Ranking the Criteria Effective in the Selection of E-Learning System by Fuzzy AHP (F-AHP) Method
Year 2023,
Volume: 16 Issue: 4, 749 - 768, 29.10.2023
Yasemin Sönmez Gümüşhan
,
Fatma Sönmez Çakır
Abstract
E-learning systems are one of the effective methods used for education. It is obvious that both during the Pandemic period when distance education is actively used and in normal life, participants apply to e-learning systems to follow lessons or improve themselves. Computer and internet applications are getting into education more and more day by day. Education through e-learning, which can work online or offline, is more and more effective every day. Thanks to these systems, education becomes more transparent, accessible and fairly distributed. Since many criteria will have an impact on the selection of a suitable e-learning system, these criteria were determined in the study and presented to expert opinions. In the selection of e-learning systems, 10 criteria were selected by literature review and the criteria were conveyed to the experts. The criteria were listed using the fuzzy AHP method. The most effective criterion in the study was found to be interaction. This criterion is followed by ease of use, content and reliability criteria.
References
- Abdel-Gawad, T., & Woollard, J. (2015). Critical success factors for implementing classless e-learning systems in the Egyptian higher education. International Journal of Instructional Technology and Distance Learning, 12(4), 29-36.
- Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: the challenges and opportunities. Interactive Learning Environments, 1-13. https://doi.org/10.1080/10494820.2020.1813180
- Alhabeeb, A., & Rowley, J. (2018). E-learning critical success factors: Comparing perspectives from academic staff and students. Computers & Education, 127, 1-12.
- Alias, N., Zakariah, Z., Ismail, N. Z., & Abd Aziz, M. N. (2012). E-Learning successful elements for higher learning institution in Malaysia. Procedia-Social and Behavioral Sciences, 67, 484-489.
- Alojaiman, B. (2021). Toward selection of trustworthy and efficient e-Learning platform. IEEE Access, 9, 133889-133901.
- Anggrainingsih, R., Umam, M. Z., & Setiadi, H. (2018). Determining e-learning success factor in higher education based on user perspective using Fuzzy AHP. In MATEC web of conferences (Vol. 154, p. 03011). EDP Sciences.
- Atıcı, U., Adem, A., Şenol, M. B., & Dağdeviren, M. (2022). A comprehensive decision framework with interval valued type-2 fuzzy AHP for evaluating all critical success factors of e-learning platforms. Education and Information Technologies, 27(5), 5989-6014. https://doi.org/10.1007/s10639-021-10834-3
- Azlan, C. A., Wong, J. H. D., Tan, L. K., Huri, M. S. N. A., Ung, N. M., Pallath, V., ... & Ng, K. H. (2020). Teaching and learning of postgraduate medical physics using Internet-based e-learning during the COVID-19 pandemic–A case study from Malaysia. Physica Medica, 80, 10-16.
- Chan, F. T., Kumar, N., Tiwari, M. K., Lau, H. C., & Choy, K. (2008). Global supplier selection: a fuzzy-AHP approach. International Journal of Production Research, 46(14), 3825-3857.
- Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655.
- Chao, R. J., & Chen, Y. H. (2009). Evaluation of the criteria and effectiveness of distance e-learning with consistent fuzzy preference relations. Expert Systems with Applications, 36(7), 10657-10662.
- Chelvarayan, A., Chee, J. E., Yoe, S. F., & Hashim, H. (2020). Students’ perceptions on mobile learning: The influencing factors. International Journal of Education Psychology and Counselling, 5(37), 1-9.
- Chou, Y. C., Yen, H. Y., Dang, V. T., & Sun, C. C. (2019). Assessing the human resource in science and technology for Asian countries: Application of Fuzzy AHP and Fuzzy TOPSIS. Symmetry, 11(2), 251-267.
- Comprehensive Learning Management System Market Report and Trends. (2021): Retrieved from: https://www.vedubox.com/wp-content/uploads/2021/05/LMS-Market-Report-2021.pdf Date: 17.11.2022
- Covella, G. J., & Olsina Santos, L. A. (2002). Specifying quality characteristics and attributes for E-Learning sites. In IV Workshop de Investigadores en Ciencias de la Computación.
- Fitriastuti, F., Rahmalisa, U., & Girsang, A. S. (2019, March). Multi-criteria decision making on successful of online learning using AHP and regression. Journal of Physics: Conference Series, 1175(1), 012071. IOP Publishing.
- Ganguly, K. K., & Guin, K. K. (2013). A fuzzy AHP approach for inbound supply risk assessment. Benchmarking: An International Journal, 20(1), 129-146. https://doi.org/10.1108/14635771311299524
- Garg, R. (2017). E‐learning website evaluation and selection using multi‐attribute decision making matrix methodology. Computer Applications in Engineering Education, 25(6), 938-947.
- Garg, R., Kumar, R., & Garg, S. (2018). MADM-based parametric selection and ranking of E-learning websites using fuzzy COPRAS. IEEE Transactions on Education, 62(1), 11-18.
- Globe news wire. (2020). Retrieved from: https://www.globenewswire.com/news-release/2020/08/18/2080347/0/en/Global-Mobile-Learning-Industry.html Date: 16.11.2022
- Gnanavelbabu, A., & Arunagiri, P. (2018). Ranking of MUDA using AHP and fuzzy AHP algorithm. Materials Today: Proceedings, 5(5), 13406-13412.
- Gong, J. W., Liu, H. C., You, X. Y., & Yin, L. (2021). An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection. Applied Soft Computing, 102, 107118.
- Güldeş, M., Gürcan, Ö. F., Atici, U., & Şahin, C. (2021). A fuzzy multi-criteria decision-making method for selection of criteria for an e-learning platform. Avrupa Bilim ve Teknoloji Dergisi, 32, 797-806.
- Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646.
- Jain, D., Garg, R., Bansal, A., & Saini, K. K. (2016). Selection and ranking of E-learning websites using weighted distance-based approximation. Journal of Computers in Education, 3(2), 193-207.
- Jaukovic Jocic, K., Jocic, G., Karabasevic, D., Popovic, G., Stanujkic, D., Zavadskas, E. K., & Thanh Nguyen, P. (2020). A novel integrated piprecia–interval-valued triangular fuzzy aras model: E-learning course selection. Symmetry, 12(6), 928.
- Khan, N. Z., Ansari, T. S. A., Siddiquee, A. N., & Khan, Z. A. (2019). Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method. Journal of Computers in Education, 6(2), 241-256.
- Kocakaya, K., Engin, T., Tektaş, M., & Aydın, U. (2021). Türkiye’de bölgesel havayollari için uçak tipi seçimi: Küresel bulanık AHP-TOPSIS yöntemlerinin entegrasyonu. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 4(1), 27-58.
- Korucuk, B. (2020). Sınıf öğretmenleri gözüyle uzaktan eğitim memnuniyet faktörlerinin derecelendirilmesi yönelik bir çalışma: Giresun ili örneği. Öğretim Teknolojisi ve Hayat Boyu Öğrenme Dergisi, 1(2), 189-202.
- Kustiyahningsih, Y., & Aini, I. Q. (2020). Integration of FAHP and COPRAS method for new student admission decision making. In 2020 Third International Conference on Vocational Education and Electrical Engineering (ICVEE) (pp. 1-6). IEEE.
- Mahalakshmi, K., & Radha, R. (2020). COVID 19: A massive exposure towards web based learning. Journal of Xidian University, 14(4), 2405-2411.
- Malik, D. A. A., Yusof, Y., & N.K. Khalif, K. M. (2021). A view of MCDM application in education. Journal of Physics: Conference Series, 1988(1), 012063). IOP Publishing.
- Mangla, S. K., Kumar, P., & Barua, M. K. (2015). Risk analysis in green supply chain using fuzzy AHP approach: A case study. Resources, Conservation and Recycling, 104, 375-390.
- Männistö, M., Mikkonen, K., Kuivila, H. M., Koskinen, C., Koivula, M., Sjögren, T., ... & Kääriäinen, M. (2020). Health and social care educators’ competence in digital collaborative learning: A cross-sectional survey. Sage Open, 10(4), 2158244020962780.
- Market Research: Retrieved from: https://www.marketresearch.com/Think-Market-Intelligence-v4247/eLearning-Intelligence-Global-Forecast-31991364/ Date: 16.11.2022
- Mohammed, H. J., Kasim, M. M., & Shaharanee, I. N. (2018). Evaluation of E-learning approaches using AHP-TOPSIS technique. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-10), 7-10.
- Muhammad, A. H., Siddique, A., Youssef, A. E., Saleem, K., Shahzad, B., Akram, A., & Al-Thnian, A. B. S. (2020). A hierarchical model to evaluate the quality of web-based e-learning systems. Sustainability, 12(10), 4071.
- Naveed, Q. N., Qureshi, M. R. N., Tairan, N., Mohammad, A., Shaikh, A., Alsayed, A. O., ... & Alotaibi, F. M. (2020). Evaluating critical success factors in implementing E-learning system using multi-criteria decision-making. Plos One, 15(5), e0231465.
- NCES (2019). Number and percentage of students enrolled in degree-granting postsecondary institutions, by distance education participation, location of student, level of enrollment, and control and level of institution: Fall 2019 and fall 2020. Retrieved from https://nces.ed.gov/programs/digest/d21/tables/dt21_311.15.asp Date: 16.11.2022
- Panda, A., & Pal, M. (2015). A study on pentagonal fuzzy number and its corresponding matrices. Pacific Science Review B: Humanities and Social Sciences, 1(3), 131-139.
- Prougestaporn, P., Visansakon, T., & Saowapakpongchai, K. (2015). Key success factors and evaluation criterias of e-learning websites for higher education. International Journal of Information and Education Technology, 5(3), 233.
- Pruengkarn, R., Praneetpolgrang, P., & Srivihok, A. (2005, July). An evaluation model for e-learning Websites in Thailand University. In Fifth IEEE International Conference on Advanced Learning Technologies (ICALT’05) (pp. 161-162). IEEE.
- Shaverdi, M., Heshmati, M. R., & Ramezani, I. (2014). Application of fuzzy AHP approach for financial performance evaluation of Iranian petrochemical sector. Procedia Computer Science, 31, 995-1004.
- Shee, D. Y., & Wang, Y. S. (2008). Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications. Computers & Education, 50(3), 894-905.
- Siew, L. W., Hoe, L. W., Fai, L. K., Bakar, M. A., & Xian, S. J. (2021). Analysis on the e-Learning Method in Malaysia with AHP-VIKOR Model. International Journal of Information and Education Technology, 11(2), 52-58.
- Sönmez Çakır, F., & Pekkaya, M. (2020). Determination of interaction between criteria and the criteria priorities in laptop selection problem. International Journal of Fuzzy Systems, 22(4), 1177-1190.
- Soong, M. B., Chan, H. C., Chua B. C., & Loh, K. F. (2001). Critical success factors for on-line course. Computers & Education, 36(2), 101-120. https://doi.org/10.1016/S0360-1315(00)00044-0
- Syamsuddin, I. (2012). Fuzzy multi criteria evaluation framework for E-learning software quality. Academic Research International, 2(1), 139-147.
- Taha, M. (2014). Investigating the success of E-learning in secondary schools: The case of the Kingdom of Bahrain [Doctoral dissertation]. Brunel University London.
- Toan, P. N., Dang, T. T., & Hong, L. T. T. (2021). E-learning platform assessment and selection using two-stage multi-criteria decision-making approach with grey theory: A case study in Vietnam. Mathematics, 9(23), 3136.
- Tudor Car, L., Kyaw, B. M., & Atun, R. (2018). The role of eLearning in health management and leadership capacity building in health system: a systematic review. Human Resources for Health, 16(1), 1-9.
- Wang, Y., Xu, L., & Solangi, Y. A. (2020). Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustainable Cities and Society, 52, 101861.
- Wirani, N., & Manurung, A. A. (2020). The importance of using a web-based learning model to prevent the spread of covid 19. Al’adzkiya International of Education and Sosial (AIoES) Journal, 1(1), 16-24.
- World Economic Forum: Retrieved from: https://www.weforum.org/agenda/2020/04/coronavirus-education-global-covid19-online-digital-learning/ Date: 17.11.2022
- Zadeh, L.A., 1965. Fuzzy sets. Information and Control, 8(3), 338–353.
- Zare, M., Pahl, C., Rahnama, H., Nilashi, M., Mardani, A., Ibrahim, O., & Ahmadi, H. (2016). Multi-criteria decision making approach in E-learning: A systematic review and classification. Applied Soft Computing, 45, 108-128.
E-Öğrenme Sistemi Seçiminde Etkili Kriterlerin Bulanık AHP (F-AHP) Yöntemiyle Sıralanması
Year 2023,
Volume: 16 Issue: 4, 749 - 768, 29.10.2023
Yasemin Sönmez Gümüşhan
,
Fatma Sönmez Çakır
References
- Abdel-Gawad, T., & Woollard, J. (2015). Critical success factors for implementing classless e-learning systems in the Egyptian higher education. International Journal of Instructional Technology and Distance Learning, 12(4), 29-36.
- Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: the challenges and opportunities. Interactive Learning Environments, 1-13. https://doi.org/10.1080/10494820.2020.1813180
- Alhabeeb, A., & Rowley, J. (2018). E-learning critical success factors: Comparing perspectives from academic staff and students. Computers & Education, 127, 1-12.
- Alias, N., Zakariah, Z., Ismail, N. Z., & Abd Aziz, M. N. (2012). E-Learning successful elements for higher learning institution in Malaysia. Procedia-Social and Behavioral Sciences, 67, 484-489.
- Alojaiman, B. (2021). Toward selection of trustworthy and efficient e-Learning platform. IEEE Access, 9, 133889-133901.
- Anggrainingsih, R., Umam, M. Z., & Setiadi, H. (2018). Determining e-learning success factor in higher education based on user perspective using Fuzzy AHP. In MATEC web of conferences (Vol. 154, p. 03011). EDP Sciences.
- Atıcı, U., Adem, A., Şenol, M. B., & Dağdeviren, M. (2022). A comprehensive decision framework with interval valued type-2 fuzzy AHP for evaluating all critical success factors of e-learning platforms. Education and Information Technologies, 27(5), 5989-6014. https://doi.org/10.1007/s10639-021-10834-3
- Azlan, C. A., Wong, J. H. D., Tan, L. K., Huri, M. S. N. A., Ung, N. M., Pallath, V., ... & Ng, K. H. (2020). Teaching and learning of postgraduate medical physics using Internet-based e-learning during the COVID-19 pandemic–A case study from Malaysia. Physica Medica, 80, 10-16.
- Chan, F. T., Kumar, N., Tiwari, M. K., Lau, H. C., & Choy, K. (2008). Global supplier selection: a fuzzy-AHP approach. International Journal of Production Research, 46(14), 3825-3857.
- Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655.
- Chao, R. J., & Chen, Y. H. (2009). Evaluation of the criteria and effectiveness of distance e-learning with consistent fuzzy preference relations. Expert Systems with Applications, 36(7), 10657-10662.
- Chelvarayan, A., Chee, J. E., Yoe, S. F., & Hashim, H. (2020). Students’ perceptions on mobile learning: The influencing factors. International Journal of Education Psychology and Counselling, 5(37), 1-9.
- Chou, Y. C., Yen, H. Y., Dang, V. T., & Sun, C. C. (2019). Assessing the human resource in science and technology for Asian countries: Application of Fuzzy AHP and Fuzzy TOPSIS. Symmetry, 11(2), 251-267.
- Comprehensive Learning Management System Market Report and Trends. (2021): Retrieved from: https://www.vedubox.com/wp-content/uploads/2021/05/LMS-Market-Report-2021.pdf Date: 17.11.2022
- Covella, G. J., & Olsina Santos, L. A. (2002). Specifying quality characteristics and attributes for E-Learning sites. In IV Workshop de Investigadores en Ciencias de la Computación.
- Fitriastuti, F., Rahmalisa, U., & Girsang, A. S. (2019, March). Multi-criteria decision making on successful of online learning using AHP and regression. Journal of Physics: Conference Series, 1175(1), 012071. IOP Publishing.
- Ganguly, K. K., & Guin, K. K. (2013). A fuzzy AHP approach for inbound supply risk assessment. Benchmarking: An International Journal, 20(1), 129-146. https://doi.org/10.1108/14635771311299524
- Garg, R. (2017). E‐learning website evaluation and selection using multi‐attribute decision making matrix methodology. Computer Applications in Engineering Education, 25(6), 938-947.
- Garg, R., Kumar, R., & Garg, S. (2018). MADM-based parametric selection and ranking of E-learning websites using fuzzy COPRAS. IEEE Transactions on Education, 62(1), 11-18.
- Globe news wire. (2020). Retrieved from: https://www.globenewswire.com/news-release/2020/08/18/2080347/0/en/Global-Mobile-Learning-Industry.html Date: 16.11.2022
- Gnanavelbabu, A., & Arunagiri, P. (2018). Ranking of MUDA using AHP and fuzzy AHP algorithm. Materials Today: Proceedings, 5(5), 13406-13412.
- Gong, J. W., Liu, H. C., You, X. Y., & Yin, L. (2021). An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection. Applied Soft Computing, 102, 107118.
- Güldeş, M., Gürcan, Ö. F., Atici, U., & Şahin, C. (2021). A fuzzy multi-criteria decision-making method for selection of criteria for an e-learning platform. Avrupa Bilim ve Teknoloji Dergisi, 32, 797-806.
- Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646.
- Jain, D., Garg, R., Bansal, A., & Saini, K. K. (2016). Selection and ranking of E-learning websites using weighted distance-based approximation. Journal of Computers in Education, 3(2), 193-207.
- Jaukovic Jocic, K., Jocic, G., Karabasevic, D., Popovic, G., Stanujkic, D., Zavadskas, E. K., & Thanh Nguyen, P. (2020). A novel integrated piprecia–interval-valued triangular fuzzy aras model: E-learning course selection. Symmetry, 12(6), 928.
- Khan, N. Z., Ansari, T. S. A., Siddiquee, A. N., & Khan, Z. A. (2019). Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method. Journal of Computers in Education, 6(2), 241-256.
- Kocakaya, K., Engin, T., Tektaş, M., & Aydın, U. (2021). Türkiye’de bölgesel havayollari için uçak tipi seçimi: Küresel bulanık AHP-TOPSIS yöntemlerinin entegrasyonu. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 4(1), 27-58.
- Korucuk, B. (2020). Sınıf öğretmenleri gözüyle uzaktan eğitim memnuniyet faktörlerinin derecelendirilmesi yönelik bir çalışma: Giresun ili örneği. Öğretim Teknolojisi ve Hayat Boyu Öğrenme Dergisi, 1(2), 189-202.
- Kustiyahningsih, Y., & Aini, I. Q. (2020). Integration of FAHP and COPRAS method for new student admission decision making. In 2020 Third International Conference on Vocational Education and Electrical Engineering (ICVEE) (pp. 1-6). IEEE.
- Mahalakshmi, K., & Radha, R. (2020). COVID 19: A massive exposure towards web based learning. Journal of Xidian University, 14(4), 2405-2411.
- Malik, D. A. A., Yusof, Y., & N.K. Khalif, K. M. (2021). A view of MCDM application in education. Journal of Physics: Conference Series, 1988(1), 012063). IOP Publishing.
- Mangla, S. K., Kumar, P., & Barua, M. K. (2015). Risk analysis in green supply chain using fuzzy AHP approach: A case study. Resources, Conservation and Recycling, 104, 375-390.
- Männistö, M., Mikkonen, K., Kuivila, H. M., Koskinen, C., Koivula, M., Sjögren, T., ... & Kääriäinen, M. (2020). Health and social care educators’ competence in digital collaborative learning: A cross-sectional survey. Sage Open, 10(4), 2158244020962780.
- Market Research: Retrieved from: https://www.marketresearch.com/Think-Market-Intelligence-v4247/eLearning-Intelligence-Global-Forecast-31991364/ Date: 16.11.2022
- Mohammed, H. J., Kasim, M. M., & Shaharanee, I. N. (2018). Evaluation of E-learning approaches using AHP-TOPSIS technique. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-10), 7-10.
- Muhammad, A. H., Siddique, A., Youssef, A. E., Saleem, K., Shahzad, B., Akram, A., & Al-Thnian, A. B. S. (2020). A hierarchical model to evaluate the quality of web-based e-learning systems. Sustainability, 12(10), 4071.
- Naveed, Q. N., Qureshi, M. R. N., Tairan, N., Mohammad, A., Shaikh, A., Alsayed, A. O., ... & Alotaibi, F. M. (2020). Evaluating critical success factors in implementing E-learning system using multi-criteria decision-making. Plos One, 15(5), e0231465.
- NCES (2019). Number and percentage of students enrolled in degree-granting postsecondary institutions, by distance education participation, location of student, level of enrollment, and control and level of institution: Fall 2019 and fall 2020. Retrieved from https://nces.ed.gov/programs/digest/d21/tables/dt21_311.15.asp Date: 16.11.2022
- Panda, A., & Pal, M. (2015). A study on pentagonal fuzzy number and its corresponding matrices. Pacific Science Review B: Humanities and Social Sciences, 1(3), 131-139.
- Prougestaporn, P., Visansakon, T., & Saowapakpongchai, K. (2015). Key success factors and evaluation criterias of e-learning websites for higher education. International Journal of Information and Education Technology, 5(3), 233.
- Pruengkarn, R., Praneetpolgrang, P., & Srivihok, A. (2005, July). An evaluation model for e-learning Websites in Thailand University. In Fifth IEEE International Conference on Advanced Learning Technologies (ICALT’05) (pp. 161-162). IEEE.
- Shaverdi, M., Heshmati, M. R., & Ramezani, I. (2014). Application of fuzzy AHP approach for financial performance evaluation of Iranian petrochemical sector. Procedia Computer Science, 31, 995-1004.
- Shee, D. Y., & Wang, Y. S. (2008). Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications. Computers & Education, 50(3), 894-905.
- Siew, L. W., Hoe, L. W., Fai, L. K., Bakar, M. A., & Xian, S. J. (2021). Analysis on the e-Learning Method in Malaysia with AHP-VIKOR Model. International Journal of Information and Education Technology, 11(2), 52-58.
- Sönmez Çakır, F., & Pekkaya, M. (2020). Determination of interaction between criteria and the criteria priorities in laptop selection problem. International Journal of Fuzzy Systems, 22(4), 1177-1190.
- Soong, M. B., Chan, H. C., Chua B. C., & Loh, K. F. (2001). Critical success factors for on-line course. Computers & Education, 36(2), 101-120. https://doi.org/10.1016/S0360-1315(00)00044-0
- Syamsuddin, I. (2012). Fuzzy multi criteria evaluation framework for E-learning software quality. Academic Research International, 2(1), 139-147.
- Taha, M. (2014). Investigating the success of E-learning in secondary schools: The case of the Kingdom of Bahrain [Doctoral dissertation]. Brunel University London.
- Toan, P. N., Dang, T. T., & Hong, L. T. T. (2021). E-learning platform assessment and selection using two-stage multi-criteria decision-making approach with grey theory: A case study in Vietnam. Mathematics, 9(23), 3136.
- Tudor Car, L., Kyaw, B. M., & Atun, R. (2018). The role of eLearning in health management and leadership capacity building in health system: a systematic review. Human Resources for Health, 16(1), 1-9.
- Wang, Y., Xu, L., & Solangi, Y. A. (2020). Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustainable Cities and Society, 52, 101861.
- Wirani, N., & Manurung, A. A. (2020). The importance of using a web-based learning model to prevent the spread of covid 19. Al’adzkiya International of Education and Sosial (AIoES) Journal, 1(1), 16-24.
- World Economic Forum: Retrieved from: https://www.weforum.org/agenda/2020/04/coronavirus-education-global-covid19-online-digital-learning/ Date: 17.11.2022
- Zadeh, L.A., 1965. Fuzzy sets. Information and Control, 8(3), 338–353.
- Zare, M., Pahl, C., Rahnama, H., Nilashi, M., Mardani, A., Ibrahim, O., & Ahmadi, H. (2016). Multi-criteria decision making approach in E-learning: A systematic review and classification. Applied Soft Computing, 45, 108-128.