The Use of Fuzzy Linguistic Information and Fuzzy Delphi Method to Validate by Consensus a Questionnaire in a Blended-Learning Environment

  • Jeovani Morales
  • Rosana Montes
  • Noe Zermeño
  • Jeronimo Duran
  • Francisco Herrera
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 855)


The virtual learning landscapes have created complex environments when evaluating an educational experience. The Fuzzy Delphi method, which incorporates the theory of fuzzy sets, takes the opinions issued by judges, from a linguistic perspective, to validate a questionnaire that will measure the degree of success of an educational experience. The judges have to reach a consensus on the validity and applicability of the instrument. This work contributes to the validation of questionnaires by enabling linguistic assessments and not only binary answers and with a calculus of consistency and consensus degrees for each item, which contributes to consensus reaching. It has been used as a practical experience to define, with the consensus of nine experts, a questionnaire that measures the virtual communication and the satisfaction with in a Blended-Learning pilot experience in the subject of Software Fundamentals, 1st semester of the Degree in Computer Engineering of the University of Granada.


Linguistic decision making Fuzzy Delphi method B-Learning Instrument validation 



This document has been funded by the research project TIN2017-89517-P of the Ministry of Science and Innovation.


  1. 1.
    Bergmann, J., Sams, A.: Flip your classroom: reach every student in every class every day. International Society for Technology in Education, Washington, D.C. (2012)Google Scholar
  2. 2.
    Berk, R.: Importance of expert judgment in content-related validity evidence. West. J. Nurs. Res. 12(5), 659–671 (1990). Scholar
  3. 3.
    Carrasco, R.A., et al.: A linguistic multi-criteria decision making model applied to the integration of education questionnaires. Int. J. Comput. Intell. Syst. 4(5), 946–959 (2011). Scholar
  4. 4.
    Cornelius, S., Gordon, C.: Providing a flexible, learner-centred programme: challenges for educators. Internet High. Educ. 11(1), 33–41 (2008). Scholar
  5. 5.
    Dalkey, N.: An experimental study of group opinion: the delphi method. Futures 1(5), 408–426 (1969). Scholar
  6. 6.
    Dong, J., Huo, H.: Identification of financing barriers to energy efficiency in small and medium-sized enterprises by integrating the fuzzy delphi and fuzzy dematel approaches. Energies 10(8), 1172 (2017). Scholar
  7. 7.
    GarcÍa-Lira, K., Gutiérrez-Santiuste, E., Montes-Soldado, R.: Cuestionarios para la evaluacion de la comunicacion y la satisfaccion al aplicar metodologias flipped classroom combinadas con m-learning en educacion superior. In: III Congreso Internacional de Educación Mediática y Competencia Digital, pp. 1145–1163 (2017)Google Scholar
  8. 8.
    Garrison, D., Akyol, Z.: Toward the development of a metacognition construct for communities of inquiry. Internet High. Educ. 17(Suppl. C), 84–89 (2013). Scholar
  9. 9.
    Gupta, R., et al.: Selection of 3PL service provider using integrated fuzzy delphi and fuzzy topsis. In: Proceedings of the World Congress on Engineering and Computer Science, vol. 2, pp. 20–22 (2010).
  10. 10.
    Ishikawa, A., et al.: The max-min delphi method and fuzzy delphi method via fuzzy integration. Fuzzy Sets Syst. 55(3), 241–253 (1993). Scholar
  11. 11.
    Jaldemark, J., et al.: Editorial introduction: collaborative learning enhanced by mobile technologies. Br. J. Educ. Technol. 49, 201–206 (2017). Scholar
  12. 12.
    Kim, J.: Developing an instrument to measure social presence in distance higher education. Br. J. Educ. Technol. 42(5), 763–777 (2011). Scholar
  13. 13.
    Lage, M.J., et al.: Inverting the classroom: a gateway to creating an inclusive learning environment. J. Econ. Educ. 31(1), 30–43 (2000). Scholar
  14. 14.
    Lensing, S.Y., et al.: Encouraging physicians to respond to surveys through the use of fax technology. Eval. Health Prof. 23(3), 348–359 (2000). Scholar
  15. 15.
    Lin, C.: Application of fuzzy delphi method (FDM) and fuzzy analytic hierarchy process (FAHP) to criteria weights for fashion design scheme evaluation. Int. J. Clothing Sci. Technol. 25(3), 171–183 (2013). Scholar
  16. 16.
    Lynn, M.R.: Determination and quantification of content validity. Nurs. Res. 35(6), 382–386 (1986)CrossRefGoogle Scholar
  17. 17.
    Noorderhaven, N.G.: Strategic Decision Making. Addison-Wesley, Wokingham (1995)Google Scholar
  18. 18.
    Tucker, B.: The flipped classroom. Educ. Next 12(1) (2012)Google Scholar
  19. 19.
    Valtonen, T., et al.: Perspectives on personal learning environments held by vocational students. Comput. Educ. 58(2), 732–739 (2012). Scholar
  20. 20.
    Zadeh, L.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965). Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Andalusian Research Institute Data Science and Computational Intelligence, DaSCIUniversity of GranadaGranadaSpain
  2. 2.Software Engineering Department, School of Informatics and Telecommunications EngineeringUniversity of GranadaGranadaSpain
  3. 3.Computer Science and Artificial Intelligence Department, School of Informatics and Telecommunications EngineeringUniversity of GranadaGranadaSpain

Personalised recommendations