ORDERING THE MOST RELEVANT SKILLS IN AN ENGINEERING DEGREE USING FUZZY LOGIC. A CASE STUDY

Authors

  • J M. Brotons Martínez Department of Economic and Financial Studies, Miguel Hernández University, Elche, Spain
  • H. Puerto Molina Engineering Department, Miguel Hernández University, Elche, Spain
  • J. M. Cámara Zapata Applied Physics Department, Miguel Hernández University, Elche, Spain

DOI:

https://doi.org/10.20319/pijtel.2020.43.1427

Keywords:

Agricultural Engineering, Climate Change, Skills, Fuzzy

Abstract

Nowadays, the increasing uncertainty of a globalized world economy poses additional challenges to the new agricultural engineering graduates. They have to face increasingly complex challenges, such as increasing demand for agricultural produce in a Climate Change situation, a growing difficulty to guarantee food safety caused by global trade, and an improvement of the resilience of productive systems based on precision agriculture. All of this along with the drawback of a reduced interest of new students in this kind of graduate study. Previous works have dealt with the importance of the general skills in an agricultural engineering degree, showing the relevance of the instrumental skills (capacity for analysis and synthesis, organization and planning capacity, ability to manage information, oral and written communication, foreign language knowledge, computer knowledge, problem resolution, and decision making). This work aims to order these instrumental skills to face the above-mentioned challenges in a more effective way. We are aware that the result of this order presents high doses of uncertainty and ambiguity, and that is why we propose the use of fuzzy logic. The application of this methodology based on fuzzy mathematics can contribute to updating the university degrees so that graduates can successfully the new challenges they will encounter in the workplace. Results show that capacity for analysis and synthesis, organization and planning capacity, and foreign language knowledge is the best-considered skills

References

Aguado, P., Ayuga, F., Briassoulis, D., Panagakis, P., Febo, P., Comparetti, A., Scarascia-Mugnozza, G., O'Donnell, C., Navickas, K., & Fehrmann, J. (2011). The transition from Agricultural to Biosystems Engineering University Studies in Europe. In: 9th International Conference on Education and Information Systems, Technologies, and Applications. EISTA. Orlando USES.

ANECA (Nacional Agency of Evaluation of Quality and Accreditation) (2005). White paper on the Degree in agricultural engineering and forest engineering. 421 p.

ASABE. American Society of Agricultural and Biological Engineers, http://www.asabe.org/news-public-affairs/aboutthis-profess ion.aspx, Accessed 5 January 2020.

Baets, B., & Fodor, J. (1997). Twenty years of fuzzy preference structures. Rivista di Matematica per le Scienze Economiche e Sociali, 20(1), 45-66. https://doi.org/10.1007/BF02688988

Bermejo, S. P., Cabero, M. O., Pérez, A. G., Sampaio-Gomes, R. C., Santos, C. E., & Prieto, L. C. (2017). Operating Method at Engineering Classes: A Twist is Necessary. PUPIL: International Journal of Teaching, Education and Learning, 1(1), 13-25. https://doi.org/10.20319/pijtel.2017.11.1427

Cervero, A., Castro-Lopez, A., Álvarez-Blanco, L., Esteban, M., Bernardo, A. (2020). Evaluation of educational quality performance on virtual campuses using fuzzy inference systems, Plos one, 15(5) https://doi.org/10.1371/journal.pone.0232802

Hsu, W. L., Chen, Y. S., Shiau, Y. C., Liu, H. L., & Chern, T. Y. (2019). Curriculum Design in Construction Engineering department for colleges in Taiwan. Education Sciences, 65(9), 1-15 https://doi.org/10.3390/educsci9010065

Klaharn, R. (2017). The Need Assessment for Improving the Competence of Thai Teachers in the Measurement and Evaluation of Analytical Thinking. PUPIL: International Journal of Teaching, Education and Learning, 1(2), 1-16. https://doi.org/10.20319/pijtel.2017.12.116

Nurmi, H. (1981). Approaches to collective decision making with fuzzy preference relations. Fuzzy Sets and Systems, 6, 249-259. https://doi.org/10.1016/0165-0114(81)90003-8

Panda, C. K., & Bhatnagar, R. (2020). Social Internet of Things in Agriculture: An Overview and Future Scope (317-334). In: Towards Social Internet of Things. Enabling Technologies Architectures and Applications, Studies in Computational Intelligence, 846. Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-24513-9_18

Saido, G. A. M., Siraj, S., DeWitt, D., & Al-Amedy, O. S. (2018). Development of an instructional model for higher order thinking in science among secondary school students: a fuzzy Delphi approach. International journal of science education, 40(8), 847-866 https://doi.org/10.1080/09500693.2018.1452307

Sansalvador, M. E., & Brotons, J. M. (2018). Development of a quantification model for the cost of loss of image with customer complaints. Total Quality Management & Business Excellence, 29 (13-14), 1633-1647. https://doi.org/10.1080/14783363.2017.1289815

SEFI (European Society for Engineering Education) (2002). 30th Annual Conference on: The Renaissance Engineer of Tomorrow, Firenze, Italy. Publisher: T. Hedberg. ISNB: 8883044797. 163 p.

Sorrosal, M. T., Barberà, G., Fernández, A., Garbajosa, M. J. (2012): Advantages of using self-organizing maps to analyse student evaluations of teaching. Fuzzy economic review, 17(1), 53-72 https://doi.org/10.25102/fer.2012.01.03

Terceño-Gomez, A., Brotons-Martinez, J. M., & Trigueros-Pina, J. A. (2009). Evaluation of water needs in Spain, Hydraulic Engineering in Mexico, vol. XXIV(, no. 4), pp., 5-21.

Tong, K.H., Nguyen, Q. L. H. T. T., Nguyen, T. T. M., & Nguyen, P. T., Vu, N. B. (2020). Applying the Fuzzy Decision-Making Method for Program Evaluation and Management Policy of Vietnamese Higher Education, Journal of asian finance economics and business, 9(7) 719-726 https://doi.org/10.13106/jafeb.2020.vol7.no9.719

Vallory, E. (2020). Change paradigm in the University. https://www.eldiario.es/opinion/tribuna-abierta/cambio-paradigma-universidad_129_1085961.html

Yu, Y., & Tang, Y. (2020). The construction of hierarchical network model and wireless activation diffusion optimization model in English teaching. Eurasip journal on wireless communications and networking, 2020(1). https://doi.org/10.1186/s13638-020-01710-8

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Published

2020-11-13

How to Cite

Brotons Martínez, J. M., Puerto Molina , H., & Cámara Zapata , J. M. (2020). ORDERING THE MOST RELEVANT SKILLS IN AN ENGINEERING DEGREE USING FUZZY LOGIC. A CASE STUDY . PUPIL: International Journal of Teaching, Education and Learning, 4(3), 14–27. https://doi.org/10.20319/pijtel.2020.43.1427