A Fuzzy-based Decision Support Tool for Engineering Curriculum Design

  • Octavian Bologa
  • Radu Eugen Breaz
  • Gabriel Sever Racz


This paper describes a decision support tool which can be used for aiding the academic sraff in making the decision of including a specialty subject in an engineering curriculum. The approach is based on building a list of competences that should be acquired through the study of the specialty subjects. An evaluation of the competences is made by means of questionnaires and finally, a fuzzy model will be run. The output of the fuzzy model reflects the need for the evaluated specialty subject to be included in the curriculum. The proposed method takes into consideration the opinions and experience of both the academic staff and the employers.

Author Biography

Octavian Bologa
Associate Editor in Chief of IJCCCRector of Agora University


[1] National Science Foundation (1996), Shaping the future: New expectations for undergraduate education in science, mathematics, engineering and technology, Report NSF 96-139, Washington DC.

[2] Ellstrom P. (1997), The many meaning of occupational competence and qualification, Journal of European Industrial Training, 21(6): 266-273.

[3] Sanchez J.(2010), University training for competency of sustainability practitioner. Its impact on intention of creation, Springer Science + Bussines Media.

[4] Sanchez J. (2010), University training for entrepreneurial competences. Its impact on in- tention of venture creation, International Entrepreneurship and Management Journal, 7: 239-254.

[5] Nab J. et al. (2010), Authentic competence-based learning in university education in en- trepreneurship, International Journal of Entrepreneurship and Small Business, 9(11):20-35.

[6] Pearce H.T. (1997), Flexibility in the engineering curriculum: a vital component for the Future, Proc. of the National Seminar on Engineering Education, South Africa, University of Cape Town, 27-28 September 1997, 198-206.

[7] Mulder M. et al. (20009), The new competence concept in higher education: error or en- richment, Journal of European Industrial Training, 33(8/9): 755-770.

[8] Khairul A., Qiang S. (2006), Data-Driven Fuzzy Rule Generation and its Application for Student Academic Performance Evaluation, Journal of Applied Intelligence, 25: 305-319.

[9] Bai S.M., Chen S.M. (2008); Evaluating students' learning achievement using fuzzy mem- bership functions and fuzzy rules, IEEE Expert Systems with Applications, 34(1): 399-410.

[10] Chen S.M., Lee C.H. (1999), New methods for students' evaluating using fuzzy sets, Fuzzy Sets and systems, 104(2): 209-218.

[11] Ma J., Zhou D. (2000), Fuzzy set approach to the assessment of student-centered learning, IEEE Transaction on Education, 2:237-241.

[12] Cavus N. (2010), The evaluation of Learning Management systems using an artificial intel- ligence fuzzy logic algorithm, Advances in Engineering Software, 41:248-254.

[13] Chang L.T., Hong C.M., Shih C.H. (1996); An Application of Fuzzy Theory to Technical Competency Analysis for the Entry-Level Electronic Technician, Intl. Fuzzy Systems and Intelligent Control Conference, Louisville KY, USA, April 8-10, 1-11.

[14] Bologa O., Beck W., Schupp P., Breaz R., Racz G., Ionescu F. (2009); A decision algorithm for optimizing the specialty curricula in machine tools and production systems engineer- ing studies, 5th Balkan Region Conference on Engineering and Business Education & 2nd International Conference on Engineering and Business Education, Sibiu, Romania, 15 - 17 October, 330-335.

[15] Beck W., Schupp P., Bologa O., Breaz R., Racz G., Ionescu F. (2010); Mathematical Model for Aiding the Decision of Changing the Curriculum for Higher Education in the Industrial Engineering Domain, ICERI 2010 Intl. Conf. of Education, Research and Innovation, 15-17 November, Madrid, Spain, 6535-6542.
How to Cite
BOLOGA, Octavian; BREAZ, Radu Eugen; RACZ, Gabriel Sever. A Fuzzy-based Decision Support Tool for Engineering Curriculum Design. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 10, n. 6, p. 43-51, oct. 2015. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/2071>. Date accessed: 06 aug. 2020. doi: https://doi.org/10.15837/ijccc.2015.6.2071.


curriculum design, decision support engineering studies, fuzzy logic