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Fuzzy decision analysis for regional contextualization of global educational frameworks

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Abstract

The main aim of this research work is to identify a suitable educational framework, which can be implemented in the institutions of a specific region, so as to reform their educational system in a contextualized way. It is proposed to investigate the impact of unpredictable events on the instructional methodologies adopted by the globally accepted educational frameworks, by perceiving experts’ opinion in linguistic terms, thus formulating a fuzzy decision matrix to derive the fuzzy set of alternatives. Expert opinions are gathered based on the cost, quality of education, and learning outcomes independently with respect to each imprecise event and the methodology to be considered. The educational framework that adopts the instructional methodology which has the highest grade of membership in the derived fuzzy set of alternatives, shall be considered for implementing educational reformation in the institutions of a specific region to match the global competency with respect to desirable graduate attributes. Fuzzy statistical methods have been applied to verify the closeness of the derived fuzzy set of alternatives towards making appropriate decisions. Fuzzy Hurwicz Rule is applied to balance the decision due to optimistic or pessimistic views of the experts about the imprecise events.

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References

  1. Crawley E F, Malmqvist J, Ostlund S and Brodeur D R 2007 Rethinking Engineering Education, The CDIO Approach. Springer

    Google Scholar 

  2. Kamp A and Klaassen R 2016 Impact of global forces and empowering situations on engineering education in 2030. In: Proceedings of the 12th International CDIO Conference, Turku University of Applied Sciences, Turku, Finland

  3. Crawley E F, Malmqvist J, Lucas W A and Brodeur D R 2011 The CDIO syllabus v2.0 an updated statement of goals for engineering education. In: Proceedings of the 7th International CDIO Conference, Technical University of Denmark, Copenhagen

  4. The Twente Education Model 2017 Website: www.utwente.nl/tom

  5. Graham R 2018 The Global State of the Art in Engineering Education. Massachusetts Institute of Technology (MIT)

    Google Scholar 

  6. TU/e Strategy 2030—Drivers for Change, Eindhoven University of Technology 2018 Website: https://www.tue.nl/en/news/news-overview/03-09-2018-tue-launches-strategy-2030/

  7. Schleicher A 2018 The Future of Education and Skills 2030 OECD. Website: https://www.oecd.org/education/2030/

  8. Pepin B 2018 Challenges for Engineering Educators. Website: https://4tucee.weblog.tudelft.nl/

  9. Edström K and Kolmos A 2012 Comparing two approaches for engineering education development: PBL and CDIO. In: Proceedings of the 8th International CDIO Conference, Queensland University of Technology, Brisbane

  10. Crawley E F, Hosoi A P and Mitra A B 2018 Redesigning undergraduate engineering education at MIT—the new engineering education transformation (NEET) initiative. In: American Society for Engineering Education Annual Conference and Exposition

  11. Piironen A, Ikonen A, Saurén K and Lankinen P 2009 Challenge based learning in engineering education. In: Proceedings of the 5th International CDIO Conference, Singapore Polytechnic, Singapore

  12. Radberg K L, Lundqvist U, Malmqvist J and Svensson O H 2018 From CDIO to Challenge-based learning experiences—Expanding student learning as well as societal impact? European Journal of Engineering Education. https://doi.org/10.1080/03043797.2018.1441265.

    Article  Google Scholar 

  13. Biggs J 2003 Aligning Teaching for Constructing Learning. The Higher Education Academy

  14. Katehi L, Pearson G and Feder M 2009 Engineering in K-12 Education: Understanding the Status and Improving the Prospects, National Academy of Engineering and National Research Council

  15. Punyabukkana P, Orisoon A, Gangwanpongpun K, Ousirimaneechai N, Sratthatad N, Saereeporncharenkul N, Intasen P, Aukkarapuntouch P, Kasuwan S, Ananthothai T and Jaktheerangkoon S 2017 Teaching methods in engineering education: a case study in Thailand. The Social Sciences 12(1): 89–95. https://doi.org/10.3923/sscience.2017.89.95

    Article  Google Scholar 

  16. Kontio J 2015 Active learning—an introductory workshop. In: Proceedings of the 11th International CDIO Conference, Chengdu University of Information Technology, Sichuan, P.R. China

  17. Braack M, Rouwenhorst C and Slotman K M J 2015 Active learning and ICT in TEM. In: International Joint Conference on the Learner in Engineering Education/ALE

  18. Sale D and Cheah S 2017 Pedagogy for evidence-based flipped classroom—Part 1: framework. In: Proceedings of the 13th International CDIO Conference, University of Calgary, Canada

  19. Bruniges M 2005 An evidence-based approach to teaching and learning. Australian Council for Educational Research (ACEReSearch). Website: https://research.acer.edu.au/research_conference_2005/15

  20. Abdulwahed M 2017 Technology innovation and engineering’ education and entrepreneurship (TIEE) in engineering schools: novel model for elevating national knowledge based economy and socio-economic sustainable development. Sustainability, MDPI. https://doi.org/10.3390/su9020171

    Article  Google Scholar 

  21. Hadley G 1967 Introduction to probability and statistical decision theory. Holden—Day

  22. Raiffa H and Schlaifer R 1965 Applied Statistical Decision Theory. Harvard University Press

    MATH  Google Scholar 

  23. Ramachandran V 1990 Fuzzy Concepts Applied to Statistical Decision Making Methods, pp. 12–39. Website: shodhganga.inflibnet.ac.in/bitstream/10603/76918/9/09_Chapter 2

  24. Ramachandran V and Sankaranarayanan V 1991 Fuzzy concepts applied to statistical decision making methods. In: 15th IFIP International Conference on System Modelling and Optimization, Zurich, Switzerland

  25. Dhar S B 1979 Power system long-range decision analysis under fuzzy environment. IEEE Transactions on Power Apparatus and Systems. 98(2): 585–596

    Article  Google Scholar 

  26. McLoone S C 2012 On using fuzzy logic for grading highly subjective assessment material—a case study. In: 18th International Ship and Offshore Structures Congress (ISSC), NUI Maynooth

  27. Michael G and Voskoglou, 2015 Use of the triangular fuzzy numbers for student assessment. American Journal of Applied Mathematics and Statistics. 3(4): 146–150

    Google Scholar 

  28. Zadeh L A 1965 Fuzzy sets. Inf. Control 8: 338–353

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, 625 701, India

    V Saranya, S Kalyani & V Ramachandran

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  1. V Saranya
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  2. S Kalyani
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  3. V Ramachandran
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Correspondence to V Saranya.

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Saranya, V., Kalyani, S. & Ramachandran, V. Fuzzy decision analysis for regional contextualization of global educational frameworks. Sādhanā 46, 92 (2021). https://doi.org/10.1007/s12046-021-01616-1

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  • DOI: https://doi.org/10.1007/s12046-021-01616-1

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