Designing a Cloud-Based Ubiquitous Learning Environment for a Hybrid University Language Course

Aom Thai (1), Rit Som (2), Ming Kiri (3), Rustiyana Rustiyana (4)
(1) Srinakharinwirot University, Thailand,
(2) Songkhla University, Thailand,
(3) Asia Commercial Bank, Cambodia,
(4) Universitas Bale Bandung, Indonesia

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

Authors

Aom Thai
aomthai@gmail.com (Primary Contact)
Rit Som
Ming Kiri
Rustiyana Rustiyana
Thai, A., Som, R., Kiri, M., & Rustiyana, R. (2025). Designing a Cloud-Based Ubiquitous Learning Environment for a Hybrid University Language Course. International Journal of Language and Ubiquitous Learning, 3(6), 270–280. https://doi.org/10.70177/ijlul.v3i6.2846

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