Las Seis Gestalts: reformulando las habilidades duras y blandas como roles sistémicos para el desarrollo profesional
Número
Sección
Publicado
30-04-2026
Resumen
Este artículo propone las Seis Gestalts como marco sistémico que reformula las habilidades duras y blandas en roles cognitivos para crecimiento profesional. En el núcleo está el Problem-Solver, razonamiento preventivo-adaptativo que actúa como columna dorsal y convierte necesidades en soluciones. Lo complementan Maverick, Specialist, Architect, Shark y Connector, que integran lo duro y lo blando para colaborar eficazmente. El marco opera a varios niveles (equipos, procesos y grupos interfuncionales) y, basado en décadas de mentoría y docencia, desplaza el foco de los silos de habilidades hacia la integración de roles, preparando a personas y organizaciones para sistemas complejos y cambiantes.
Palabras clave:
Educación, habilidades duras y blandas, aprendizaje holístico, pensamiento crítico, resolución de problemas
Agencias de apoyo
NoReferencias
AHUETT-GARZA, H., URBINA CORONADO, P. D., NORIEGA VELASCO, J., DÍAZ DE LEÓN LÓPEZ, E., MARKERT, B., & KURFESS, T. R. (2022). Train the trainers in industry 4.0: A model for the development of competencies in non-synchronous environments. International Journal on Interactive Design and Manufacturing, 16(2), 775–789. https://doi.org/10.1007/s12008-022-00901-5
ALTER, S. (2022). Understanding artificial intelligence in the context of usage: Contributions and smartness of algorithmic capabilities in work systems. International Journal of Information Management, 67, 102392. https://doi.org/10.1016/j.ijinfomgt.2021.102392
ARASTOOPOUR IRGENS, G., DABHOLKAR, S., BAIN, C., WOODS, P., HALL, K., SWANSON, H., HORN, M., & WILENSKY, U. (2020). Modeling and Measuring High School Students’ Computational Thinking Practices in Science. Journal of Science Education and Technology, 29(1), 137–161. https://doi.org/10.1007/s10956-020-09811-1
ASHBY, W. R. (1956). An Introduction to Cybernetics. Chapman and Hall.
BIKANGA ADA, M., & FOSTER, M. E. (2023). Enhancing postgraduate students’ technical skills: Perceptions of modified team-based learning in a six-week multi-subject Bootcamp-style CS course. Computer Science Education, 33(2), 186–210. https://doi.org/10.1080/08993408.2021.1959174
BJELICA, D. L., MIHIC, M., PETROVIC, D., PERUNICIC-MLADENOVIC, I., PAVLOVIC, D., BODROZA, D., DJUKIC, M., DABETIC, V., & TOMIC, A. D. (2025). The Relationship Between Teaching Approaches and Engineering Students’ Life Satisfaction. International Journal of Engineering Education, 41(2), 409–421.
BRODLEY, C. E., REBBAPRAGADA, U., SMALL, K., & WALLACE, B. (2012). Challenges and Opportunities in Applied Machine Learning. AI Magazine, 33(1), Article 1. https://doi.org/10.1609/aimag.v33i1.2367
CAI, C. J., & GUO, P. J. (2019). Software Developers Learning Machine Learning: Motivations, Hurdles, and Desires. 2019 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 25–34. https://doi.org/10.1109/VLHCC.2019.8818751
CARDÓS, M., MAHEUT, J., CANOS-DAROS, L., CORTES, P., & ANDRES, C. (2024). Design of a learning environment based on reverse teaching in Industrial Organization Engineering subjects. Direccion y Organizacion, 82, 72–86. https://doi.org/10.37610/dyo.v0i82.661
CHANG, W.-C. (2025). Problem-based Learning in a Data Visualization University Course During COVID-19. International Journal of Engineering Education, 41(2), 365–370.
CHATLEY, R., & FIELD, T. (2017). Lean Learning—Applying Lean Techniques to Improve Software Engineering Education. 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering Education and Training Track (ICSE-SEET), 117–126. https://doi.org/10.1109/ICSE-SEET.2017.5
CRESSWELL-YEAGER, T. (2021). Forming, storming, norming, and performing: Using a semester-long problem-based learning project to apply small-group communication principles. Communication Teacher, 35(2), 155–165. https://doi.org/10.1080/17404622.2020.1842476
ELDER, L., & PAUL, R. (1998). The Role of Socratic Questioning in Thinking, Teaching, and Learning. The Clearing House. https://doi.org/10.1080/00098659809602729
GALL, J. (1977). Systemantics: How Systems Work and Especially How They Fail. Quadrangle/The New York Times Book Co.
GUAL, J. C., CLIMENT, R. P., REGALIZA, J. C. P., & GARCÍA, F. J. P. (2024). Pipes and puddles framework: Risk management in manufacturing processes to reduce the total cost of quality. Journal of Industrial Engineering and Management, 17(1), Article 1. https://doi.org/10.3926/jiem.6448
HECKMAN, J. J., & KAUTZ, T. (2012). Hard evidence on soft skills. Labour economics, 19(4), 451-464
JONASSEN, D. (2014). Engineers as problem solvers. In Johri & B. Olds (Eds.), Cambridge handbook of engineering education research (pp. 103–118). Cambridge University Press. https://doi.org/10.1017/CBO9781139013451.009
KROPP, M., & MEIER, A. (2014). New sustainable teaching approaches in software engineering education. 2014 IEEE Global Engineering Education Conference (EDUCON), 1019–1022. https://doi.org/10.1109/EDUCON.2014.6826229
LORENTE, P. J., & PEREDA, M. (2024). Experience the Prisoner's Dilemma: a game-based learning tool. Dirección y Organización, 18-27. https://doi.org/10.37610/ntvzy102
LUBURIĆ, N., SLIVKA, J., DORIĆ, L., PROKIĆ, S., & KOVAČEVIĆ, A. (2025). A framework for designing software engineering project-based learning experiences based on the 4 C/ID model. Education and Information Technologies, 30(2), 1947–1977. https://doi.org/10.1007/s10639-024-12882-x
LYU, W., & LIU, J. (2021). Soft skills, hard skills: What matters most? Evidence from job postings. Applied Energy, 300, 117307
MING, X., VAN DER VEEN, J., & MACLEOD, M. (2024). Competencies in interdisciplinary engineering education: Constructing perspectives on interdisciplinarity in a Q-sort study. European Journal of Engineering Education, 50(2), 406–427. https://doi.org/10.1080/03043797.2024.2397419
ÖZKAN, D. S., DAVIS, K. A., DAVIS, J. C., DETERS, J., & MURZI, H. (2024). Fostering systems thinking through engineering study abroad programs. European Journal of Engineering Education, 0(0), 1–26. https://doi.org/10.1080/03043797.2024.2434168
PALEYES, A., URMA, R.-G., & LAWRENCE, N. D. (2022). Challenges in Deploying Machine Learning: A Survey of Case Studies. ACM Computing Surveys, 55(6), 114:1-114:29. https://doi.org/10.1145/3533378
PANTOJA YÉPEZ, W. L., HURTADO ALEGRÍA, J. A., BANDI, A., & KIWELEKAR, A. W. (2024). Training software architects suiting software industry needs: A literature review. Education and Information Technologies, 29(9), 10931–10994. https://doi.org/10.1007/s10639-023-12149-x
PATEL, K., FOGARTY, J., LANDAY, J. A., & HARRISON, B. (2008). Investigating statistical machine learning as a tool for software development. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 667–676. https://doi.org/10.1145/1357054.1357160
PENG, A., HUNTER, S., & MILLER, S. R. (2025). An Examination of Individual Attributes and their Impact on Team Creative Design Outputs. International Journal of Engineering Education, 41(3), 598–615.
QAMAR, S. Z., PERVEZ, T., & AL-KINDI, M. (2019). Engineering Education: Challenges, Opportunities, and Future Trends. 26–28.
RAVEN, R., VAN DEN BOSCH, S., & WETERINGS, R. (2010). Transitions and strategic niche management: towards a competence kit for practitioners. International Journal of Technology Management, 51(1), 57-74.
RAVI, M., & BESHARAT, M. (2025). A holistic consideration of authentic assessments: Student perception of assessment design, delivery, flexibility and creativity. European Journal of Engineering Education, 0(0), 1–18. https://doi.org/10.1080/03043797.2025.2480116
REDMAN, T. C., & DAVENPORT, T. H. (2023). The rise of connector roles in data science. MIT Sloan Management Review, 65(1).
SCHULZ, B. (2008). The importance of soft skills: Education beyond academic knowledge. Journal of Language and Communication, 2(1), 146-154 https://doi.org/10.1016/0006-3207(93)90452-7
TAN, B., JIN, H.-Y., & CUTUMISU, M. (2024). The applications of machine learning in computational thinking assessments: A scoping review. Computer Science Education, 34(2), 193–221. https://doi.org/10.1080/08993408.2023.2245687
TO, T. T., AL MAHMUD, A., & RANSCOMBE, C. (2025). A framework for integrating additive manufacturing into engineering education: Perspectives of students and educators. European Journal of Engineering Education, 50(2), 298–319. https://doi.org/10.1080/03043797.2024.2358368
TUCKMAN, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63(6), 384–399. https://doi.org/10.1037/h0022100
WEBSTER, R., & TURNER, M. (2024). Assessing Industry-Critical Skill Development in Engineering Technology Capstone Courses. International Journal of Engineering Education, 40(5), 1262–1272.
XIANG, G., WANG, L., SUN, X., & TANG, W. (2024). A Work-based Project Practice Motivated by Problem-Solving in Software Engineering. International Journal of Engineering Education, 40(3), 511–519
ZAKARIA, Z., VANDENBERG, J., TSAN, J., BOULDEN, D. C., LYNCH, C. F., BOYER, K. E., & WIEBE, E. N. (2022). Two-Computer Pair Programming: Exploring a Feedback Intervention to improve Collaborative Talk in Elementary Students. Computer Science Education, 32(1), 3–29. https://doi.org/10.1080/08993408.2021.1877987
ZHOU, R., LI, Y., HE, X., JIANG, C., FANG, J., & LI, Y. (2024). Understanding undergraduates’ computational thinking processes: Evidence from an integrated analysis of discourse in pair programming. Education and Information Technologies, 29(15), 19367–19399. https://doi.org/10.1007/s10639-024-12597-z
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Derechos de autor 2026 Carlos García-Gerbolés, José Costas Gual, Raúl Pino, Rafael Pastor-Climent

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.

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