Identifying and Ranking Effectiveness Factors of E-Learning System
Subject Areas :
Hamidreza Nematollahi
1
,
ندا محمداسمعیلی
2
,
Arian Gholipour
3
,
saeed پاکدل
4
1 - Master's degree, Department of Leadership and Human Capital, Faculty of Management, University of Tehran, Tehran, Iran
2 - Assistant Professor, Department of Leadership and Human Capital, Faculty of Management, University of Tehran, Tehran, Iran
3 - Professor, Department of Leadership and Human Capital, Faculty of Management, University of Tehran, Tehran, Iran
4 - Vice President of the Scientific Association of Education and Development of Human Resources
Keywords: e-learning, learning, e-learning improvement, e-learning effectiveness, mixed method,
Abstract :
Electronic education and learning is one of the subjects which has recently received great attention in the educational system. Hence it is important to investigate the factors that have a significant impact on the success of the electronic education process and lead to the improvement or reduction of the quality of this educational system. In this regard, the present study ought to provide a comprehensive classification of effective factors in the e-learning system by using the mixed method. First, this study by using the mixed method (theme analysis) method, tried to provide a comprehensive classification of effective factors in the e-learning system, and then by using TOPSIS method the factors were ranked. With regard to the goal, this was an applied research and in terms of time it is a cross-sectional. The participants in the research were employees, professors and students in different fields of Tehran University. 15 individuals were selected after theoretical saturation and the data was collected through semi-structured interviews. By analyzing the obtained data, 43 organizing themes were extracted from the codes, and with further consideration the researchers reached 6 main and comprehensive themes. As the result of ranking revealed, the factors including standardization of e-learning, content interaction, documentation and monitoring of education, and the factors of pedagogy and educational design have the greatest impact, and the factors including increase in perceived usefulness, personal and skill improvement, and network learning have the least impact.
1) Zaharias P, Koutsabasis P. Heuristic evaluation of e-learning courses: A comparative analysis of two e-learning heuristic sets. Vol. 29, Campus-Wide Information Systems. 2011.
2 )Chiu HY, Sheng CC, Chen AP. Modeling agent-based performance evaluation for e-learning systems. Electron Libr. 2008;26(3).
3) Baber H. Determinants of students’ perceived learning outcome and satisfaction in online learning during the pandemic of COVID19. J Educ e-Learning Res. 2020;7(3).
4) Vetrugno G, Laurenti P, Franceschi F, Foti F, D’Ambrosio F, Cicconi M, et al. Gemelli decision tree Algorithm to Predict the need for home monitoring or hospitalization of confirmed and unconfirmed COVID-19 patients (GAP-Covid19): Preliminary results from a retrospective cohort study. Eur Rev Med Pharmacol Sci. 2021;25(6).
5) Tokarieva A V., Volkova NP, Degtyariova Y V., Bobyr OI. E-learning in the present-day context: From the experience of foreign languages department, PSACEA. In: Journal of Physics: Conference Series. 2021.
6) Shehzadi S, Nisar QA, Hussain MS, Basheer MF, Hameed WU, Chaudhry NI. The role of digital learning toward students’ satisfaction and university brand image at educational institutes of Pakistan: a post-effect of COVID-19. Asian Educ Dev Stud. 2021;10(2).
7) Aissaoui K, Amane M, Berrada M, Madani MA. A New Framework to Secure Cloud Based e-Learning Systems. In 2022.
8) Mustafa A. The personalization of e-learning systems with the contrast of strategic knowledge and learner’s learning preferences: an investigatory analysis. Appl Comput Informatics. 2021;17(1).
9) Srivastava B, Haider MTU. Personalized assessment model for alphabets learning with learning objects in e-learning environment for dyslexia. J King Saud Univ - Comput Inf Sci. 2020;32(7).
10) Koh JHL, Kan RYP. Students’ use of learning management systems and desired e-learning experiences: are they ready for next generation digital learning environments? High Educ Res Dev. 2021;40(5).
11) Ahmed Z, Zeeshan S, Foran DJ, Kleinman LC, Wondisford FE, Dong XQ. Integrative clinical, genomics and metabolomics data analysis for mainstream precision medicine to investigate COVID-19. Vol. 7, BMJ Innovations. 2021.
12) Kratochvíl J. Evaluation of e-learning course, Information Literacy, for medical students. Electron Libr. 2013;31(1).
13) Ning Z, Zhang K, Wang X, Guo L, Hu X, Huang J, et al. Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution. IEEE Trans Intell Transp Syst. 2021;22(4).
14) Williamson B. Making markets through digital platforms: Pearson, edu-business, and the (e)valuation of higher education. Crit Stud Educ. 2021;62(1).
15) Overmyer KA, Shishkova E, Miller IJ, Balnis J, Bernstein MN, Peters-Clarke TM, et al. Large-Scale Multi-omic Analysis of COVID-19 Severity. Cell Syst. 2021;12(1).
16) Wei HL, Mukherjee T, Zhang W, Zuback JS, Knapp GL, De A, et al. Mechanistic models for additive manufacturing of metallic components. Vol. 116, Progress in Materials Science. 2021.
17) Zeng N, Li H, Wang Z, Liu W, Liu S, Alsaadi FE, et al. Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip. Neurocomputing. 2021;425.
18) Ranieri M, Raffaghelli JE, Bruni I. Game-based student response system: Revisiting its potentials and criticalities in large-size classes. Act Learn High Educ. 2021;22(2).
19) Fadli MR, Sudrajat A, Zulkarnain Z, Aman A, Setiawan R, Amboro K. The effectiveness of E-Module learning history inquiry model to grow student historical thinking skills material event proclamation of Independence. Int J Adv Sci Technol. 2020;29(08).
20) Matveev MO. Psychological aspects of history e-learning. Vopr Istor. 2021;(3).
21) Daud A, Hardian M. THE APPLICATION OF BASIC PRINCIPLES OF ONLINE LEARNING THROUGH GOOGLE SUITE FOR EDUCATION DURING COVID19 OUTBREAK. Ta’dib. 2021;24(1).
22) Tsekea S, Chigwada JP. COVID-19: strategies for positioning the university library in support of e-learning. Digit Libr Perspect. 2021;37(1).
23) Daghestani LF, Ibrahim LF, Al-Towirgi RS, Salman HA. Adapting gamified learning systems using educational data mining techniques. Comput Appl Eng Educ. 2020;28(3).
24) Vijayalakshmi V, Venkatachalapathy K, Ohmprakash V. Analysis of E-Learning Concept. Int J Futur Revolut Comput Sci Commun Eng. 2017;3(12).
25) Nanang J, Rahman S, Surat S. Motivasi Menggunakan E Pembelajaran dan Pencapaian Sejarah dalam Kalangan Pelajar Tingkatan 4 ( Motivation using E Learning and Achievement of History Subject among Form 4 Students ). Asian J Univ Educ. 2021;3(1).
26) Giannakos MN, Mikalef P, Pappas IO. Systematic Literature Review of E-Learning Capabilities to Enhance Organizational Learning. Inf Syst Front. 2021;
27) Wu W, Plakhtii A. E-Learning Based on Cloud Computing. Int J Emerg Technol Learn. 2021;16(10).
28) Tyurina Y, Troyanskaya M, Babaskina L, Choriyev R, Pronkin N. E-Learning for SMEs. Int J Emerg Technol Learn. 2021;16(2):108–19.
29) Kagola O, Khau M. Using collages to change school governing body perceptions of male foundation phase teachers. Educ Res Soc Chang. 2020;9(2).
30) Dzyabura D, Peres R. Visual Elicitation of Brand Perception. J Mark. 2021;85(4).
31) Li JPO, Liu H, Ting DSJ, Jeon S, Chan RVP, Kim JE, et al. Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective. Vol. 82, Progress in Retinal and Eye Research. 2021.
32) Suppan M, Stuby L, Carrera E, Cottet P, Koka A, Assal F, et al. Asynchronous Distance Learning of the National Institutes of Health Stroke Scale during the COVID-19 Pandemic (E-Learning vs Video): Randomized Controlled Trial. J Med Internet Res. 2021;23(1).
33) Ismaili Y. Evaluation of students’ attitude toward distance learning during the pandemic (Covid-19): a case study of ELTE university. Horiz. 2020;29(1).
34) Nichols M. A theory for eLearning. Vol. 6, Educational Technology and Society. 2003.
35) Ulrich F, Helms NH, Frandsen UP, Rafn AV. Learning effectiveness of 360° video: experiences from a controlled experiment in healthcare education. Interact Learn Environ. 2021;29(1).
36) Wang YH. Exploring the effectiveness of adopting anchor-based game learning materials to support flipped classroom activities for senior high school students. Interact Learn Environ. 2021;29(3).
37) Kelly RF, Mihm-Carmichael M, Hammond JA. Students’ engagement in and perceptions of blended learning in a clinical module in a veterinary degree program. J Vet Med Educ. 2021;48(2).
38) Song BK. E-portfolio implementation: Examining learners’ perception of usefulness, self-directed learning process and value of learning. Australas J Educ Technol. 2021;37(1).
39) Zhou Z, Wang Z, Yu H, Liao H, Mumtaz S, Oliveira L, et al. Learning-Based URLLC-Aware Task Offloading for Internet of Health Things. IEEE J Sel Areas Commun. 2021;39(2).
40) Alizadehsani R, Khosravi A, Roshanzamir M, Abdar M, Sarrafzadegan N, Shafie D, et al. Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020. Vol. 128, Computers in Biology and Medicine. 2021.
41) Mujal GN, Taylor ME, Fry JL, Gochez-Kerr TH, Weaver NL. A Systematic Review of Bystander Interventions for the Prevention of Sexual Violence. Vol. 22, Trauma, Violence, and Abuse. 2021.
42) Wand APF, Draper B, Brodaty H, Hunt GE, Peisah C. Evaluation of an Educational Intervention for Clinicians on Self-Harm in Older Adults. Arch Suicide Res. 2021;25(1).
43) McCallum S, Milner MM. The effectiveness of formative assessment: student views and staff reflections. Assess Eval High Educ. 2021;46(1).
44) Sujitha B, Parvathy VS, Lydia EL, Rani P, Polkowski Z, Shankar K. Optimal deep learning based image compression technique for data transmission on industrial Internet of things applications. Trans Emerg Telecommun Technol. 2021;32(7).
45) Wang ZY, Zhang LJ, Liu YH, Jiang WX, Jia JY, Tang SL, et al. The effectiveness of E-learning in continuing medical education for tuberculosis health workers: a quasi-experiment from China. Infect Dis Poverty. 2021;10(1).
46) Tian H, Ren D, Li K, Zhao Z. An adaptive update model based on improved Long Short Term Memory for online prediction of vibration signal. J Intell Manuf. 2021;32(1).
47) Tang KY, Chang CY, Hwang GJ. Trends in artificial intelligence-supported e-learning: a systematic review and co-citation network analysis (1998–2019). Interactive Learning Environments. 2021.
48) Gope P, Gheraibia Y, Kabir S, Sikdar B. A Secure IoT-Based Modern Healthcare System with Fault-Tolerant Decision Making Process. IEEE J Biomed Heal Informatics. 2021;25(3).
49) Shi J, Miskin N, Dabiri BE, DeSimone AK, Schaefer PM, Matalon SA, et al. Beyond business as usual: Radiology residency educational response to the COVID-2019 pandemic. Vol. 69, Clinical Imaging. 2021.
50) DePietro DM, Santucci SE, Harrison NE, Kiefer RM, Trerotola SO, Sudheendra D, et al. Medical Student Education During the COVID-19 Pandemic: Initial Experiences Implementing a Virtual Interventional Radiology Elective Course. Acad Radiol. 2021;28(1).
51) Sun PC, Tsai RJ, Finger G, Chen YY, Yeh D. What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Comput Educ. 2008;50(4):1183–202.
52) Hong D, Gao L, Yokoya N, Yao J, Chanussot J, Du Q, et al. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification. IEEE Trans Geosci Remote Sens. 2021;59(5).
53) Imran SM, Malik BA. Evaluation of e-learning web-portals. DESIDOC J Libr Inf Technol. 2017;37(3).
54) Grabowski E, Alten F, Termühlen J, Heiduschka P, Brücher V, Eter N, et al. Analysis of the importance of e-learning in ophthalmology and evaluation of an e-learning app. Ophthalmologe. 2020;117(12).
55) Zhang W, Cheng YL. Quality assurance in e-learning: PDPP evaluation model and its application. Int Rev Res Open Distance Learn. 2012;13(3).
56) Barteit S, Guzek D, Jahn A, Bärnighausen T, Jorge MM, Neuhann F. Evaluation of e-learning for medical education in low- and middle-income countries: A systematic review. Comput Educ. 2020;145.
57) Hao Y, Borich G. A practical guide to evaluate quality of online courses. In: Handbook of Research on Human Performance and Instructional Technology. 2009.
58) Garad A, Al-Ansi AM, Qamari IN. The role of e-learning infrastructure and cognitive competence in distance learning effectiveness during the covid-19 pandemic. Cakrawala Pendidik. 2021;40(1).
59) Demirci MDS, Adan A. Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection. PeerJ. 2020;2020(6).
60) Sarid M, Peled Y, Vaknin-Nusbaum V. The relationship between second language college students’ perceptions of online feedback on draft-writing and academic procrastination. Read Writ. 2021;34(5).
61) Humeniuk I, Kuntso O, Popel N, Voloshchuk Y. MASTERING LISTENING COMPREHENSION AT ESP CLASSES USING TED TALKS. Adv Educ. 2021;8(18).
62) Pennell NA, Dillmon M, Levit LA, Allyn Moushey E, Alva AS, Blau S, et al. American society of clinical oncology road to recovery report: Learning from the covid-19 experience to improve clinical research and cancer care. J Clin Oncol. 2021;39(2).
63) Müller AM, Goh C, Lim LZ, Gao X. Covid-19 emergency elearning and beyond: Experiences and perspectives of university educators. Educ Sci. 2021;11(1).
64) Mitra NK, Aung HH, Kumari M, Perera J, Sivakumar A, Singh A, et al. Improving the learning process in anatomy practical sessions of chiropractic program using e-learning tool. Transl Res Anat. 2021;23.
65) Silva PG de B, de Oliveira CAL, Borges MMF, Moreira DM, Alencar PNB, Avelar RL, et al. Distance learning during social seclusion by COVID-19: Improving the quality of life of undergraduate dentistry students. Eur J Dent Educ. 2021;25(1).
66) Reynisson B, Alvarez B, Paul S, Peters B, Nielsen M. NetMHCpan-4.1 and NetMHCIIpan-4.0: Improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Res. 2021;48(W1).
67) Swords C, Bergman L, Wilson-Jeffers R, Randall D, Morris LL, Brenner MJ, et al. Multidisciplinary Tracheostomy Quality Improvement in the COVID-19 Pandemic: Building a Global Learning Community. Ann Otol Rhinol Laryngol. 2021;130(3).
68) Arifin AJ, Correa RJM, Goodman CD, Laba J, Dinniwell RE, Palma DA, et al. Remote contouring and virtual review during the covid-19 pandemic (Recovr-covid19): Results of a quality improvement initiative for virtual resident training in radiation oncology. Curr Oncol. 2021;28(4).
69) Smajic H, Duspara T. Education 4.0: An Remote Approach for Training of Intelligent Automation and Robotic During COVID19. TH Wildau Eng Nat Sci Proc. 2021;1.
70( Luu NN, Yver CM, Douglas JE, Tasche KK, Thakkar PG, Rajasekaran K. Assessment of YouTube as an Educational Tool in Teaching Key Indicator Cases in Otolaryngology During the COVID-19 Pandemic and Beyond: Neck Dissection. J Surg Educ. 2021;78(1).
71) Pinilla S, Cantisani A, Klöppel S, Strik W, Nissen C, Huwendiek S. Curriculum development with the implementation of an open-source learning management system for training early clinical students: An educational design research study. Adv Med Educ Pract. 2021;12.
72) Hibbi FZ, Abdoun O, Khatir H El. Coronavirus pandemic in Morocco: Measuring the impact of containment and improving the learning process in higher education. Int J Inf Educ Technol. 2020;11(1).
73) Pérez-Sanagustín M, Sapunar-Opazo D, Pérez-Álvarez R, Hilliger I, Bey A, Maldonado-Mahauad J, et al. A MOOC-based flipped experience: Scaffolding SRL strategies improves learners’ time management and engagement. Comput Appl Eng Educ. 2021;29(4).
74)Yuan X, Li L, Shardt YAW, Wang Y, Yang C. Deep Learning with Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development. IEEE Trans Ind Electron. 2021;68(5).
75) Leelavathy S, Nithya M. Public opinion mining using natural language processing technique for improvisation towards smart city. Int J Speech Technol. 2021;24(3).
76) Patil D, Naqvi WM. COVID-19 and education system: Impact of current pandemic on adaptive learning strategies in medical education system. Int J Res Pharm Sci. 2020;11(Special Issue 1).
77) Fisher R, Perényi Á, Birdthistle N. The positive relationship between flipped and blended learning and student engagement, performance and satisfaction. Act Learn High Educ. 2021;22(2).
78) Hilman I. ADVANTAGE OF MAP AS GEOGRAPHY LEARNING MEDIA TO ENHANCE STUDENTS SPATIAL INTELLIGENCE. Int J GEOMATE. 2020;18(68).
79) Li F, Lu H, Hou M, Cui K, Darbandi M. Customer satisfaction with bank services: The role of cloud services, security, e-learning and service quality. Technol Soc. 2021;64.
80) Mailizar M, Burg D, Maulina S. Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies. 2021.
81) Bautista AS, Lissen ES. E-learning in 15 days. Challenges and renovations in Primary and Secondary Education of the Republic of Croatia during the COVID-19 crisis. How have we Introduced distance Learning? Rev Esp Educ Comp. 2020;(36).
82) Moore JL, Dickson-Deane C, Galyen K. e-Learning, online learning, and distance learning environments: Are they the same? Internet High Educ. 2011 Mar 1;14(2):129–35.
83) Hamdi G, Zaghdoudi A, Frikha MT, Makhlouf M, Sassi K, Ben Badr M, et al. Acute abdominal syndrome revealing an intestinal amoebiasis: Report of two cases in Tunisia. Int J Surg Case Rep. 2021;79.
84) Yumnam R. E-learning: An effective mode of teaching English as a Second Language. J Transl Lang Stud. 2021;2(2).
85) Regmi K, Jones L. A systematic review of the factors - Enablers and barriers - Affecting e-learning in health sciences education. Vol. 20, BMC Medical Education. 2020.
86) Abdollahi, M. H., gholami torksaluye, S., abbasian, M. Developing a model of effective factors in the effectiveness of virtual education in general physical education lessons in corona pandemic conditions. Research on Educational Sport, 2022; 9(25): 89-110. doi: 10.22089/res.2021.10469.2092
87) Zareisaroukolaei, M., Shams, G., Rezaeizadeh, M., ghahremani, M. Determinants of e-learning effectiveness: A qualitative study on the instructor. Research in Teaching, 2020; 8(2): 79-55. doi: https://doi.org/10.34785/J012.2020.124
88) Mohammadi Chemardani, H., Rahmani, M. Identifying effective factors in the success of electronic training courses (mixed research). Journal of Educational Scinces, 2019; 26(1): 137-154. doi: 10.22055/edus.2019.27633.2677
89) Lincoln YS, Guba EG, Pilotta JJ. Naturalistic inquiry: Beverly Hills. Int J Intercult Relations. 1985;9(4).
90) Lincoln YS, Guba EG, Pilotta JJ. Naturalistic inquiry: Beverly Hills, CA: Sage Publications, 1985, 416 pp., $25.00 (Cloth). Int J Intercult Relations. 1985;9(4).
91) Braun V, Clarke V. Braun, V ., Clarke, V .Using thematic analysis in psychology., 3:2 (2006), 77-101. Qual Res Psychol. 2006;3.
