An Learning Management Systems (LMS) is important in boosting knowledge acquisition and information management in the digital world. This investigation examines factors affecting students' satisfaction with each aspect of the LMS instructional content, interaction, and accessibility. Using a quantitative research design, data was collected through an online survey from 104 undergraduate students at Universitas Pendidikan Indonesia. The results showed that over half of the participants were satisfied or highly satisfied with LMS features such as interaction, accessibility, and instructional content. 89.4% of students were satisfied with direct communication from the LMS in interaction. When asked about accessibility, 99% of respondents praised the platform's flexibility and ease of use. For the instructional component, 90 percent of students expressed satisfaction with the quality and accessibility of the materials provided. These findings are significant for educational institutes to enhance learning management system features as per user requirements, enabling more flexible and interactive learning approaches. Research related to learning management systems introduced at a tertiary institution to improve learning effectiveness during the pre- and post-COVID-19 period requires deep analysis, including different particulars shaped in the higher education landscape by the impact of the pandemic. This study significantly contributes to developing technology-based education policies in the digital age.

Aguilera-Hermida, A., Quiroga-Garza, A., Gómez-Mendoza, S., Villanueva, C., Avolio, B., & Avcı, D. (2021). Comparison of students’ use and acceptance of emergency online learning due to COVID-19 in the USA, Mexico, Peru, and Turkey. Education and Information Technologies, 26(6), 6823-6845. https://doi.org/10.1007/s10639-021-10473-8

Aguilera-Hermida, A., Quiroga-Garza, A., Gómez-Mendoza, S., Villanueva, C., Avolio, B., & Avcı, D. (2021). Comparison of students’ use and acceptance of emergency online learning due to COVID-19 in the USA, Mexico, Peru, and Turkey. Education and Information Technologies, 26(6), 6823-6845. https://doi.org/10.1007/s10639-021-10473-8

Akbar, M. A., Sang, J., Khan, A. A., Mahmood, S., Qadri, S. F., Hu, H., & Xiang, H. (2019). Success factors influencing requirements change management process in global software development. Journal of Computer Languages, 51(1), 1121130. https://doi.org/10.1016/j.cola.2018.12.005

Aldossari, S. M., & Chen, K. C. (2019). Machine learning for wireless communication channel modeling: An overview. Wireless Personal Communications, 106(1), 41–70. https://doi.org/10.1007/s11277-019-06275-4

Alharbi, S., & Drew, S. (2014). Using the technology acceptance model in understanding academics’ behavioral intention to use learning management systems. International Journal of Advanced Computer Science and Applications, 5(1), 143–155. https://doi.org/10.1016/j.cola.2018.12.005

Ali, Q., Abbas, A., Raza, A., Khan, M., Zulfiqar, H., Iqbal, M., et al. (2023). Exploring the students’ perceived effectiveness of online education during the COVID-19 pandemic: empirical analysis using structural equation modeling (SEM). Behavioral Sciences, 13(7), 578. https://doi.org/10.3390/bs13070578

Ali, Q., Abbas, A., Raza, A., Khan, M., Zulfiqar, H., Iqbal, M., et al. (2023). Exploring the students’ perceived effectiveness of online education during the COVID-19 pandemic: empirical analysis using structural equation modeling (SEM). Behavioral Sciences, 13(7), 578. https://doi.org/10.3390/bs13070578

Al-Mamary, Y. H. S. (2019). Measuring Information Systems Success In Yemen: Potential Of Delone And Mcleans Model. International Journal of Scientific & Technology Research, 8(7), 793–799.

Al-Mamary, Y. H. S. (2020). Using Structural Equation Modeling Approach to Investigate the Impact of Technological Factors on User Satisfaction. Quality access to Success. Calitatea, 21(178), 90–95. https://www.researchgate.net/publication/343389680_Using_Structural_Equation_Modeling_Approach_to_Investigate_the_Impact_of_Technological_Factors_on_User_Satisfaction

Al-Mamary, Y. H. S. (2022). Examining the factors affecting the use of ICT in teaching in Yemeni schools. Journal of Public Affairs, 22(1), e2330. https://doi.org/10.1002/pa.2330

Al-Mamary, Y. H. S., Abdulrab, M., Alwaheeb, M. A., & Alshammari, N. G. M. (2020). Factors impacting entrepreneurial intentions among university students in Saudi Arabia: testing an integrated model of TPB and EO. Education+Training. https://doi.org/10.1108/ET-04-2020-0096

Al-Mamary, Y. H. S., Al-Nashmi, M. M., Shamsuddin, A., & Abdulrab, M. (2019). Development of an integrated model for successful adoption of management information systems in yemeni telecommunication organizations. International Journal of Scientific & Technology Research, 8(11), 3912–3939. http://www.ijstr.org/final-print/nov2019/Development-Of-An-Integrated-Model-For-Successful-Adoption-Of-Management-Information-Systems-In-Yemeni-Telecommunication-Organizations.pdf#

Al-Mamary, Y. H., & Shamsuddin, A. (2015). Testing of the technology acceptance model in context of Yemen. Mediterranean Journal of Social Sciences, 6(4), 268–269. https://doi.org/10.5901/mjss.2015.v6n4s1p268

Al-Mamary, Y. H., Abdulrab, M., Jazim, F., Khan, I., & Al-Ghurbani, A. M. (2021). Factors influencing the use of technology in higher education in Saudi Arabia: A conceptual framework and future research directions. Journal of Public Affairs, 7(5), 2683- 2695. https://doi.org/10.1002/pa.2683

Al-Mamary, Y. H., Shamsuddin, A., Hamid, N. A. Al-Maamari, & Mohammed, Hasan (2015). Adoption of Management Information Systems in Context of Yemeni Organizations: A Structural Equation Modeling Approach. Journal of Digital Information Management, 13(9), 429–444. https://www.researchgate.net/publication/293653734_Adoption_of_Management_Information_Systems_in_Context_of_Yemeni_Organizations_A_Structural_Equation_Modeling_Approach

Almusharraf, N., & Khahro, S. (2020). Students’ satisfaction with online learning experiences during the COVID-19 pandemic. International Journal of Emerging Technologies in Learning, 15(21), 246. https://doi.org/10.3991/ijet.v15i21.15647

Alshehri, A., Rutter, M. J., & Smith, S. (2020). The effects of UTAUT and usability qualities on students’ use of learning management systems in Saudi tertiary education. Journal of Information Technology Education Research, 19(8), 891. https://doi.org/10.28945/4659

Aristovnik, A., Kerˇziˇc, D., Ravˇselj, D., Tomaˇzeviˇc, N., & Umek, L. (2020). Impacts of the COVID-19 pandemic on life of higher education students: A global perspective. Sustainability (Switzerland), 12(20), 1–34. https://doi.org/10.3390/su12208438

Auliana, R. (2023). The factors that influence student satisfaction during online learning on the subject of culinary in the bachelor of applied culinary program of UNY. Pedagogia Jurnal Pendidikan, 13(1), 43-55. https://doi.org/10.21070/pedagogia.v13i1.1539

Birru, M. S., Monaco, V. M., Charles, L., Drew, H., Njie, V., Bierria, T., & Steinman, R. A. (2004). Internet usage by low-literacy adults seeking health information: An observational analysis. Journal of Medical Internet Research, 6(3), 25- 38. https://doi.org/10.2196/jmir.6.3.e25

Boulton, C. A., Kent, C., & Williams, H. T. (2018). Virtual learning environment engagement and learning outcomes at a ‘bricks-and-mortar’ university. Computers & Education, 126, 129–142. https://doi.org/10.1016/j.compedu.2018.06.031

Chakraborty, P., Mittal, P., Gupta, M., Yadav, S., & Arora, A. (2020). Opinion of students on online education during the COVID‐19 pandemic. Human Behavior and Emerging Technologies, 3(3), 357-365. https://doi.org/10.1002/hbe2.240

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of Applied Social Psychology, 22(14), 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x

Delahunty, J., Verenikina, I., & Jones, P. (2014). Socio-emotional connections: Identity, belonging and learning in online interactions. A literature review. Technology, Pedagogy and Education, 23(2), 243- 265. https://doi.org/10.1080/1475939X.2013.813405

Dringus, L. P., & Seagull, A. B. (2015). A five-year study of sustaining blended learning initiatives to enhance academic engagement in computer and information sciences campus courses. In Blended learning: Research perspectives. Vol. 2. Edited by A. G. Picciano, C. D. Dziuban, and C. R. Graham, 122-140. Routledge.

Dziuban, C., & Moskal, P. (2011). A course is a course is a course: Factor invariance in student evaluation of online, blended and face-to-face learning environments. The Internet and Higher Education, 14(4), 236–241. https://doi.org/10.1016/j.iheduc.2011.05.003

Edginton, A., & Holbrook, J. (2010). A blended learning approach to teaching basic pharmacokinetics and the significance of face-to-face interaction. American Journal of Pharmaceutical Education, 74(5), 88. https://doi.org/10.5688/aj740588

Fidalgo, P., Thormann, J., Kulyk, O., & Lencastre, J. A. (2020). Students’ perceptions on distance education: A multinational study. International Journal of Educational Technology. Higher Education, 17(1), 346- 360. https://doi.org/10.1186/s41239-020-00194-2

Fung, H., & Yuen, A. (2012). Factors affecting students’ and teachers’ use of LMS–Towards a holistic framework. In International conference on hybrid learning (pp. 306–316). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-32018-7_29

Hamid, S., Zaki, H., & Senik, Z. (2022). Students’ satisfaction and intention to continue online learning during the COVID-19 pandemic. Malaysian Journal of Society and Space, 18(3). https://doi.org/10.17576/geo-2022-1803-09

Hasan, N., & Bao, Y. (2020). Impact of “e-Learning crack-up” perception on psychological distress among college students during COVID-19 pandemic: A mediating role of “fear of academic year loss”. Children and Youth Services Review, 118(2), 110- 123. https://doi.org/10.1016/j.childyouth.2020.105355

Hațegan, C., Hodorogea, A., Talaş, D., Milevoj, K., Petrović, B., Sivickiene, R., et al. (2022). Students’ satisfaction with online learning at the beginning of the SARS-CoV-2 pandemic. Journal of Educational Sciences & Psychology, 12(74)(1), 10-23. https://doi.org/10.51865/jesp.2022.1.03

Holmes, N. (2018). Engaging with assessment: Increasing student engagement through continuous assessment. Active Learning in Higher Education, 19(1), 23–34. https://doi.org/10.1177/1469787417723230

Hung, L. (2021). Enhancing learners’ satisfaction to improve retention in online classes: current practices at a center of foreign languages in Vietnam. European Journal of Open Education and E-Learning Studies, 6(2). https://doi.org/10.46827/ejoe.v6i2.3936

Hussein, E., Daoud, S., Alrabaiah, H., & Badawi, R. (2020). Exploring undergraduate students’ attitudes towards emergency online learning during COVID-19: A case from the UAE. Children and Youth Services Review, 119(3), 105699- 105720. https://doi.org/10.1016/j.childyouth.2020.105699

Jiang, H., Islam, A., Gu, X., & Spector, J. (2021). Online learning satisfaction in higher education during the COVID-19 pandemic: A regional comparison between Eastern and Western Chinese universities. Education and Information Technologies, 26(6), 6747-6769. https://doi.org/10.1007/s10639-021-10519-x

Jovanovi´c, J., Gaˇsevi´c, D., Dawson, S., Pardo, A., & Mirriahi, N. (2017). Learning analytics to unveil learning strategies in a flipped classroom. Internet and Higher Education, 33, 74–85. https://doi.org/10.1016/j.iheduc.2017.02.001

Kapasia, N., Paul, P., Roy, A., Saha, J., Zaveri, A., Mallick, R., & Chouhan, P. (2020). Impact of lockdown on learning status of undergraduate and postgraduate students during COVID-19 pandemic in West Bengal. India. Children and Youth Services Review, 116 (8), 105194- 105210. https://doi.org/10.1016/j.childyouth.2020.105194

Khan, I., Khan, N., Jazim, F., Al-Mamary, Y. H., Abdulrab, M., & Al-Ghurbani, A. M. (2021). The effect of external factors in use of technology among Ha’il university academic faculty: evidence from Saudi Arabia. Journal of Applied Research in Higher Education. https://doi.org/10.1108/JARHE-04-2021-0140

Korkealehto, K., Lakkala, M., & Toom, A. (2021). Enrolled or engaged? Students’ perceptions of engagement and oral interaction in a blended learning language course. The JALT CALL Journal, 17(1), 1-22. https://doi.org/10.29140/jaltcall.v17n1.268

Kujur, F., & Singh, S. (2017). Engaging customers through online participation in social networking sites. Asia Pacific Management Review, 22(1), 16- 24. https://doi.org/10.1016/j.apmrv.2016.10.006

Lalitha, T. B., & Sreeja, P. S. (2020). Personalised self-directed learning recommendation system. Procedia Computer Science, 171, 583–592. https://doi.org/10.1016/j.procs.2020.04.063

Lavrakas, P.J. (2008). Encyclopedia of Survey Research Methods. Sage. https://doi.org/10.4135/9781412963947

Lazar, J., & Jaeger, P. (2011). Reducing barriers to online access for people with disabilities. Issues in Science and Technology, 27(2), 69- 83.

Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3), 1–47. https://doi.org/10.1177/016146811311500307

Mishra, L., Gupta, T., & Shree, A. (2020). Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. International Journal of Educational Research Open, 1, 100012. https://doi.org/10.1016/j.ijedro.2020.100012

Moskal, P., Dziuban, C., & Hartman, J. (2013). Blended learning: A dangerous idea? The Internet and Higher Education, 18(4), 15–23. https://doi.org/10.1016/j.iheduc.2012.12.001

Musa, M. A., & Othman, M. S. (2012). Critical success factor in e-learning: An ex- amination of technology and student factors. International Journal of Advances in Engineering & Technology, 3(2), 2231- 1963. https://www.researchgate.net/publication/235966913_CRITICAL_SUCCESS_FACTOR_IN_E-LEARNING_AN_EXAMINATION_OF_TECHNOLOGY_AND_STUDENT_FACTORS

Ndegeya, R. M. (2019). Comparison of learning management systems. available at http://urn.fi/URN:NBN:fi:amk-2019061016388.

Nguyen, N. T. (2019). Optimizing factors for accuracy of forecasting models in food processing industry: A context of cacao manufacturers in Vietnam. Industrial Engineering & Management Systems, 18(4), 808- 824. https://doi.org/10.7232/iems.2019.18.4.808

Nguyen, N. T. (2020). Performance evaluation in strategic alliances: A case of Vietnamese construction industry. Global Journal of Flexible Systems Management, 21(1), 85- 99. https://doi.org/10.1007/s40171-019-00230-9

Nguyen, N. T., & Tran, T. T. (2019). Raising opportunities in strategic alliance by evaluating efficiency of logistics companies in Vietnam: A case of cat lai port. Neural Computing & Applications, 31 (11), 7963-7974. https://doi.org/10.1007/s00521-018-3639-2

Nguyen, N. T., Tran, T. T., Wang, C. N., & Nguyen, N. T. (2015). Optimization of strategic alliances by integrating DEA and grey model. Journal of Grey System, 27 (1), 38- 49.

Nizam Ismail, S., Hamid, S., Ahmad, M., Alaboudi, A., & Jhanjhi, N (2021). Exploring students engagement towards the learning management system (LMS) using learning analytics. Computer Systems Science and Engineering, 37(1), 73–87. https://doi.org/10.32604/csse.2021.015261

Paudel, P. (2020). Online education: benefits, challenges and strategies during and after COVID-19 in higher education. International Journal on Studies in Education, 3(2), 70-85. https://doi.org/10.46328/ijonse.32

Paudel, P. (2020). Online education: benefits, challenges and strategies during and after COVID-19 in higher education. International Journal on Studies in Education, 3(2), 70-85. https://doi.org/10.46328/ijonse.32

Petrina, S. (2004). Sidney Pressey and the automation of education, 1924-1934. Technology and Culture, 45(2), 305- 330. https://doi.org/10.1353/tech.2004.0085

Praetorius, A.-K., Klieme, E., Herbert, B., & Pinger, P. (2018). Generic dimensions of teaching quality: The German framework of the three basic dimensions. ZDM Mathematics Education, 50(2), 407–426. https://doi.org/10.1007/s11858-018-0918-4

Puljak, L., Čivljak, M., Haramina, A., Mališa, S., Čavić, D., Klinec, D., et al. (2020). Attitudes and concerns of undergraduate university health sciences students in Croatia regarding complete switch to e-learning during COVID-19 pandemic: a survey. BMC Medical Education, 20(1). https://doi.org/10.1186/s12909-020-02343-7

Puljak, L., Čivljak, M., Haramina, A., Mališa, S., Čavić, D., Klinec, D., et al. (2020). Attitudes and concerns of undergraduate university health sciences students in Croatia regarding complete switch to e-learning during COVID-19 pandemic: a survey. BMC Medical Education, 20(1). https://doi.org/10.1186/s12909-020-02343-7

Rasoft Inc. (1997). Reproduced from how to plan and implement a successful survey. Windermere.

Rovai, A. P., & Jordan, H. M. (2004). Blended learning and sense of community: A comparative analysis with traditional and fully online graduate courses. International Review of Research in Open and Distance Learning, 5(2), 1–13. https://doi.org/10.19173/irrodl.v5i2.192

Simamora, R. (2020). The challenges of online learning during the COVID-19 pandemic: An essay analysis of performing arts education students. Studies in Learning and Teaching, 1(2), 86-103. https://doi.org/10.46627/silet.v1i2.38

Strain-Moritz, T. E. (2016). Perceptions of Technology Use and Its Effects on Student Writing. Culminating Projects in Teacher Development. 8. https://repository.stcloudstate.edu/ed_etds/8

Swan, K. (2001). Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education, 22(2), 306- 331. https://doi.org/10.1080/0158791010220208

SWARGIARY, K. (2023). The COVID-19 pandemic and online education revolution: a comprehensive survey. https://doi.org/10.20944/preprints202311.1390.v3

Sweetman, D. S. (2021). Making virtual learning engaging and interactive. FASEB BioAdvances, 3(1), 11–19. https://doi.org/10.1096/fba.2020-00084

Trevisan, O., Rossi, M., Christensen, R., Knezek, G., & Smits, A. (2023). Factors shaping faculty online teaching competencies during the COVID-19 pandemic. Educational Technology Research and Development. https://doi.org/10.1007/s11423-023-10197-1

Trevisan, O., Rossi, M., Christensen, R., Knezek, G., & Smits, A. (2023). Factors shaping faculty online teaching competencies during the COVID-19 pandemic. Educational Technology Research and Development. https://doi.org/10.1007/s11423-023-10197-1

Ustun, A. B., Karaoglan Yilmaz, F. G., & Yilmaz, R. (2021). Investigating the role of accepting learning management system on students’ engagement and sense of community in blended learning. Education and Information Technologies, 26. https://doi.org/10.1007/s10639-021-10500-8

van Merri¨enboer, J. J. G., & Sluijsmans, D. M. A. (2009). Toward a synthesis of cognitive load theory, four-component instructional design, and self-directed learning. Educational Psychology Review, 21(1), 55–66. https://doi.org/10.1007/s10648-008-9092-5

Vargo, D., Zhu, L., Benwell, B., & Yan, Z. (2020). Digital technology use during COVID‐19 pandemic: A rapid review. Human Behavior and Emerging Technologies, 3(1), 13-24. https://doi.org/10.1002/hbe2.242

Vargo, D., Zhu, L., Benwell, B., & Yan, Z. (2020). Digital technology use during COVID‐19 pandemic: a rapid review. Human Behavior and Emerging Technologies, 3(1), 13-24. https://doi.org/10.1002/hbe2.242

Wang, C. N., Nguyen, N. T., & Tran, T. T. (2015). Integrated DEA models and grey system theory to evaluate past-to-future performance: A case of Indian electricity industry. Science World Journal, 3(26), 638710- 638723. https://doi.org/10.1155/2015/638710

Yu, Q. (2022). Factors influencing online learning satisfaction. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.852360