Narratives of Resilience: Exploring Student Stories During Remote Learning in the COVID-19 Pandemic
Article Sidebar
-
COVID-19, Narrative Inquiry, Resilience, Remote Learning, Student Experiences
Abstract
Background. The COVID-19 pandemic forced an abrupt transition from face-to-face instruction to remote learning, exposing students worldwide to significant academic, technological, and psychosocial challenges. Issues related to motivation, engagement, access to digital resources, and emotional well-being became more pronounced, positioning resilience as a crucial determinant of student success in virtual learning environments. Understanding resilience through students’ personal narratives offers valuable insights into how learners adapt, cope, and grow amid educational disruption.
Purpose. This study aimed to explore students’ lived experiences of resilience during remote learning by examining their narratives of adaptation, coping strategies, and personal development in online educational contexts.
Method. A qualitative research design employing narrative inquiry was used. Data were collected from 50 secondary and tertiary students across diverse educational settings through in-depth narrative accounts. The data were analyzed thematically to identify recurring patterns of adaptive behavior, emotional regulation, and problem-solving strategies.
Results. The findings revealed that students demonstrated resilience through proactive time management, creative engagement with digital platforms, peer collaboration, and positive cognitive reframing of challenges. Participants reported enhanced self-directed learning skills, increased autonomy, and improved emotional regulation as outcomes of prolonged remote learning.
Conclusion. The study concludes that resilience plays a vital role in sustaining student engagement and well-being in remote learning environments. Students’ personal narratives highlight the transformative potential of adversity and provide pedagogical insights for designing learning experiences that foster adaptability, motivation, and holistic development.
Full text article
References
Abdullah, N., Zolkafli, A., & Omar, M. (2025). ADVANCEMENTS AND INTEGRATION OF BIOPHYSICAL, SOCIO-ECONOMIC, AND LOCAL KNOWLEDGE IN AGRICULTURAL LAND SUITABILITY ASSESSMENTS: A SYSTEMATIC LITERATURE REVIEW. Mesopotamia Journal of Agriculture, 53(1), 168–192. Scopus. https://doi.org/10.33899/mja.2025.156944.1531
Abdulwahid, W. M., Feizizadeh, B., Blaschke, T., & Karimzadeh, S. (2025). A Geoinformation Approach for Spatiotemporal Mapping of Climate Change Environmental Impacts on Sustainable Food Production in Iraq. International Journal of Environmental Research, 19(5). Scopus. https://doi.org/10.1007/s41742-025-00821-8
Akomea-Frimpong, I., Dzagli, J. R. A. D., Eluerkeh, K., Bonsu, F. B., Opoku-Brafi, S., Gyimah, S., Asuming, N. A. S., Atibila, D. W., & Kukah, A. S. (2025). A systematic review of artificial intelligence in managing climate risks of PPP infrastructure projects. Engineering, Construction and Architectural Management, 32(4), 2430–2454. Scopus. https://doi.org/10.1108/ECAM-01-2023-0016
Al-Mekhlaf, Z. G., Saare, M. A., Mohammed Hachim Altmemi, J. M. H., Al-Shareeda, M. A., Abdulkarem Mohammed, B. A., Alshammari, G., ALRashdi, R., Alkhabra, Y. A., & Alreshidi, I. (2025). A quantum-resilient lattice-based security framework for internet of medical things in healthcare systems. Journal of King Saud University - Computer and Information Sciences, 37(6). Scopus. https://doi.org/10.1007/s44443-025-00140-0
Alnajjar, S., Garcia-Martinez, A., López-Cabeza, V. P., & Al-Azhari, W. (2025). A Multidimensional Approach to Mapping Urban Heat Vulnerability: Integrating Remote Sensing and Spatial Configuration. Smart Cities, 8(4). Scopus. https://doi.org/10.3390/smartcities8040137
Altherwi, A., Ahmad, M. T., Alam, M. M., Mirza, H., Sultana, N., Ali Pasha, A. A., Sultana, N., Khan, A. I., Alam, M. M., & Azim, R. (2025). A hybrid optimization approach for securing cloud-based e-health systems. Multimedia Tools and Applications, 84(16), 16525–16560. Scopus. https://doi.org/10.1007/s11042-024-19688-6
Anees, S. A., Mehmood, K., Luo, M., Abuelgasim, A., Pan, S., Shahzad, F., Muhammad, S., & Khan, W. R. (2025). Advancing forest fire burn severity and vegetation recovery assessments using remote sensing and machine learning approaches. Ecological Informatics, 92. Scopus. https://doi.org/10.1016/j.ecoinf.2025.103446
Badal, T., Nicholson, C., Ayer, J., Cheung, M., Grigg, L., Celermajer, D. S., & Strange, G. (2025). A detailed profiling study from the national Australian Congenital Heart Disease registry: Rationale and design. International Journal of Cardiology Congenital Heart Disease, 21. Scopus. https://doi.org/10.1016/j.ijcchd.2025.100595
Braik, A. M., Han, X., & Koliou, M. (2025). A framework for resilience analysis and equitable recovery in tornado-impacted communities using agent-based modeling and computer vision-based damage assessment. International Journal of Disaster Risk Reduction, 121. Scopus. https://doi.org/10.1016/j.ijdrr.2025.105427
Claudia, C., & BalaAnand, M. (2025). A Novel Deep Learning-Based Soil Moisture Prediction Model Using Adaptive Group Radial Lasso Regularized Basis Function Networks (AGRL-RBFN) Optimized by Hierarchical Correlated Spider Wasp Optimizer (HCSWO) and Incremental Learning (IL). Water (Switzerland), 17(16). Scopus. https://doi.org/10.3390/w17162379
Darko, R. O., Odoi-Yorke, F., Abbey, A. A., Afutu, E., Owusu-Sekyere, J. D., Sam-Amoah, L. K., & Acheampong, L. (2025). A Review of Climate Change Impacts on Irrigation Water Demand and Supply—A Detailed Analysis of Trends, Evolution, and Future Research Directions. Water Resources Management, 39(1), 17–45. Scopus. https://doi.org/10.1007/s11269-024-03964-z
Dias, C. R. G., Neves, A. K., Silva, J. M. N., Ribeiro, N. S., & Pereira, J. M. C. (2025). A landsat-based burned area atlas (2000–2023) for the Niassa Special Reserve, Mozambique using U-Net deep learning. ISPRS Journal of Photogrammetry and Remote Sensing, 230, 147–169. Scopus. https://doi.org/10.1016/j.isprsjprs.2025.09.005
Dong, X., Ye, Y., Su, D., Yi, S., Yang, R., Haase, D., & Lausch, A. (2025). Adaptive ranking of specific tree species for targeted green infrastructure intervention in response to urban hazards. Urban Forestry and Urban Greening, 107. Scopus. https://doi.org/10.1016/j.ufug.2025.128776
Durham, C., Chinnis, S., Stanley, A., Harmon, E., & Stephens, T. (2025). Adaptation, Innovation, and Resilience: Serendipitous Outcomes of a Rapid Transition to Virtual Learning. Journal of Nursing Education, 64(9), 598–601. Scopus. https://doi.org/10.3928/01484834-20241029-03
Garbanzo-León, G., Céspedes, J., Temudo, M., Cameira, M. D. R., Paredes, P., & Ramos, T. (2025). Advances in soil salinity diagnosis for mangrove swamp rice production in Guinea Bissau, West Africa. Science of Remote Sensing, 11. Scopus. https://doi.org/10.1016/j.srs.2025.100231
Ghaffar, Z., Kuo, W.-C., Mahmood, K., Alturki, N., Saleem, M. A., & Bashir, A. K. (2025). A Machine Learning Attack Resilient Authentication Protocol for AI-Driven Consumer Wearable Health Monitoring. IEEE Transactions on Consumer Electronics. Scopus. https://doi.org/10.1109/TCE.2025.3593648
Hadad, S., & Deshen, M. (2025). Adapting to crisis: Assessing teacher self-efficacy, stability, and ICT support within emergency remote teaching and learning environments. Learning Environments Research. Scopus. https://doi.org/10.1007/s10984-025-09539-y
Islam, A., Md Masuduzzaman, M., & Shin, S. Y. (2025). A deep transfer learning-based blockchain-assisted cooperative network architecture for internet of unmanned any vehicle things. Internet of Things (The Netherlands), 32. Scopus. https://doi.org/10.1016/j.iot.2025.101659
Islam, U., Alatawi, M. N., Alqazzaz, A., Alamro, S., Shah, B., & Moreira, F. (2025). A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience. Scientific Reports, 15(1). Scopus. https://doi.org/10.1038/s41598-025-09696-3
Kabinesh, V., Suwethaasri, D., Baranidharan, K., Ravi, R., Tilak, M., Kalpana, M., Ragunath, K. P., Vennila, S., Hemalatha, P., Vijayabhama, M., Bargavi, S., & Eniya, A. (2025). A critical review of exploring the recent trends and technological advancements in forest biomass estimation. Plant Science Today, 12. Scopus. https://doi.org/10.14719/pst.6695
Kanani-Sadat, Y., Safari, A., Nasseri, M., & Homayouni, S. (2025). A novel explainable stacking ensemble model for estimating design floods: A data-driven approach for ungauged regions. Advanced Engineering Informatics, 66. Scopus. https://doi.org/10.1016/j.aei.2025.103429
Li, S., Liu, G., Hu, P., Li, P., Xu, D., & Wang, Z. (2025). Acoustic Sensing for Contactless Health Monitoring: Technologies, Algorithms, and Emerging Applications. IEEE Access, 13, 163907–163935. Scopus. https://doi.org/10.1109/ACCESS.2025.3609787
Meheretu, S. E., Nigussie, E., Gebremeskel, G. B., & Hailesilassie, S. Y. (2025). A Systematic Literature Review on Spoofing and Jamming Approaches in Unmanned Aerial Vehicles Navigation. Journal of Aerospace Technology and Management, 17. Scopus. https://doi.org/10.1590/jatm.v17.1396
Muhammad, A., Khan, Z. U., Khan, J., Mashori, A. S., Ali, A., Jabeen, N., Han, Z., & Li, F. (2025). A comprehensive review of crop stress detection: Destructive, non-destructive, and ML-based approaches. Frontiers in Plant Science, 16. Scopus. https://doi.org/10.3389/fpls.2025.1638675
Quang, N. H., Nguyen, M. N., Hung, N. M., Lee, H., & Kim, G. (2025). AI-based flood mapping from high-resolution ASNARO-2 images: Case study of a severe event in the Center of Vietnam. Natural Hazards, 121(15), 17647–17675. Scopus. https://doi.org/10.1007/s11069-025-07485-9
Rajesh, V., Godwin Roy, N. G., Muhammed Faiz, C. A., Liyanto, K. A., Baby, A., & Sreehari, S. (2025). AI-Based Landslide Prediction System with Real-Time Data Monitoring. 130–135. Scopus. https://doi.org/10.1109/ACCESS65134.2025.11135694
Rotimi, F. E., Kalatehjari, R., Moshood, T. D., & Dokyi, G. (2025). A comprehensive review of bibliometric and methodological approaches in flood mitigation studies: Current trends and future directions. Journal of Safety Science and Resilience, 6(2), 280–296. Scopus. https://doi.org/10.1016/j.jnlssr.2024.12.004
Sertel, E., & Huang, X. (2025). Advancing Human Geography with GeoAI: Transforming Land Use and Land Cover Analysis. In Springer Geography: Vol. Part F723 (pp. 373–386). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-3-031-87421-5_26
Sudianto, S., & Cahyadi, E. F. (2025). A Soil Nutrient Assessment for Crop Recommendation Using Ensemble Learning and Remote Sensing. International Journal of Intelligent Systems and Applications, 17(3), 34–47. Scopus. https://doi.org/10.5815/ijisa.2025.03.03
Tika, N., Paksi, N. R., & Muhammad, D. (2025). Advancing Tsunami Vulnerability Modelling: A Systematic Review and Bibliometric Analysis of Remote Sensing and GIS Applications. European Journal of Geography, 16(2), 75–95. Scopus. https://doi.org/10.48088/EJG.N.TIK.16.2.075.095
Uthradevi, G., Thiruvasagam, P., Mythili, S., & Manoj, S. O. (2025). A Semi-Supervised Deep Learning Approach for Intrusion Detection and Classification for the Internet of Things. Biomedical Materials and Devices. Scopus. https://doi.org/10.1007/s44174-025-00321-5
Wijesena, S., & Pradhan, B. (2025). Advancements in Weather Index Insurance: A Review of Data-Driven Approaches to Design, Pricing and Risk Management. Earth Systems and Environment, 9(3), 2355–2379. Scopus. https://doi.org/10.1007/s41748-025-00712-0
Authors
Copyright (c) 2025 Catherine Li, Rahmat Hidayat, Kumudu Wijerathna, Alma Yulianti
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
