Abstract
Distance education (DE) has a unique potential to ensure continuity of education in extraordinary circumstances such as pandemics and earthquakes, in addition to its advantages such as flexibility in terms of time and space and self-paced learning options. Institutional support provided for instructors engaged in DE programmes is one of the factors which directly affect the efficiency of DE and the quality of the education provided. This study aimed to determine the criteria of institutional support offered to DE instructors through document analysis, and to reveal the importance weights of those criteria by using the method of multi-criteria decision-making (MCDM). The author examined the standards published by a number of accreditation institutions and international educational organisations for DE, and determined the importance weights of those criteria by applying an analytic hierarchy process (AHP). She determined seven support criteria, namely (in order of importance): (1) technical training and orientation; (2) teaching material and resource support; (3) technical support; (4) professional development support; (5) support during the course; (6) evaluation and report submission support; and (7) career development, incentives and financial support. In presenting her study, the author provides an effective evaluation framework for DE support systems which includes a comprehensive set of indicators based on a literature review and feedback from experts.
Résumé
Définition, sur la base de la méthode d’aide à la décision multicritère, d’un cadre pour le soutien institutionnel aux enseignants intervenant dans des programmes d’enseignement à distance – En plus des avantages qu’il offre en termes de flexibilité quant au temps, au lieu et au rythme d’apprentissage défini individuellement, l’enseignement à distance recèle des possibilités uniques pour assurer la continuité de l’enseignement dans des circonstances exceptionnelles comme les pandémies et les tremblements de terre. Le soutien institutionnel fourni aux enseignants intervenant dans des programmes d’enseignement à distance est l’un des facteurs qui influent directement sur l’efficacité et la qualité des prestations offertes en la matière. Cette étude vise à définir les critères du soutien institutionnel proposé aux enseignants dans l’enseignement à distance en s’appuyant sur l’analyse de documents et à révéler les poids d’importance de ces critères en recourant à la méthode d’aide à la décision multicritère. L’autrice s’est penchée sur les normes publiées par un ensemble d’organismes d’accréditation et d’organisations internationales d’éducation en matière d’enseignement à distance et a déterminé les poids d’importance de ces critères en se basant sur un processus de hiérarchisation analytique. Elle a déterminé sept critères de soutien (par ordre d’importance) : (1) formation et orientation techniques ; (2) soutien concernant le matériel pédagogique et les ressources ; (3) soutien technique ; (4) soutien au développement professionnel ; (5) soutien pendant les cours ; (6) soutien à l’évaluation et à la présentation d’un rapport ; (7) soutien en matière d’évolution de carrière, d’incitations et en termes financiers. Par cette étude, l’autrice nous offre un cadre d’évaluation efficace des systèmes de soutien à l’enseignement à distance, qui englobe un ensemble exhaustif d’indicateurs reposant sur un examen de la littérature et les commentaires de spécialistes.




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Data availability
Data will be made available on reasonable request.
Notes
A learning management system “is a software application or web-based technology used to plan, implement and assess a specific learning process. It’s used for e-learning practices and, in its most common form, consists of two elements: a server that performs the base functionality and a user interface (UI) that is operated by instructors, students and administrators. Typically, an LMS provides an instructor with a way to create and deliver content, monitor student participation, and assess student performance. It might also provide students with interactive features, such as threaded discussions, video conferencing and discussion forums” (Kirvan and Brush 2023, online).
A supplementary table with detailed descriptions of each criterion is available from the author upon reasonable request.
The AHP calculation is available (in Turkish) from the author upon reasonable request.
References
ACCET (Accrediting Council for Continuing Education Training) (2015). Interactive Distance Learning (Idl) Template. Washington, DC: ACCET. Retrieved 23 January 2024 from https://s3.amazonaws.com/docs.accet.org/downloads/docs/Dec%202015%20Updated%20Final%20Docs/doc.3.idl.2015.final.pdf
ACCJC (Accrediting Commission for Community and Junior Colleges) (2014). Accreditation Standards. Sacramento, CA: ACCJC. Retrieved 23 January 2024 from https://accjc.org/wp-content/uploads/Accreditation-Standards_-Adopted-June-2014.pdf
ACCJC (2021). Policy on Distance Education and on Correspondence Education. Sacramento, CA: ACCJC. Retrieved 23 January 2024 from https://accjc.org/wp-content/uploads/Policy-on-Distance-and-on-Correspondence-Education.pdf
ACICS (Accrediting Council for Independent Colleges and Schools) (2022). Criteria [dedicated webpage]. Washington, DC: ACICS. Retrieved 30 January 2023 from https://www.acics.org/accreditation-criteria
Adem, A., Çakıt, E., & Dağdeviren, M. (2022). Selection of suitable distance education platforms based on human-computer interaction criteria under fuzzy environment. Neural Computing & Applications, 34(10), 7919–7931. https://doi.org/10.1007/s00521-022-06935-w
AFT (American Federation of Teachers) (2000). Distance education: Guidelines for good practice. Washington, DC: AFT. Retrieved 23 January 2024 from https://silo.tips/download/distance-education-guidelines-for-good-practice
Aguti, J. N., & Fraser, W. J. (2005). The challenges of universal primary education in Uganda through distance education programmes. Africa Education Review, 2(1), 91–108. https://doi.org/10.1080/18146620508566293
Al-Busaidi, K. A., & Al-Shihi, H. (2010). Instructors' acceptance of learning management systems: A theoretical framework. Communications of the IBIMA, Art. no. 862128. https://doi.org/10.5171/2010.862128
Aldossari, S., & Altalhab, S. (2022). Distance learning during COVID-19: EFL students’ engagement and motivation from teachers’ perspectives. English Language Teaching, 15(7), 85–109. https://doi.org/10.5539/elt.v15n7p85
Alhih, M., Ossiannilsson, E., & Berigel, M. (2017). Levels of interaction provided by online distance education models. Eurasia Journal of Mathematics, Science and Technology Education, 13(6), 2733–2748. https://doi.org/10.12973/eurasia.2017.01250a
Ali, N. S., Hodson-Carlton, K., Ryan, M., Flowers, J., Rose, M., & Wayda, V. (2005). Online education: Needs assessment for faculty development. Journal of Continuing Education in Nursing, 36(1), 32–38. https://doi.org/10.3928/0022-0124-20050101-09
Alice, P. S., Abirami, A. M., & Askarunisa, A. (2012). A semantic based approach to organize eLearning through efficient information retrieval for interview preparation. In Proceedings of the 2012 International Conference on Recent Trends in Information Technology (pp. 151-156). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). Retrieved 23 January 2024 from https://ieeexplore.ieee.org/abstract/document/6206743
Alshaboul, Y., Hamaidi, D., Arouri, Y., & Alshaboul, A. (2021). COVID-19 Enforced shift to distance education: Readiness and challenges. Journal of Education and E-Learning Research, 8(3), 349–359. https://doi.org/10.20448/journal.509.2021.83.349.359
Andrade, M. S. (2015). Teaching online: A theory-based approach to student success. Journal of Education and Training Studies, 3(5), 1–9. https://doi.org/10.11114/jets.v3i5.904
Arbour, M., Kaspar, R. W., & Teall, A. M. (2015). Strategies to promote cultural competence in distance education. Journal of Transcultural Nursing, 26(4), 436–440. https://doi.org/10.1177/1043659614547201
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
Avila, E. C., Abin, G. J., Bien, G. A., Acasamoso, D. M., & Arenque, D. D. (2021). Students’ perception on online and distance learning and their motivation and learning strategies in using educational technologies during COVID-19 pandemic. Journal of Physics: Conference Series, 1933, Art. no. 012130. https://doi.org/10.1088/1742-6596/1933/1/012130
Ayouni, S., Menzli, L. J., Hajjej, F., Madeh, M., & Al-Otaibi, S. (2021). Fuzzy Vikor application for learning management systems evaluation in higher education. International Journal of Information and Communication Technology Education, 17(2), 17–35. https://doi.org/10.4018/Ijicte.2021040102
Bao, W. (2020). COVID 19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(2), 113–115. https://doi.org/10.1002/hbe2.191
CACE (Community Association for Community Education) (2001). Creating quality guidelines for online education and training: Consultation workbook. Vancouver, BC: CACE. Retrieved 23 January 2024 from http://futured.com/form/pdf/english.pdf
Çakmak, Z., & Kaçar, T. (2021). The views of social studies teachers on distance education. Review of International Geographical Education Online, 11(3), online. https://doi.org/10.33403/rigeo.870846
Çalişkan, S., Kurbanov, R. A., Platonova, R. I., Ishmuradova, A. M., Vasbieva, D. G., & Merenkova, I. V. (2020). Lecturers’ views of online instructors about distance education and Adobe Connect. International Journal of Emerging Technologies in Learning, 23(15), 145–157. https://doi.org/10.3991/ijet.v15i23.18807
Casey, D. M. (2008). A journey to legitimacy: The historical development of distance education through technology. TechTrends, 52(2), 45–51. https://doi.org/10.1007/s11528-008-0135-z
Çelik, T. I., Konokman, G. Y., & Yelken, T. Y. (2022). Evaluation of distance learning practices (from the instructors perspective): Planning, implementation and evaluation. Education Quarterly Reviews, 5(2), 1–21. https://doi.org/10.31014/aior.1993.05.02.463
Chapman, D. D. (2011). Contingent and tenured/tenure-track faculty: Motivations and incentives to teach distance. Online Journal of Distance Learning Administration, 14(3), 1–12. Retrieved 23 January 2024 from https://ojdla.com/archive/fall143/chapman143.pdf
CHEA (Council for Higher Education Accreditation) (2002). Accreditation and assuring quality in distance learning. Washington, DC: CHEA. Retrieved 23 January 2024 from https://www.chea.org/accreditation-and-assuring-quality-distance-learning
Chen, J. F., Hsieh, H. N., & Do, Q. H. (2015). Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach. Applied Soft Computing, 28, 100–108. https://doi.org/10.1016/j.asoc.2014.11.050
Choi, S., Lee, S. Y., Lee, J. W. (2022). 유아교육 교수자의 원격수업 운영 현황 및 인식 [Early childhood education instructors’ teaching practice and perceptions of distance learning]. 韓國幼兒敎育·保育行政硏究 [Journal of Early Childhood Education and Welfare], 26(3), 113–132. https://doi.org/10.22590/ecee.2022.26.3.113
Clark, T. (1993). Attitudes of higher education faculty toward distance education: A national survey. American Journal of Distance Education, 7(2), 19–33. https://doi.org/10.1080/08923649309526820
Coe, J. A. R., & Elliott, D. (1999). An evaluation of teaching direct practice courses in a distance education program for rural settings. Journal of Social Work Education, 35(3), 353–365. https://doi.org/10.1080/10437797.1999.10778974
Colace, F., & De Santo, M. (2011). Evaluation models for e-learning platforms and the AHP approach: A case study. The IPSI BGD Transactions on Internet Research, 7(1), 31–43. https://doi.org/10.1109/FIE.2006.322312
Colace, F., De Santo, M., & Pietrosanto, A. (2006). Evaluation models for e-learning platform: An AHP approach. In Proceedings. Frontiers in Education. 36th Annual Conference (pp. 1–6). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/FIE.2006.322312
Cook, R. G., Ley, K., Crawford, C., & Warner, A. (2009). Motivators and inhibitors for university faculty in distance and e-learning. British Journal of Educational Technology, 40(1), 149–163. https://doi.org/10.1111/j.1467-8535.2008.00845.x
Dağdeviren, M., Akay, D., & Kurt, M. (2004). İş Değerlendirme Sürecinde Analitik Hiyerarşi Prosesi ve Uygulaması [Analytical hierarchy process and its application in job evaluation process]. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi [Gazi University Journal of Faculty of Engineering and Architecture], 19(2), 131–138.
DEAC (Distance Education Accrediting Commission) (2022). Accreditation handbook: Policies, procedures, standards and guides of the Distance Education Accrediting Commission (31st edn). Washington, DC: DEAC. Retrieved 23 January 2024 from https://www.deac.org/UploadedDocuments/Handbook/DEAC_Accreditation_Handbook.pdf
Doliner, L., & Nazarov, V. (2021). Adapting the e-course for teacher training in the teacher professional development system. E3S Web of Conferences, 295, Art. no. 05002. https://doi.org/10.1051/e3sconf/202129505002
Donegan, H. A., Dodd, F. J., & McMaster, T. B. M. (1992). A new approach to AHP decision-making. Journal of the Royal Statistical Society: Series D (The Statistician), 41(3), 295–302. https://doi.org/10.2307/2348551
EADTU (European Association of Distance Teaching Universities) (2016). Quality assessment for e-learning: A benchmarking approach (3rd edn). Maastricht: EADTU. Retrieved 23 January 2024 from https://e-xcellencelabel.eadtu.eu/images/E-xcellence_manual_2016_third_edition.pdf
EFQUEL (European Foundation for Quality in e-Learning). (2011). UNIQUe – European Universities Quality in e-Learning – the guidelines [dedicated webpage]. Brussels: EFQUEL. Retrieved 30 January 2023 from http://efquel.org/aboutus/
ENQA (European Association for Quality Assurance in Higher Education), ESU (European Students’ Union), EUA (European University Association), EURASHE (European Association of Institutions in Higher Education), EI (Education International) BUSINESSEUROPE, & EQAR (European Quality Assurance Register for Higher Education) (2015). Standards and guidelines for quality assurance in the European higher education area (ESG). Brussels: EURASHE. Retrieved 23 January 2024 from https://www.enqa.eu/wp-content/uploads/2015/11/ESG_2015.pdf
Fandel, G., Spronk, J., & Matarazzo, B. (Eds.). (1985). Multiple criteria decision methods and applications: Selected readings of the first international summer school, Acireale, Sicily, September 1983. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-70583-0
Ferdousi, F., Ahmed, A., & Momen, M. A. (2022). Evolution of quality assurance practices in enhancing the quality of open and distance education in a developing nation: a case study. Asian Association of Open Universities Journal, 17(2), 147–160. https://doi.org/10.1108/AAOUJ-02-2022-0025
Fish, W. W., & Wickersham, L. E. (2009). Best practices for online instructors: Reminders. Quarterly Review of Distance Education, 10(3), 279–284.
Gámez, F. D. G., Párraga, L. M., Palmero, J. R., & Rodríguez, A. P. (2022). Formación del profesorado universitario en Competencia Digital: análisis con métodos de investigación correlacionales y comparativos [Training of university teachers in digital competence: Analysis with correlational and comparative research methods]. Hachetetepé. Revista científica de educación y comunicación, 24, Article no. 1101. https://doi.org/10.25267/hachetetepe.2022.i24.1101
Garg, R., Kumar, R., & Garg, S. (2019). MADM-based parametric selection and ranking of e-learning websites using fuzzy COPRAS. IEEE Transactions on Education, 62(1), 11–18. https://doi.org/10.1109/TE.2018.2814611
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, Article no. 107118. https://doi.org/10.1016/j.asoc.2021.107118
Guennoun, B., & Benjelloun, N. (2022). Distance teacher training and assessment in the era of Covid 19 pandemic. International Journal of Information and Education Technology, 12(12), 1321–1336. https://doi.org/10.18178/ijiet.2022.12.12.1756
Gupta, V., Chauhan, D. S., & Dutta, K. (2013). Incremental development & revolutions of e-learning software systems in education sector: A case study approach. Human-centric Computing and Information Sciences, 3(1), Article no. 8. https://doi.org/10.1186/2192-1962-3-8
Hadullo, K.; Oboko, R.; Omwenga, E. (2017). A model for evaluating e-learning systems quality in higher education in developing countries. International Journal of Education and Development using ICT, 13(2), 185–204. Retrieved 23 January 2024 from http://ijedict.dec.uwi.edu/viewarticle.php?id=2311
Hassenplug, C. A., & Harnish, D. (1998). The nature and importance of interaction in distance education credit classes at technical institutes. Community College Journal of Research and Practice, 22(6), 591–605. https://doi.org/10.1080/1066892980220602
Hou, F., Geng, J., & Cao, L. (2021). Analysis of quality supervision of distance learning in typical developed countries. In Proceedings of the 2021 12th International Conference on E-Education, E-Business, E-Management, and E-Learning (IC4E ‘21) (pp. 243–247). New York, NY: Association for Computing Machinery (ACM). https://doi.org/10.1145/3450148.3450157
IHEP (Institute for Higher Education Policy) (2014 [2000]). Quality on the line: Benchmarks for success in internet-based distance education. Washington, DC: IHEP. Retrieved 29 January 2024 from https://www.ihep.org/wp-content/uploads/2014/05/uploads_docs_pubs_qualityontheline.pdf
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. https://doi.org/10.1007/s40692-016-0061-6
Jeong, H. Y., & Yeo, S. S. (2014). The quality model for e-learning system with multimedia contents: a pairwise comparison approach. Multimedia Tools and Applications, 73(2), 887–900. https://doi.org/10.1007/s11042-013-1445-5
Kadoić, N., Ređep, N. B., & Divjak, B. (2017). Structuring e-learning multi-criteria decision-making problems. In Proceedings of the 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 705–710). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.23919/MIPRO.2017.7973514
Kara, M., Kukul, V., & Çakır, R. (2018). Conceptions and misconceptions of instructors pertaining to their roles and competencies in distance education: A qualitative case study. Participatory Educational Research, 5(2), 67–79. https://doi.org/10.17275/per.18.12.5.2
Karimov, K. A. (2022). Modeling the process of distance training of managers and teachers of professional education system. Moscow: Pero. https://doi.org/10.15350/9785002044658
Kayaduman, H. (2021). The adaptation process of a first-time distance education instructor: A Single-subject research study. In T. P. Fudge & S. S. Ferebee (Eds.), Curriculum development and online instruction for the 21st century (pp. 301–322). Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-7998-7653-3.ch016
Kazondovi, C., Isaacs, A., & Lwendo, S. B. (2022). The challenges distance education students experience during their education degree program in the Faculty of Education at the University of Namibia. Higher Education Studies, 12(2), 54–59. https://doi.org/10.5539/hes.v12n2p54
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. https://doi.org/10.1007/s40692-019-00135-7
Kirvan, P., & Brush, K. (2023). What is a learning management system (LMS)? TechTarget, 8 September [online resource]. Retrieved 29 January 2024 from https://www.techtarget.com/searchcio/definition/learning-management-system
Kurilovas, E., & Dagiene, V. (2010). Multiple criteria evaluation of quality and optimisation of e-learning system components. Electronic Journal of e-Learning, 8(2), 141–150. Retrieved 23 January 2024 from https://academic-publishing.org/index.php/ejel/article/view/1595
Magdalinou, A., Liaskos, J., Isaakidou, M., & Mantas, J. (2022). The transition to distance learning in the era of Covid-19 pandemic: The perceptions and experiences of nursing students. In J. Mantas, P. Gallos, E. Zoulias, A. Hasman, M. S. Househ, M. Diomidous, J. Liaskos, & M. Charalampidou (Eds.), Advances in Informatics, management and technology in healthcare (pp. 495–498). Amsterdam: IOS Press. https://doi.org/10.3233/shti220773
Mahlangu, V. P. (2016). Assuring quality in ODL through Ubuntu. In M. Letseka (Ed.), Open distance learning (ODL) through the philosophy of Ubuntu (pp. 107–118). New York, NY: Nova.
Marchenko, A., Nikolishyna, E., Litovchenko, I., Nikolishyn, I., & Khmil, T. (2020). Advantages and disadvantages of distance education for future dentists. Пpoблeми бeзпepepвнoї мeдичнoї ocвiти тa нayки, 40(4), 11–14. https://doi.org/10.31071/promedosvity2020.04.011
Meccawy, Z., Meccawy, M., & Alsobhi, A. (2021). Assessment in “survival mode”: Student and faculty perceptions of online assessment practices in HE during Covid-19 pandemic. International Journal for Educational Integrity, 17, Article no. 16. https://doi.org/10.1007/s40979-021-00083-9
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), Article no. 4071. https://doi.org/10.3390/su12104071
Munkhtsetseg, N., Garmaa, D., & Uyanga, S. (2014). Multi-criteria comparative evaluation of the e-learning systems: A case study. In Proceedings of the 2014 7th International Conference on Ubi-Media Computing and Workshops (pp. 190–195). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/U-MEDIA.2014.47
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), Article no. e0231465. https://doi.org/10.1371/journal.pone.0231465
Nguyen, D. N., Zierler, B., & Nguyen, H. Q. (2011). A survey of nursing faculty needs for training in use of new technologies for education and practice. Journal of Nursing Education, 50(4), 181–189. https://doi.org/10.3928/01484834-20101130-06
Niku, E. M. (2023). Quality management of distance learning higher education. International Journal of Social Science and Human Resources, 6(3), 1941–1948. https://doi.org/10.47191/ijsshr/v6-i3-72
Nsamba, A., & Makoe, M. (2017). Evaluating quality of students’ support services in open distance learning. Turkish Online Journal of Distance Education, 18(4), 91–103. https://doi.org/10.17718/tojde.340391
NSQ (National Standards for Quality) (2019). Overview of changes to the national standards for quality online programs: Second edition. Annapolis, MD: Quality Matters (QM), Virtual Learning Leadership Alliance (VLA), and Digital Learning Collaborative (DLC). Retrieved 23 January 2024 from https://www.nsqol.org/the-standards/quality-online-programs/
Paul, M., Chrispen, C., & Alexander, C. R. (2012). Removing stumps and blocks for students to reach the unreached through quality assurance at the Zimbabwe Open University: A case study. Huria: Journal of the Open University of Tanzania, 13(2), 1–14. https://www.ajol.info/index.php/huria/article/view/110800
Qin, Y., & Zhang, Q. (2008). The research on affecting factors of e-learning training effect. In Proceedings of the 2008 International Conference on Computer Science and Software Engineering (Vol. 5, pp. 271–277). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CSSE.2008.141
Rizwan, M. (2021). Factors affecting student satisfaction in distance learning: A case study of COMSATS (VIRTUAL CAMPUS). Journal of Learning Improvement and Lesson Study, 1(1), 1–10. https://doi.org/10.24036/jlils.v1i1.3
Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281. https://doi.org/10.1016/0022-2496(77)90033-5
Saaty, T. L. (2004). Decision making: The analytic hierarchy and network processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1–35. https://doi.org/10.1007/s11518-006-0151-5
Samawi, F. (2021). Educational crisis management requirements and its relation to using distance learning approach: A cross-sectional survey secondary stage schools in Al-balqa’a governorate during Covid-19 outbreak from the perspectives of teachers. Turkish Online Journal of Distance Education, 22(3), 196–212. https://doi.org/10.17718/tojde.961837
Sesabo, J. K., Mfaume, R., & Msabila, D. T. (2015). Opportunities and challenges in implementing distance learning and e-learning: A case study. In J. Keengwe (Ed.), Handbook of research on educational technology integration and active learning (pp. 329–345). Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-4666-8363-1.ch016
Sharma, R., Banati, H., & Bedi, P. (2011). Incorporating social opinion in content selection for an e-learning course. In Proceedings of the 2011 6th International Conference on Computer Science & Education (ICCSE) (pp. 1027–1032). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICCSE.2011.6028811
Shelton, K., Saltsman, G., Holstrom, L., & Pedersen, K. (Eds.). (2014). Quality scorecard 2014 handbook: Criteria for excellence in the administration of online programs. Newburyport, MA: Online Learning Consortium (OLC).
Simon, H. A. (1960). The new science of management decision. New York, NY: Harper & Brothers. https://doi.org/10.1037/13978-000
Stella, A., & Gnanam, A. (2004). Quality assurance in distance education: The challenges to be addressed. Higher Education, 47(2), 143–160. https://doi.org/10.1023/B:HIGH.0000016420.17251.5c
Stickney, L. T., Bento, R. F., Aggarwal, A., & Adlakha, V. (2019). Online higher education: Faculty satisfaction and its antecedents. Journal of Management Education, 43(5), 509–542. https://doi.org/10.1177/1052562919845022
Tarasova, N. V., Pastukhova, I. P., & Chigrina, S. G. (2021). Heкoтopыe acпeкты мeтoдичecкoгo coпpoвoждeния yчитeлeй в ycлoвияx цифpoвизaции oбщeгo oбpaзoвaния [Some aspects of methodological support of teachers in the conditions of digitalization of general education]. Пepcпeктивы Hayки и Oбpaзoвaния, 5(53), 481–494. https://doi.org/10.32744/pse.2021.5.33
Thapliyal, U. (2014). Perceived quality dimensions in distance education: Excerpts from student experiences. Turkish Online Journal of Distance Education, 15(3), 60–67. https://doi.org/10.17718/tojde.76579
Thomas, P., Carswell, L., Price, B., & Petre, M. (1998). A holistic approach to supporting distance learning using the Internet: transformation, not translation. British Journal of Educational Technology, 29(2), 149–161. https://doi.org/10.1111/1467-8535.00056
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), Article no. 3136. https://doi.org/10.3390/math9233136
Tseng, M. L., Lin, R. J., & Chen, H. P. (2011). Evaluating the effectiveness of e-learning system in uncertainty. Industrial Management & Data Systems, 111(6), 869–889. https://doi.org/10.1108/02635571111144955
Tukenova, N. I., Ramazanov, R. G., Gruzdeva, M. L., Baydildinov, T. Z., & Naubetova, S. A. (2019). Methodology for developing e-learning courses in IT education. International Journal of Innovative Technology and Exploring Engineering, 8(10), 3614–3616. https://doi.org/10.35940/ijitee.j9787.0881019
Tuma, F., Nassar, A. K., Kamel, M. K., Knowlton, L. M., & Jawad, N. K. (2021). Students and faculty perception of distance medical education outcomes in resource-constrained system during COVID-19 pandemic: A cross-sectional study. Annals of Medicine and Surgery, 62, 377–382. https://doi.org/10.1016/j.amsu.2021.01.073
Turan, H. (2018). Assessment factors affecting e-learning using fuzzy analytic hierarchy process and SWARA. The International Journal of Engineering Education, 34(3), 915–923. Retrieved 23 January 2024 from https://www.ijee.ie/latestissues/Vol34-3/08_ijee3607.pdf
Turan, Z., Kucuk, S., & Cilligol Karabey, S. (2022). The university students’ self-regulated effort, flexibility and satisfaction in distance education. International Journal of Educational Technology in Higher Education, 19(1), Article no. 35. https://doi.org/10.1186/s41239-022-00342-w
Vaill, A. L., & Testori, P. A. (2012). Orientation, mentoring and ongoing support: A three-tiered approach to online faculty development. Journal of Asynchronous Learning Networks, 16(2), 111–119. https://doi.org/10.24059/olj.v16i2.256
Visser, Y. L. (2005). Dynamism and evolution in student support and instruction in distance education. In Y. L. Visser, L. Visser, M. Simonsın, & R. Amirault (Eds.), Trends and issues in distance education: International perspectives (pp. 287–307). Charlotte, NC: Information Age Publishing.
Vrazhnova, M. N., Anastasov, M. S., & Takigawa, G. N. (2021). Impact of professional self-improvement on the effectiveness of teachers in distance education. Revista Tempos e Espaços em Educação, 14(33), Article no. e16159. https://doi.org/10.20952/revtee.v14i33.16159
WICHE (Western Interstate Commission for Higher Education). (1995). Principles of good practice for electronically offered academic degree and certificate programs. Boulder, CO: WICHE.
Yigit, T., Isik, A. H., & Ince, M. (2014). Web-based learning object selection software using analytical hierarchy process. IET Software, 8(4), 174–183. https://doi.org/10.1049/iet-sen.2013.0116
Yildiz, M., & Erdem, M. (2018). An investigation on instructors’ knowledge, belief and practices towards distance education. Malaysian Online Journal of Educational Technology, 6(2), 1–20. https://doi.org/10.17220/mojet.2018.02.001
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. https://doi.org/10.1016/j.asoc.2016.04.020
Zavadskas, E. K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy, 16(2), 159–172. https://doi.org/10.3846/tede.2010.10
Zhang, L., Wen, H., Li, D., Fu, Z., & Cui, S. (2010). E-learning adoption intention and its key influence factors based on innovation adoption theory. Mathematical and Computer Modelling, 51(11–12), 1428–1432. https://doi.org/10.1016/j.mcm.2009.11.013
Zhao, J., & Li, X. (2009). Inspiration from an analysis of the British and American quality assurance system of distance higher education. In Proceedings of the 2009 First International Workshop on Education Technology and Computer Science (pp. 241–246). Piscataway Township, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/etcs.2009.581
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Tonbuloğlu, B. Determining a framework for institutional support of instructors engaged in distance education programmes using the multiple-criteria decision-making method. Int Rev Educ 70, 111–141 (2024). https://doi.org/10.1007/s11159-023-10045-7
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DOI: https://doi.org/10.1007/s11159-023-10045-7


