EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 576 (2024) E3S Web Conf., 576 (2024) 01004 References
Open Access
Issue
E3S Web Conf.
Volume 576, 2024
The 13th Engineering International Conference “Sustainable Development Through Green Engineering and Technology” (EIC 2024)
Article Number 01004
Number of page(s) 13
Section Energy Management System
DOI https://doi.org/10.1051/e3sconf/202457601004
Published online 03 October 2024
  1. Ruzieva, D., Sodikov, U., Mukhlisov, S.: Research of human-computer interaction in the modern education system. In: AIP Conference Proceedings. AIP Publishing (2023). [Google Scholar]
  2. Kosch, T., Karolus, J., Zagermann, J., Reiterer, H., Schmidt, A., Woźniak, P.W.: A survey on measuring cognitive workload in human-computer interaction. ACM Comput Surv. (2023). [Google Scholar]
  3. AL-Sayid, F., Kirkil, G.: Students’ web-based activities moderate the effect of humancomputer-interaction factors on their E-Learning acceptance and success during COVID-19 pandemic. Int J Hum Comput Interact. 39, 2852–2875 (2023). [CrossRef] [Google Scholar]
  4. Alebeisat, F., Altarawneh, H., Alhalhouli, Z.T., Qatawneh, A., Almahasne, M.: The Impact of Human and Computer Interaction on eLearning Quality. International Journal of Interactive Mobile Technologies. 16, (2022). [Google Scholar]
  5. Kaiser, R., Oertel, K.: Emotions in HCI – An Affective E-Learning System. Computer (Long Beach Calif). (2006). [Google Scholar]
  6. Gawande, V., Computer, A.H., Hci, I.: Effective Use of HCI in e-Learning. International Journal. (2009). [Google Scholar]
  7. El Falaki, B., El Faddouli, N.E., Khalidiidrissi, M., Bennani, S.: Individualizing HCI in e-learning through assessment approach. International Journal of Engineering Education. 29, (2013). [Google Scholar]
  8. Panigrahi, R., Srivastava, P.R., Panigrahi, P.K.: Effectiveness of e-learning: the mediating role of student engagement on perceived learning effectiveness. Information Technology & People. 34, 1840–1862 (2021). [CrossRef] [Google Scholar]
  9. Zareisaroukolaei, M., Shams, G., Rezaeizadeh, M., Ghahremani, M.: Determinants of e-learning effectiveness: A qualitative study on the instructor. Research in Teaching. 8, 55–79 (2020). [Google Scholar]
  10. Indriana, Alamsyah, D.P., Othman, N.A.: Toward an E-Learning Adoption: Student Perspectives. In: 2022 International Conference on ICT for Smart Society (ICISS). pp. 1–4 (2022). https://doi.org/10.1109/ICISS55894.2022.9915113. [Google Scholar]
  11. Alipichev, A., Nazarova, L., Shingareva, M., Siman, A.: Improving the credibility of pedagogical diagnostics in E-Learning. In: CEUR Workshop Proceedings. p. 203 (2020). [Google Scholar]
  12. Utomo, S.M., Purnama Alamsyah, D., Hariyanto, O.I.B.: Continuance Intention of ELearning: New Model of Technology Adoption. In: 2022 3rd International Conference on Big Data Analytics and Practices (IBDAP). pp. 85–89 (2022). https://doi.org/10.1109/IBDAP55587.2022.9907354. [Google Scholar]
  13. Alamsyah, D.P., Indriana, Setyawati, I., Rohaeni, H.: New Technology Adoption of ELearning: Model of Perceived Usefulness. In: 2022 3rd International Conference on Big Data Analytics and Practices (IBDAP). pp. 79–84 (2022). https://doi.org/10.1109/IBDAP55587.2022.9907261. [Google Scholar]
  14. Othman, N.A., Alamsyah, D.P., Utomo, S.M.: IT Infrastructure and Perceived Ease of Use to Increase E-Learning Adoption. In: 2022 International Conference on Information Management and Technology (ICIMTech). pp. 89–93 (2022). https://doi.org/10.1109/ICIMTech55957.2022.9915218. [Google Scholar]
  15. Ananga, P.: Pedagogical Considerations of E-Learning in Education for Development in the Face of COVID-19. International Journal of Technology in Education and Science. 4, 310–321 (2020). [CrossRef] [Google Scholar]
  16. Madani, Y., Ezzikouri, H., Erritali, M., Hssina, B.: Finding optimal pedagogical content in an adaptive e-learning platform using a new recommendation approach and reinforcement learning. J Ambient Intell Humaniz Comput. 11, 3921–3936 (2020). [CrossRef] [Google Scholar]
  17. Indriana, Alamsyah, D.P., Hikmawati, N.K.: Model of Expected Benefit, E-Learning Curriculum, and Education Partners on E-Learning. In: 2022 International Conference on Information Management and Technology (ICIMTech). pp. 318–322 (2022). https://doi.org/10.1109/ICIMTech55957.2022.9915129. [Google Scholar]
  18. Alamsyah, D.P., Chang, A., Sudirman, I.D.: The Antecedent of E-Learning Adoption. In: 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS). pp. 1–5. IEEE (2022). [Google Scholar]
  19. Saqr, R.R., Al-Somali, S.A., Sarhan, M.Y.: Exploring the Acceptance and User Satisfaction of AI-Driven e-Learning Platforms (Blackboard, Moodle, Edmodo, Coursera and edX): An Integrated Technology Model. Sustainability (Switzerland). 16, (2024). https://doi.org/10.3390/su16010204. [Google Scholar]
  20. Lee, Y.H., Hsiao, C., Purnomo, S.H.: An empirical examination of individual and system characteristics on enhancing e-learning acceptance. Australasian Journal of Educational Technology. 30, (2014). https://doi.org/10.14742/ajet.381. [CrossRef] [Google Scholar]
  21. Alhabeeb, A., Rowley, J.: E-learning critical success factors: Comparing perspectives from academic staff and students. Comput Educ. 127, (2018). https://doi.org/10.1016/j.compedu.2018.08.007. [CrossRef] [Google Scholar]
  22. Almaiah, M.A., Alyoussef, I.Y.: Analysis of the Effect of Course Design, Course Content Support, Course Assessment and Instructor Characteristics on the Actual Use of E-Learning System. IEEE Access. 7, (2019). https://doi.org/10.1109/ACCESS.2019.2956349. [Google Scholar]
  23. Hsbollah, H.M., Idris, K.M.: E-learning adoption: The role of relative advantages, trialability and academic specialisation. Campus-Wide Information Systems. 26, 54–70 (2009). https://doi.org/10.1108/10650740910921564. [CrossRef] [Google Scholar]
  24. Denan, Z., Munir, Z.A., Razak, R.A., Kamaruddin, K., Sundram, V.P.K.: Adoption of technology on E-learning effectiveness. Bulletin of Electrical Engineering and Informatics. 9, 1121–1126 (2020). [CrossRef] [Google Scholar]
  25. Sigala, M.: Investigating the factors determining e-learning effectiveness in tourism and hospitality education. Journal of Hospitality and Tourism Education. 16, (2004). https://doi.org/10.1080/10963758.2004.10696789. [Google Scholar]
  26. Chavoshi, A., Hamidi, H.: Social, individual, technological and pedagogical factors influencing mobile learning acceptance in higher education: A case from Iran. Telematics and Informatics. 38, (2019). https://doi.org/10.1016/j.tele.2018.09.007. [Google Scholar]
  27. Zhai, X., Shi, L.: Understanding How the Perceived Usefulness of Mobile Technology Impacts Physics Learning Achievement: a Pedagogical Perspective. J Sci Educ Technol. 29, 743–757 (2020). https://doi.org/10.1007/s10956-020-09852-6. [CrossRef] [Google Scholar]
  28. Indriana, Alamsyah, D.P., Othman, N.A.: The Continuance Intention of E-Learning: The Role of Compatibility and Self-Efficacy Technology Adoption. In: 2022 10th International Conference on Cyber and IT Service Management (CITSM). pp. 1–5 (2022). https://doi.org/10.1109/CITSM56380.2022.9935868. [Google Scholar]
  29. Belkhamza, Z., Bin Abdullah, M.M.: Trainee characteristics and organizational environment for enhancing individual performance in e-learning involvement. International Journal of Web-Based Learning and Teaching Technologies. 14, (2019). https://doi.org/10.4018/IJWLTT.2019040106. [Google Scholar]
  30. Tsevis, T., Westman, E., Poulakis, K., Lindberg, O., Badji, A., Religa, D., Wahlund, L.O.: Demographic and Clinical Characteristics of Individuals with Mild Cognitive Impairment Related to Grade of Alcohol Consumption. Dement Geriatr Cogn Disord. 50, (2022). https://doi.org/10.1159/000519736. [Google Scholar]
  31. Purnomo, S.H., Nastiti, T.: Does management support matter in elucidating the linkage of individual characteristics and E-learning acceptance? Asian Academy of Management Journal. 24, (2019). https://doi.org/10.21315/aamj2019.24.1.4. [Google Scholar]
  32. Al-Samarraie, H., Teng, B.K., Alzahrani, A.I., Alalwan, N.: E-learning continuance satisfaction in higher education: a unified perspective from instructors and students. Studies in higher education. 43, 2003–2019 (2018). [CrossRef] [Google Scholar]
  33. Fernando, E., Murad, D.F., Warnars, H.L.H.S., Oktriono, K.: Development Conceptual Model and Validation Instrument for E-Learning Succes Model at Universities in Indonesia: Perspectives influence of Instructor’s Activities and Motivation. In: 2019 International Congress on Applied Information Technology (AIT). pp. 1–6. IEEE (2019). [Google Scholar]
  34. Saputri, M.E., Utami, F.N., Sari, D.: The Effectiveness of E-Learning Service Quality in Influencing E-Learning Student Satisfaction and Loyalty at Telkom University. In: 2022 International Conference Advancement in Data Science, E-learning and Information Systems (ICADEIS). pp. 1–5 (2022). https://doi.org/10.1109/ICADEIS56544.2022.10037454. [Google Scholar]
  35. Utomo, S.M., Alamsyah, D.P., Rohaeni, H., Siswanto, B.: Exploring The Significance of E-Learning Quality, Usefulness, and Effectiveness on Student Intention. In: 2023 International Conference on IoT, Communication and Automation Technology (ICICAT). pp. 1–6 (2023). https://doi.org/10.1109/ICICAT57735.2023.10263649. [Google Scholar]
  36. Lee, J.J., Yoon, H.: A comparative study of technological learning and organizational capability development in complex products systems: Distinctive paths of three latecomers in military aircraft industry. Res Policy. 44, 1296–1313 (2015). https://doi.org/10.1016/j.respol.2015.03.007. [CrossRef] [Google Scholar]
  37. Fernandez, A.I., Al Radaideh, A., Singh Sisodia, G., Mathew, A., Jimber del Río, J.A.: Managing university e-learning environments and academic achievement in the United Arab Emirates: An instructor and student perspective. PLoS One. 17, e0268338 (2022). [CrossRef] [PubMed] [Google Scholar]
  38. Sobaih, A.E.E., Elshaer, I.A.: Personal Traits and Digital Entrepreneurship: A Mediation Model Using SmartPLS Data Analysis. Mathematics. 10, 3926 (2022). [CrossRef] [Google Scholar]
  39. Ringle, C.M., Da Silva, D., Bido, D.D.S.: Structural Equation Modeling with the Smartpls. Revista Brasileira de Marketing. 13, (2014). [Google Scholar]
  40. Surucu, L., Maslakci, A.: Validity and Realibility. Business & Management Studies: An International Journal. 8, (2020). [Google Scholar]
  41. Habiger, J.D., Peña, E.A.: Compound p-value statistics for multiple testing procedures. J Multivar Anal. 126, (2014). https://doi.org/10.1016/j.jmva.2014.01.007. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.