.1109/ICEV.2019.8920523
DOI: https://doi.org/10.1109/ICEV.2019.8920523
- J. A. Cerrito, J. Trusty, R. J. Behun, “Comparing Web-Based and Traditional Career Interventions With Elementary Students: An Experimental Study,” Career Development Quarterly, vol. 66, no. 4, pp. 286–299, 2018. https://doi.org/10.1002/cdq.12151
DOI: https://doi.org/10.1002/cdq.12151
- Y. Turganbayev, G. Adilgazinov, Y. Barabanova, A. Zhakupov, G. Zhukibayeva, “Information System for Vocational Guidance, Employment and the Forecasting of Labor Demand: The Case of Kazakhstan,” in IEEE International Conference on Smart Information Systems and Technologies, pp. 28–30, 2021. https://doi.org/10.1109/SIST50301.2021.9465984
DOI: https://doi.org/10.1109/SIST50301.2021.9465984
- A. Afolabi, R. Ojelabi, L. Amusan, F. Adefarati, “Development of a web-based building profession career portal as a guidance information system for secondary school students,” in Proceedings of the IEEE International Conference on Computing, Networking and Informatics, pp. 1–10, 2017. https://doi.org/10.1109/ICCNI.2017.8123771
DOI: https://doi.org/10.1109/ICCNI.2017.8123771
- U. Paukstadt, K. Bergener, J. Becker, V. Dahl, C. Denz, I. Zeisberg, “Design recommendations for web-based career guidance platforms – Let young women experience IT careers!,” in Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 5116–5125, 2018. https://doi.org/10.24251/hicss.2018.639
DOI: https://doi.org/10.24251/HICSS.2018.639
- J. C. G. Vargas, J. L. P. Laguna, A. Carrillo-Ramos, “KunaySoft: Adaptive system of vocational guidance,” in 10th Computing Colombian Conference, pp. 448–455, 2015. https://doi.org/10.1109/ColumbianCC.2015.7333460
DOI: https://doi.org/10.1109/ColumbianCC.2015.7333460
- N. Cobelli, A. Bonfanti, S. Cubico, G. Favretto, “Quality and perceived value in career guidance e-services,” International Journal of Quality and Service Sciences, vol. 11, no. 1, pp. 53–68, 2019. https://doi.org/10.1108/IJQSS-12-2017-0114
DOI: https://doi.org/10.1108/IJQSS-12-2017-0114
- F. Martinez-Plumed, L. Contreras-Ochando, C. Ferri, J. Hernández-Orallo, M. Kull, N. Lachiche, M. J. Ramírez-Quintana, P. Flach, “CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories,” IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 8, pp. 3048–3061, 2021. https://doi.org/10.1109/TKDE.2019.2962680
DOI: https://doi.org/10.1109/TKDE.2019.2962680
- J. L. Holland, Making vocational choices: A theory of vocational personalities and work environments, US: Psychological Assessment Resources, 1997.
- A. Erdogan, Holland’s theory of careers and vocational choice, 2022.
- J. F. Martin Calvo, “Calidad educativa en la educación superior colombiana: una aproximación teórica,” Sophia, vol. 14, pp. 4–14, 2018. https://doi.org/10.18634/sophiaj.14v.2i.799
DOI: https://doi.org/10.18634/sophiaj.14v.2i.799
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