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Öğrenci Memnuniyetine Dayalı Yüz Yüze, Uzaktan ve Hibrit Eğitim Modelleri için Performans Analizi

Year 2021, Issue: 23, 254 - 271, 30.04.2021
https://doi.org/10.31590/ejosat.866479

Abstract

Öğrenme, bireye kalıcı davranış değişikliği getirmektir. Öğrenmenin gerçekleşmesi için farklı yöntem ve modeller kullanılmaktadır. Uzun yıllar eğitime hizmet veren yüz yüze öğrenme modeli, teknolojinin gelişmesiyle birlikte yerini diğer modellere bırakıyor. Bununla birlikte, bu geçiş sürecinde yaşanan bazı eksiklikler, öğrencinin psikolojik, teknik ve eğitimsel yeterlilik açısından kararlarını etkilemektedir. Öğrencilerden yüz yüze eğitim, uzaktan eğitim ve karma eğitim arasında bir seçim yapmaları istendiğinde durum ilginçtir. Bu makale, yüksek öğretim sistemindeki eğitim yöntemlerinde tercihleri çözmek için Tercih Sıralaması Tekniğinin İdeal Çözüme Benzerlik (TOPSIS) ve VlseKriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) ile karşılaştırılmasına odaklanmaktadır. Farklı eğitim yöntemlerinin sıralaması, bir çok kriterli karar verme (MCDM) problemidir. Bu yazıda Analitik Hiyerarşi Süreci (AHP) -TOPSIS tabanlı yaklaşım kullanılmıştır. Ardından, elde edilen sonuçları ve önerilen modeli doğrulamak için VIKOR yöntemi kullanılarak test edilmiştir. Araştırma, anket sorularını yanıtlayan 4009 üniversite öğrencisi ile gerçekleştirildi. Teknolojik fırsatlara ve değişikliklere rağmen en çok tercih edilen model olarak yüz yüze eğitim modeli ortaya çıkmakta, onu hibrit model ve uzaktan eğitim modeli takip etmektedir.

References

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  • A. Alenezi, (2020). The Role of e-Learning Materials in Enhancing Teaching and Learning Behaviors IJIET 10(1), 48-56.
  • A. Alghamdi, A. C. Karpinski, A. Lepp, J. Barkley, (2020). Online and face-to-face classroom multitasking and academic performance: Moderated mediation with self-efficacy for self-regulated learning and gender, Computers in Human Behavior , 102 , 214-222.
  • C. Carlson, G. Peterson and D. Day, (2019). Utilizing Portable Learning Technologies to Improve Student Engagement and Retention, in IEEE Transactions on Education, 63(1), 32-38, doi:10.1109/TE.2019.2941700.
  • L. A. Fish, C. R. Snodgrass, (2019). Instructor Academic Factors and Their Influence on Instructor Perspectives of Online versus Face-to-Face Education at a Jesuit Institution, Business Education Innovation Journal 11(1) ,107-117.
  • J. C. Evans, H. Yip, K. Chan, C. Armatas, A. Tse (2020) Blended learning in higher education: professional development in a Hong Kong university, Higher Education Research & Development, 39:4, 643-656, DOI: 10.1080/07294360.2019.1685943.
  • J. L. Núñez, E. T. Caro, J. R. H. González, (2017). From Higher Education to Open Education: Challenges in the Transformation of an Online Traditional Course, in IEEE Transactions on Education, 60(2), 134-142, doi: 10.1109/TE.2016.2607693.
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  • A. Tratnik, M. Urh, E. Jereb (2019) Student satisfaction with an online and a face-to-face Business English course in a higher education context, Innovations in Education and Teaching International, 56:1, 36-45, DOI: 10.1080/14703297.2017.1374875.
  • M. Usher, M. Barak, (2020). Team diversity as a predictor of innovation in team projects of faceto-face and online learners, Computers & Education 144, 103702.
  • C.Wang, H.C. K. Hsu, E. M. Bonem, J. D. Moss, S. Yu, D. B. Nelson, C. Levesque-Bristol, (2019). Need satisfaction and need dissatisfaction: A comparative study of online and face-to-face learning contexts’, Computers in Human Behavior, 95 ,114–125.
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  • E. Yıldız, S.S. Seferoğlu, (2020). Examination of Self-Efficacy Perception of Distance Education Students About Online Technologies, Celal Bayar University Journal of Social Sciences, 18 (1); 33-46.
  • Ö.F. Gökmen, İ. Duman, M.B. Horzum, (2016). Theories, changes and new directions in distance education, AUAd 2(3), 29-51. E. Larraza-Mendiluze, O. Arbelaitz, A. Arruarte, J. F. Lukas and N. Garay-Vitoria, (2020). JolasMATIKA: An Experience for Teaching and Learning Computing Topics From University to Primary Education, in IEEE Transactions on Education, 63(3), 136-143, doi: 10.1109/TE.2019.2951568.
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  • İ. Kaya, M. Çolak, F. Terzi, (2019). A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making. Energy Strategy Reviews, 24, 207-228.
  • E. Eren, U.R. Tuzkaya (2019) Occupational health and safety-oriented medical waste management: A case study of Istanbul, Waste Manag Res, 37(9):876-884. doi: 10.1177/0734242X19857802. A.Y. Korkusuz, U.H. İnan, Y. Özdemir, H. Başlıgil, (2020). Occupational health and safety performance measurement in healthcare sector using integrated multi criteria decision making methods, Journal of the Faculty of Engineering and Architecture of Gazi University 35,1 ,81-96.
  • T. L. Saaty, (1980). Axiomatic Foundation of the Analytic Hierarchy Process, Management Science, 32 (7), 841-855.
  • S. Tepe, A. Görener, (2014). An Implementation of Analytic Hierarchy Process and Moora Methods on the Employee Selection, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi,13(25), 1-14.
  • S. Aslantaş, S. Tepe, B. Mertoğlu, (2019). A Fuzzy Based Risk Assessment Model with a Real Case Study, In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga A., Sari I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, 1029. Springer, Cham. H.C. Liu, J. Wu, P. Li (2013). Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision-making method’, Waste Management 33, 2744–2751.
  • Jaschik, S. and Letterman, D. (2014). The 2014 Inside Higher Ed Survey of Faculty Attitudes to Technology Washington DC, Higher Education.
  • Means, B. et al. (2009) Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies Washington DC, US Department of Education.

A Performance Analysis for Face-to-Face, Distance and Hybrid Education Models Based on Student Satisfaction

Year 2021, Issue: 23, 254 - 271, 30.04.2021
https://doi.org/10.31590/ejosat.866479

Abstract

Learning is to bring about permanent behavioral change in the individual. Different methods and models are used for the realization of learning. The face-to-face learning model, which has served education for many years, leaves its place to other models with the development of technology. However, some lack of enthusiasm and deficiencies experienced during this transition process affect the learner's decisions in terms of psychological, technical and educational competence. The situation is interesting when students are asked to make a choice between face-to-face education, distance education and hybrid education. The present paper focuses on the comparison of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) to resolve preferences in education methods in higher education system. The ranking of the different education methods can be similar to solving multiple criteria decision-making (MCDM) problems. In this paper, Analytical Hierarchy Process (AHP) -TOPSIS based approach was used. Then it was tested using the VIKOR method to validate the results obtained and the proposed model. The study was conducted with 4009 university students answering the survey questions. Despite technological opportunities and changes, face-to-face education model emerges as the most preferred model, it is followed by hybrid model and distance education model.

References

  • P. J. Martínez, F. J. Aguilar and M. Ortiz, (2020). Transitioning from Face-to-Face to Blended and Full Online Learning Engineering Master’s Program, IEEE Transactions on Education, 63(1), 2-9, doi: 10.1109/TE.2019.2925320.
  • A. Alenezi, (2020). The Role of e-Learning Materials in Enhancing Teaching and Learning Behaviors IJIET 10(1), 48-56.
  • A. Alghamdi, A. C. Karpinski, A. Lepp, J. Barkley, (2020). Online and face-to-face classroom multitasking and academic performance: Moderated mediation with self-efficacy for self-regulated learning and gender, Computers in Human Behavior , 102 , 214-222.
  • C. Carlson, G. Peterson and D. Day, (2019). Utilizing Portable Learning Technologies to Improve Student Engagement and Retention, in IEEE Transactions on Education, 63(1), 32-38, doi:10.1109/TE.2019.2941700.
  • L. A. Fish, C. R. Snodgrass, (2019). Instructor Academic Factors and Their Influence on Instructor Perspectives of Online versus Face-to-Face Education at a Jesuit Institution, Business Education Innovation Journal 11(1) ,107-117.
  • J. C. Evans, H. Yip, K. Chan, C. Armatas, A. Tse (2020) Blended learning in higher education: professional development in a Hong Kong university, Higher Education Research & Development, 39:4, 643-656, DOI: 10.1080/07294360.2019.1685943.
  • J. L. Núñez, E. T. Caro, J. R. H. González, (2017). From Higher Education to Open Education: Challenges in the Transformation of an Online Traditional Course, in IEEE Transactions on Education, 60(2), 134-142, doi: 10.1109/TE.2016.2607693.
  • E. F. Monk, K. R. Guidry, K. L. Pusecker, T. W. Ilvento, (2020). Blended learning in computing education: It’s here but does it work? Education and Information Technologies 25, 83–104.
  • https://doi.org/10.1007/s10639-019-09920-4.
  • O. Pala, M. Aksaraylı, (2019). Evaluation of Quality Improvement Dimensions in Distance Education: SMART-AHP Based SERVQUAL Approach’, Ege Academic Review, 19 (2), 173 -187.
  • A. Tratnik, M. Urh, E. Jereb (2019) Student satisfaction with an online and a face-to-face Business English course in a higher education context, Innovations in Education and Teaching International, 56:1, 36-45, DOI: 10.1080/14703297.2017.1374875.
  • M. Usher, M. Barak, (2020). Team diversity as a predictor of innovation in team projects of faceto-face and online learners, Computers & Education 144, 103702.
  • C.Wang, H.C. K. Hsu, E. M. Bonem, J. D. Moss, S. Yu, D. B. Nelson, C. Levesque-Bristol, (2019). Need satisfaction and need dissatisfaction: A comparative study of online and face-to-face learning contexts’, Computers in Human Behavior, 95 ,114–125.
  • S.C. Yen, Y. Lo, A. Lee, J. May Enriquez, (2018). Learning online, offline, and in-between: comparing student academic outcomes and course satisfaction in face-to-face, online, and blended teaching modalities, Educ Inf echnol 23, 2141–2153.
  • E. Yıldız, S.S. Seferoğlu, (2020). Examination of Self-Efficacy Perception of Distance Education Students About Online Technologies, Celal Bayar University Journal of Social Sciences, 18 (1); 33-46.
  • Ö.F. Gökmen, İ. Duman, M.B. Horzum, (2016). Theories, changes and new directions in distance education, AUAd 2(3), 29-51. E. Larraza-Mendiluze, O. Arbelaitz, A. Arruarte, J. F. Lukas and N. Garay-Vitoria, (2020). JolasMATIKA: An Experience for Teaching and Learning Computing Topics From University to Primary Education, in IEEE Transactions on Education, 63(3), 136-143, doi: 10.1109/TE.2019.2951568.
  • Hannah T. Nennig, Katrina L. Idárraga, Luke D. Salzer, April Bleske-Rechek, Roslyn M. Theisen, ‘Comparison of student attitudes and performance in an online and a face-to-face inorganic chemistry course’, Chem. Educ. Res. Pract., 2020.
  • Ö.N. Bilişik, M. Erdogan, İ. Kaya, H. Baraçlı, (2013). A hybrid fuzzy methodology to evaluate customer satisfaction in a public transportation system for Istanbul. Total Quality Management & Business Excellence, 24, 1141-1159.
  • İ. Kaya, M. Çolak, F. Terzi, (2019). A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making. Energy Strategy Reviews, 24, 207-228.
  • E. Eren, U.R. Tuzkaya (2019) Occupational health and safety-oriented medical waste management: A case study of Istanbul, Waste Manag Res, 37(9):876-884. doi: 10.1177/0734242X19857802. A.Y. Korkusuz, U.H. İnan, Y. Özdemir, H. Başlıgil, (2020). Occupational health and safety performance measurement in healthcare sector using integrated multi criteria decision making methods, Journal of the Faculty of Engineering and Architecture of Gazi University 35,1 ,81-96.
  • T. L. Saaty, (1980). Axiomatic Foundation of the Analytic Hierarchy Process, Management Science, 32 (7), 841-855.
  • S. Tepe, A. Görener, (2014). An Implementation of Analytic Hierarchy Process and Moora Methods on the Employee Selection, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi,13(25), 1-14.
  • S. Aslantaş, S. Tepe, B. Mertoğlu, (2019). A Fuzzy Based Risk Assessment Model with a Real Case Study, In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga A., Sari I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, 1029. Springer, Cham. H.C. Liu, J. Wu, P. Li (2013). Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision-making method’, Waste Management 33, 2744–2751.
  • Jaschik, S. and Letterman, D. (2014). The 2014 Inside Higher Ed Survey of Faculty Attitudes to Technology Washington DC, Higher Education.
  • Means, B. et al. (2009) Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies Washington DC, US Department of Education.
There are 25 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Serap Tepe 0000-0002-9723-6049

Publication Date April 30, 2021
Published in Issue Year 2021 Issue: 23

Cite

APA Tepe, S. (2021). A Performance Analysis for Face-to-Face, Distance and Hybrid Education Models Based on Student Satisfaction. Avrupa Bilim Ve Teknoloji Dergisi(23), 254-271. https://doi.org/10.31590/ejosat.866479