Modelo adaptativo de clasificación de profesiones en sistemas de orientación vocacional
Resumen
La orientación vocacional forma parte del desarrollo psicosocial y se entiende, como un método que ayuda a determinar la profesión más adecuada, en función de las aptitudes y capacidades de los estudiantes. Los procesos de orientación vocacional, son dinámicos y se enfocan en educar y favorecer el proceso de toma de decisiones en la elección profesional. proporcionándoles un camino de aprendizaje claro para seguir a lo largo de su vida y para que la sociedad se beneficie de su talento enfocado. La mayoría de soluciones actuales, teóricas y de aplicación, de Europa y Norteamérica, difieren al utilizarse en el contexto colombiano, principalmente para adultos, las cuales en términos del proceso de clasificación de profesiones presentan bajos niveles de exactitud y precisión. Además, existen diversos proyectos educativos y sistemas de evaluación en los centros de enseñanza secundaria. En este nivel de educación, los estudiantes tienen una decisión vocacional cambiante que implica tener en cuenta características específicas del contexto, también, los determinantes su perfil de orientación vocacional. El objetivo del presente artículo es describir el modelo adaptativo de clasificación de profesiones, integrado a la Plataforma Web Inteligente, utilizada en instituciones educativas del Departamento del Cauca. El uso de la metodología CRISP-DM permitió encontrar los algoritmos de Naive Bayes y Deep learning como los de mejor desempeño en la clasificación de profesiones.
Palabras clave
inteligencia adaptativa, minería de datos, orientación vocacional, plataforma web
Biografía del autor/a
Andrés-Felipe Cruz-Eraso
Roles: Investigación, Metodología, Escritura-Borrador original, Software.
Carolina González-Serrano
Roles: Investigación, Metodología, Escritura-revisión y edición.
Referencias
- 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
Descargas
Los datos de descargas todavía no están disponibles.