Research Article
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EVALUATION OF LEARNING MANAGEMENT SYSTEMS USING INTERVAL VALUED INTUITIONISTIC FUZZY-Z NUMBERS

Year 2023, Volume: 24 Issue: 4, 179 - 206, 01.10.2023
https://doi.org/10.17718/tojde.1170338

Abstract

The use of online education tools has increased rapidly with the transition to distance education caused by the pandemic. The obligation to carry out all activities of face-to-face education online made it very important for the tools used in distance education to meet the increasing needs. In line with these needs, radical changes have occurred in the learning management systems used in distance education. Therefore, in this study, it is aimed to determine the features that the systems used in distance education should have and to compare the existing systems according to these features. For this purpose, a novel fuzzy extension, interval valued intuitionistic fuzzy Z-numbers, is defined for modeling uncertainty, and AHP and WASPAS methods using proposed fuzzy numbers are developed to determine the importance of decision criteria and compare alternatives.

References

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Year 2023, Volume: 24 Issue: 4, 179 - 206, 01.10.2023
https://doi.org/10.17718/tojde.1170338

Abstract

References

  • Abdel-Basset, M., Mohamed, M., Zhou, Y., & Hezam, I. (2017). Multi-criteria group decision making based on neutrosophic analytic hierarchy process. Journal of Intelligent & Fuzzy Systems, 33(6), 4055-4066.
  • Abdullah, L., & Najib, L. (2014a). A new preference scale of intuitionistic fuzzy analytic hierarchy process in multi-criteria decision making problems. Journal of Intelligent & Fuzzy Systems, 26(2), 1039-1049.
  • Abdullah, L., & Najib, L. (2014b). Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia. International Journal of Sustainable Energy, 35(4), 360-377.
  • Abdullah, L., & Najib, L. (2017). Interval Type-2 fuzzy analytic hierarchy process for sustainable energy sources selection. International Journal of Fuzzy System Applications (IJFSA), 6(3), 124-137.
  • Abdullah, L., Sunadia, J., & Imran, T. (2009). A new analytic hierarchy process in multi-attribute group decision making. International Journal of Soft Computing, 4(5), 208-214.
  • Al-Ajlan, A. S. (2012). A comparative study between e-learning features. Methodologies, tools and new developments for e-learning, 191-214.
  • Altıparmak, M., Kurt, İ. D., & Kapıdere, M. (2011). E-öğrenme ve uzaktan eğitimde açık kaynak kodlu öğrenme yönetim sistemleri. XI. Akademik Bilişim Kongresi.
  • Azadeh, A., Saberi, M., Atashbar, N. Z., Chang, E., & Pazhoheshfar, P. (2013, July). Z-AHP: A Z-number extension of fuzzy analytical hierarchy process. In 2013 7th IEEE International Conference on Digital Ecosystems and Technologies (DEST) (pp. 141-147). IEEE.
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  • BAHÇECİ, F., & YILDIZ, E. (2016). Yetişkin eğitimindeki bireylerin öğrenme yönetim sistemleri hakkındaki görüşleri. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 2(1), 94-113.
  • Bezovski, Z., & Poorani, S. (2016, March). The evolution of e-learning and new trends. In Information and Knowledge Management (Vol. 6, No. 3, pp. 50-57). IISTE.
  • BİÇER, H., & KORUCU, A. T. (2020). E-ÖĞRENMEYE YÖNELİK TUTUM ÖLÇEĞİNİN TÜRKÇEYE UYARLANMASI. Eğitim Teknolojisi Kuram ve Uygulama, 10(1), 237-256.
  • Bilgic, H. G., & Tuzun, H. (2020). Issues and Challenges in Web-Based Distance Education Programs in Turkish Higher Education Institutes. Turkish Online Journal of Distance Education, 21(1), 143-164.
  • Boender, C. G. E., De Graan, J. G., & Lootsma, F. A. (1989). Multi-criteria decision analysis with fuzzy pairwise comparisons. Fuzzy sets and Systems, 29(2), 133-143.
  • Boltürk, E., & Kahraman, C. (2018). A novel interval-valued neutrosophic AHP with cosine similarity measure. Soft Computing, 22(15), 4941-4958.
  • Boltürk, E., & Kahraman, C. (2019, July). As/RS technology selection using interval-valued pythagorean fuzzy WASPAS. In International Conference on Intelligent and Fuzzy Systems (pp. 867-875). Springer, Cham.
  • Boltürk, E., Çevik Onar, S., Öztayşi, B., Kahraman, C., & Goztepe, K. (2016). Multi-attribute warehouse location selection in humanitarian logistics using hesitant fuzzy AHP. International Journal of the Analytic Hierarchy Process, 8(2), 271-298.
  • Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy sets and systems, 17(3), 233-247.
  • Cavus, N., & Zabadi, T. (2014). A comparison of open source learning management systems. Procedia-Social and Behavioral Sciences, 143, 521-526.
  • ÇETİNKAYA, V., & DEVECİ, D. A. (2020). Optimal Sürdürülebilir Rota Tespiti İçin Gerekli Göstergelerin Bir Çok Kriterli Karar Verme Yöntemi İle Önem Düzeyi Tespiti. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 12(1), 25-46.
  • Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European journal of operational research, 95(3), 649-655.
  • Chaubey, A., & Bhattacharya, B. (2015). Learning management system in Higher education. IJSTE-International Journal of Science Technology & Engineering, 2(3).
  • Cheung, K. S. (2007). A Comparison of WebCT, Blackboard and Moodle for the teaching and learning of continuing education courses. In Enhancing learning through technology (pp. 219-228).
  • Cigdem, H., & Ozturk, M. (2016). Factors affecting students’ behavioral intention to use LMS at a Turkish post-secondary vocational school. International Review of Research in Open and Distributed Learning, 17(3), 276-295.
  • Collins, A., & Halverson, R. (2018). Rethinking education in the age of technology: The digital revolution and schooling in America. Teachers College Press.
  • Dogan, O., Deveci, M., Canıtez, F., & Kahraman, C. (2019). A corridor selection for locating autonomous vehicles using an interval-valued intuitionistic fuzzy AHP and TOPSIS method. Soft Computing, 1-17.
  • Dutta, B., & Guha, D. (2015). Preference programming approach for solving intuitionistic fuzzy AHP. International Journal of Computational Intelligence Systems, 8(5), 977-991.
  • Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., ... & Raman, R. (2020). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211.
  • Ellis, R. A., Ginns, P., & Piggott, L. (2009). E‐learning in higher education: some key aspects and their relationship to approaches to study. Higher Education Research & Development, 28(3), 303-318.
  • Gowda, R. S., & Suma, V. (2017, February). A comparative analysis of traditional education system vs. e-Learning. In 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) (pp. 567-571). IEEE.
  • Gülbahar, Y. (2017). E-öğrenme. Pegem Atıf İndeksi, 1-410.
  • Gündoğdu, F. K., & Kahraman, C. (2020). A novel spherical fuzzy analytic hierarchy process and its renewable energy application. Soft Computing, 24(6), 4607-4621.
  • Han, I., & Shin, W. S. (2016). The use of a mobile learning management system and academic achievement of online students. Computers & Education, 102, 79-89.
  • Ilbahar, E., & Kahraman, C. (2018). Retail store performance measurement using a novel interval-valued Pythagorean fuzzy WASPAS method. Journal of Intelligent & Fuzzy Systems, 35(3), 3835-3846.
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There are 93 citations in total.

Details

Primary Language English
Subjects Lifelong learning
Journal Section Articles
Authors

Duygu Sergı 0000-0003-1636-0230

Irem Ucal Sarı 0000-0002-1627-612X

Publication Date October 1, 2023
Submission Date September 2, 2022
Published in Issue Year 2023 Volume: 24 Issue: 4

Cite

APA Sergı, D., & Sarı, I. U. (2023). EVALUATION OF LEARNING MANAGEMENT SYSTEMS USING INTERVAL VALUED INTUITIONISTIC FUZZY-Z NUMBERS. Turkish Online Journal of Distance Education, 24(4), 179-206. https://doi.org/10.17718/tojde.1170338