Designing a Cloud-Based Ubiquitous Learning Environment for a Hybrid University Language Course
Abstract
Background. The rise of hybrid learning models in higher education has highlighted the need for flexible, scalable, and context-aware digital learning environments capable of supporting continuous language learning beyond classroom boundaries.
Purpose. This study aims to design and evaluate a cloud-based ubiquitous learning environment tailored for a hybrid university language course to enhance learner autonomy, engagement, and communicative competence.
Method. Employing a design-based research methodology, the study involved iterative cycles of analysis, design, implementation, and evaluation with 42 undergraduate language learners. Data were collected through system usage analytics, pre- and post-course proficiency assessments, and learner experience surveys.
Results. The results indicate significant improvements in vocabulary retention, listening comprehension, and task-based communication skills, accompanied by increased learner satisfaction with the flexibility and responsiveness of the system.
Conclusion. The study concludes that a cloud-based ubiquitous learning environment can meaningfully enhance hybrid language instruction by integrating mobility, accessibility, and real-time support into traditional course structures.
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References
Auer, M. E., Langmann, R., May, D., & Roos, K. (Eds.). (2024a). 21st International Conference on Smart Technologies and Education, STE 2024. Lecture Notes in Networks and Systems, 1028 LNNS. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197409171&partnerID=40&md5=7275192417096229ea3ff780c683bbb4
Auer, M. E., Langmann, R., May, D., & Roos, K. (Eds.). (2024b). 21st International Conference on Smart Technologies and Education, STE 2024. Lecture Notes in Networks and Systems, 1027 LNNS. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196207071&partnerID=40&md5=2c37e3b8873c96d28a98eeeed9f86f8f
Cai, D., Wang, S., Zhang, Z., Lin, F. X., & Xu, M. (2024). SILENCE: Lightweight Protection for Privacy in Offloaded Speech Understanding. In A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, & C. Zhang (Eds.), Adv. Neural inf. Proces. Syst. (Vol. 37). Neural information processing systems foundation; Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000497398&partnerID=40&md5=eb16548174abb4cec9f48c92ca9e34b3
Ch??d, P., & Ogiela, M. R. (2023). Deep Learning and Cloud-Based Computation for Cervical Spine Fracture Detection System. Electronics (Switzerland), 12(9). Scopus. https://doi.org/10.3390/electronics12092056
Dobie, J., & Holder, R. (2024). Network System of Systems Manager. Integr. Commun., Navig. Surveill. Conf., ICNS. Integrated Communications, Navigation and Surveillance Conference, ICNS. Scopus. https://doi.org/10.1109/ICNS60906.2024.10550591
Hamzehei, S., Akbarzadeh, O., Attar, H., Rezaee, K., Fasihihour, N., & Khosravi, M. R. (2023). Predicting the total Unified Parkinson’s Disease Rating Scale (UPDRS) based on ML techniques and cloud-based update. Journal of Cloud Computing, 12(1). Scopus. https://doi.org/10.1186/s13677-022-00388-1
Hui, Z., Cai, Z., Xu, P., Xia, Y., & Cheng, P. (2023). Tree Species Classification Using Optimized Features Derived from Light Detection and Ranging Point Clouds Based on Fractal Geometry and Quantitative Structure Model. Forests, 14(6). Scopus. https://doi.org/10.3390/f14061265
Jha, D. N., Chen, Z., Liu, S., Wu, M., Zhang, J., Morgan, G., Ranjan, R., & Li, X. (2023). A Hybrid Accuracy- and Energy-Aware Human Activity Recognition Model in IoT Environment. IEEE Transactions on Sustainable Computing, 8(1), 1–14. Scopus. https://doi.org/10.1109/TSUSC.2022.3209086
Kathane, K. A., & Sharma, V. K. (2023). Leveraging Graph-Based Analysis and Deep Learning for Dynamic Cloud Forensic Profiling Operations. In D. Goyal, A. Kumar, D. Singh, M. Paprzycki, P. Jain, B. B. Gupta, & U. P. Singh (Eds.), ACM Int. Conf. Proc. Ser. Association for Computing Machinery; Scopus. https://doi.org/10.1145/3647444.3647896
Kim, T., Lee, J., Jung, H., & Kim, S. (2023). AI Accelerators for Standalone Computer. In Artificial Intelligence and Hardw. Accelerators (pp. 53–93). Springer International Publishing; Scopus. https://doi.org/10.1007/978-3-031-22170-5_2
Kline, S. (2023). CGScholar: Promoting reflexive pedagogy in a web-based writing and learning ecosystem. In Promot. Next-Gener. Learn. Environ. Through CGScholar (pp. 206–229). IGI Global; Scopus. https://doi.org/10.4018/978-1-6684-5124-3.ch011
Lee, H.-Y., & Huang, Y.-M. (2024). Bridging STEM Education and Ubiquitous Learning: A Case Study on Developing a LINE Chatbot with Google’s Gemini for Virtual Peer Collaboration. In Y.-P. Cheng, M. Pedaste, E. Bardone, & Y.-M. Huang (Eds.), Lect. Notes Comput. Sci.: Vol. 14786 LNCS (pp. 237–246). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-3-031-65884-6_25
Liu, L., Feng, J., Mu, X., Pei, Q., Lan, D., & Xiao, M. (2023). Asynchronous Deep Reinforcement Learning for Collaborative Task Computing and On-Demand Resource Allocation in Vehicular Edge Computing. IEEE Transactions on Intelligent Transportation Systems, 24(12), 15513–15526. Scopus. https://doi.org/10.1109/TITS.2023.3249745
Matsui, T., Misaki, S., Suwa, H., & Yasumoto, K. (2023). Privacy Filtering Using Word Embedding for 3D Point Cloud Based Spatial Sharing Systems. Int. Conf. Mob. Comput. Ubiquitous Netw., ICMU. Scopus. https://doi.org/10.23919/ICMU58504.2023.10412252
Nkongolo, M., & Tokmak, M. (2023). Zero-Day Threats Detection for Critical Infrastructures. In A. Gerber & M. Coetzee (Eds.), Commun. Comput. Info. Sci.: Vol. 1878 CCIS (pp. 32–47). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-3-031-39652-6_3
Ooi, M. P.-L., Sohail, S., Huang, V. G., Hudson, N., Baughman, M., Rana, O., Hinze, A., Chard, K., Chard, R., Foster, I., Spyridopoulos, T., & Nagra, H. (2023). Measurement and Applications: Exploring the Challenges and Opportunities of Hierarchical Federated Learning in Sensor Applications. IEEE Instrumentation and Measurement Magazine, 26(9), 21–31. Scopus. https://doi.org/10.1109/MIM.2023.10328671
Perakovic, D., & Knapcikova, L. (Eds.). (2025). 8th EAI International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures, FABULOUS 2024. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 596 LNICST. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207667045&partnerID=40&md5=99ec01ae42d871dc11bf0e85711084a5
Prabhu, D., Karthick, R., Sruthi, A., Niroshini Infantia, H. N., Raja, M. G., & Arul Selvan, M. (2025). Deep Learning Algorithms for Cloud-Based IOT Healthcare Systems. Int. Conf. Circuit, Power Comput. Technol., ICCPCT, 935–940. Scopus. https://doi.org/10.1109/ICCPCT65132.2025.11176582
Puertas-Aguilar, M.-Á., García Sipols, A. E. G., & de Lázaro-Torres, M.-L. (2023). Web GIS to Learn Geopolitics in Secondary Education: A case study from Spain. European Journal of Geography, 14(2), 15–31. Scopus. https://doi.org/10.48088/ejg.m.pue.14.2.015.031
Puthal, D., Mohanty, S., & Choi, B.-Y. (Eds.). (2024a). 6th IFIP International Conference on Internet of Things, IFIP IoT 2023. IFIP Advances in Information and Communication Technology, 683 AICT. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177191769&partnerID=40&md5=ebbf1307cd120e8acef7f66ebe278d10
Puthal, D., Mohanty, S., & Choi, B.-Y. (Eds.). (2024b). 6th IFIP International Conference on Internet of Things, IFIP IoT 2023. IFIP Advances in Information and Communication Technology, 684 AICT. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176909594&partnerID=40&md5=646efaae77f117206e8c4a687713f9e0
Ramesh Babu, G., Phaneendra Varma, P. V., Majji, T., Likhitha Hasini, S. S., Hemasri, M., & Prasanthi, M. L. (2023). A Design of an Integrated Intrusion Detection System on Cloud Using DNN. In H. K. Mittal & S. Singla (Eds.), Proc. - Int. Conf. Adv. Comput. Commun. Technol., ICACCTech (pp. 72–80). Institute of Electrical and Electronics Engineers Inc.; Scopus. https://doi.org/10.1109/ICACCTech61146.2023.00021
Shankar, M., Anita Patil, K., Julia Faith, S., Raja, G. V., Suresh, B., Mickle Aancy, H., & Aravind Prasad, B. (2025). Transforming Healthcare Delivery: A Framework for Remote Monitoring and Predictive Analysis Through AI and IoT Technologies. In V. Venkatraman, S. K. T S, & L. C. Chuan (Eds.), AIP Conf. Proc. (Vol. 3270, Issue 1). American Institute of Physics; Scopus. https://doi.org/10.1063/5.0261616
Shi, D., Zhao, J., Wang, Z., Zhao, H., Eze, C., Wang, J., Lian, Y., & Burke, A. F. (2023). Cloud-Based Deep Learning for Co-Estimation of Battery State of Charge and State of Health. Energies, 16(9). Scopus. https://doi.org/10.3390/en16093855
Singh, N. K., Lakhanpal, A., Srivastava, S., Sandhu, K. S., Arya, S., & Tiwari, A. (2024). Ubiquitous intelligent machine learning resource allocation system in IoT. Int. Conf. Augment. Real., Intell. Syst., Ind. Autom., ARIIA. Scopus. https://doi.org/10.1109/ARIIA63345.2024.11051621
Singh, P., Jain, D., Sharma, A. K., Jain, A., & Vats, P. (2023). Cloud-Based Patient Health Information Exchange System Using Blockchain Technology. In M. S. Kaiser, J. Xie, & V. S. Rathore (Eds.), Lect. Notes Networks Syst. (Vol. 401, pp. 569–577). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-981-19-0098-3_55
Sudharsanan, R., Rekha, M., Pritha, N., Gandhi, G., Arokia Nerling Rasoni, G., & Uthayakumar, G. S. (2024). Intruder identification using feed forward encasement-based parameters for cybersecurity along with IoT devices. Measurement: Sensors, 32. Scopus. https://doi.org/10.1016/j.measen.2024.101035
Vettenburg, T., & Valantinas, L. (2024). Scattering on the Cloud: Scaling-up wave physics computations. In K.-I. Kitayama & V. j. Sorger (Eds.), Proc SPIE Int Soc Opt Eng (Vol. 12903). SPIE; Scopus. https://doi.org/10.1117/12.3002884
Wang, J., Chen, P., Wang, J., & Yang, B. (2024). A Hierarchical Federated Learning Paradigm in O-RAN for Resource-Constrained IoT Devices. In M. Valenti, D. Reed, & M. Torres (Eds.), IEEE Int Conf Commun (pp. 3500–3505). Institute of Electrical and Electronics Engineers Inc.; Scopus. https://doi.org/10.1109/ICC51166.2024.10623078