Integrating Service Learning in Higher Education: Developing Civic Responsibility and Practical Skills through Real-World Engagement
Article Sidebar
-
Civic Responsibility, Community Engagement, Higher Education, Practical Skills, Service Learning
Abstract
Background: The integration of service learning in higher education has gained significant attention in recent years as an innovative pedagogical approach aimed at fostering civic responsibility and developing practical skills in students. Service learning encourages students to engage with real-world issues while contributing to community development, enhancing their academic and personal growth.
Objective: This study aims to explore the impact of integrating service learning into higher education curricula on students’ development of civic responsibility and practical skills, particularly in fostering social awareness, communication, teamwork, and problem-solving abilities.
Methods: A mixed-methods approach was employed in this research. Quantitative data were collected through surveys to assess the students’ self-reported changes in civic engagement and skill development. Qualitative data were gathered from focus group discussions to gain insights into students’ experiences and reflections on the service learning activities.
Results: The findings indicate that service learning significantly enhanced students’ sense of civic responsibility, critical thinking, and practical skills such as collaboration and communication. Students also reported a stronger commitment to community service and a deeper understanding of social issues.
Conclusion: Integrating service learning into higher education not only promotes civic responsibility but also equips students with essential skills for their professional and personal lives. The study recommends further incorporation of service learning in curricula to foster holistic student development.
Full text article
References
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004
Alsaedi, A., Moustafa, N., Tari, Z., Mahmood, A., & Anwar, A. (2020). TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems. IEEE Access, 8, 165130–165150. https://doi.org/10.1109/ACCESS.2020.3022862
Bag, S., Wood, L. C., Xu, L., Dhamija, P., & Kayikci, Y. (2020). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation and Recycling, 153, 104559. https://doi.org/10.1016/j.resconrec.2019.104559
Berger, J., Humphreys, A., Ludwig, S., Moe, W. W., Netzer, O., & Schweidel, D. A. (2020). Uniting the Tribes: Using Text for Marketing Insight. Journal of Marketing, 84(1), 1–25. https://doi.org/10.1177/0022242919873106
Besley, T. (2020). State Capacity, Reciprocity, and the Social Contract. Econometrica, 88(4), 1307–1335. https://doi.org/10.3982/ECTA16863
Birjali, M., Kasri, M., & Beni-Hssane, A. (2021). A comprehensive survey on sentiment analysis: Approaches, challenges and trends. Knowledge-Based Systems, 226, 107134. https://doi.org/10.1016/j.knosys.2021.107134
Bu, D., Luo, H., Huo, P., Wang, Z., Zhang, S., He, Z., Wu, Y., Zhao, L., Liu, J., Guo, J., Fang, S., Cao, W., Yi, L., Zhao, Y., & Kong, L. (2021). KOBAS-i: Intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Research, 49(W1), W317–W325. https://doi.org/10.1093/nar/gkab447
Chan, R. C. H., & Mak, W. W. S. (2020). Empowerment for civic engagement and well-being in emerging adulthood: Evidence from cross-regional and cross-lagged analyses. Social Science & Medicine, 244, 112703. https://doi.org/10.1016/j.socscimed.2019.112703
Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., & Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International Journal of Production Economics, 226, 107599. https://doi.org/10.1016/j.ijpe.2019.107599
Gal, I., Grotlüschen, A., Tout, D., & Kaiser, G. (2020). Numeracy, adult education, and vulnerable adults: A critical view of a neglected field. ZDM, 52(3), 377–394. https://doi.org/10.1007/s11858-020-01155-9
Gaunt, H., Duffy, C., Coric, A., González Delgado, I. R., Messas, L., Pryimenko, O., & Sveidahl, H. (2021). Musicians as “Makers in Society”: A Conceptual Foundation for Contemporary Professional Higher Music Education. Frontiers in Psychology, 12, 713648. https://doi.org/10.3389/fpsyg.2021.713648
Kaushal, V., & Srivastava, S. (2021). Hospitality and tourism industry amid COVID-19 pandemic: Perspectives on challenges and learnings from India. International Journal of Hospitality Management, 92, 102707. https://doi.org/10.1016/j.ijhm.2020.102707
Khan, N. A., Khan, A. N., Soomro, M. A., & Khan, S. K. (2020). Transformational leadership and civic virtue behavior: Valuing act of thriving and emotional exhaustion in the hotel industry. Asia Pacific Management Review, 25(4), 216–225. https://doi.org/10.1016/j.apmrv.2020.05.001
Li, S., Wang, Y., Xue, J., Zhao, N., & Zhu, T. (2020). The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users. International Journal of Environmental Research and Public Health, 17(6), 2032. https://doi.org/10.3390/ijerph17062032
Lim, S. B., & Yigitcanlar, T. (2022). Participatory Governance of Smart Cities: Insights from e-Participation of Putrajaya and Petaling Jaya, Malaysia. Smart Cities, 5(1), 71–89. https://doi.org/10.3390/smartcities5010005
Logue, D., & Grimes, M. (2022). Platforms for the people: Enabling civic crowdfunding through the cultivation of institutional infrastructure. Strategic Management Journal, 43(3), 663–693. https://doi.org/10.1002/smj.3110
Lu, Y., Huang, X., Dai, Y., Maharjan, S., & Zhang, Y. (2020). Blockchain and Federated Learning for Privacy-Preserved Data Sharing in Industrial IoT. IEEE Transactions on Industrial Informatics, 16(6), 4177–4186. https://doi.org/10.1109/TII.2019.2942190
Lu, Y., Huang, X., Zhang, K., Maharjan, S., & Zhang, Y. (2020). Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles. IEEE Transactions on Vehicular Technology, 69(4), 4298–4311. https://doi.org/10.1109/TVT.2020.2973651
Morse, J. S., Lalonde, T., Xu, S., & Liu, W. R. (2020). Learning from the Past: Possible Urgent Prevention and Treatment Options for Severe Acute Respiratory Infections Caused by 2019?nCoV. ChemBioChem, 21(5), 730–738. https://doi.org/10.1002/cbic.202000047
Oh, Y., Park, S., & Ye, J. C. (2020). Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets. IEEE Transactions on Medical Imaging, 39(8), 2688–2700. https://doi.org/10.1109/TMI.2020.2993291
Okafor, O. N., Adebisi, F. A., Opara, M., & Okafor, C. B. (2020). Deployment of whistleblowing as an accountability mechanism to curb corruption and fraud in a developing democracy. Accounting, Auditing & Accountability Journal, 33(6), 1335–1366. https://doi.org/10.1108/AAAJ-12-2018-3780
Ranchod, R. (2020). The data-technology nexus in South African secondary cities: The challenges to smart governance. Urban Studies, 57(16), 3281–3298. https://doi.org/10.1177/0042098019896974
Santini, Z. I., Jose, P. E., Koyanagi, A., Meilstrup, C., Nielsen, L., Madsen, K. R., & Koushede, V. (2020). Formal social participation protects physical health through enhanced mental health: A longitudinal mediation analysis using three consecutive waves of the Survey of Health, Ageing and Retirement in Europe (SHARE). Social Science & Medicine, 251, 112906. https://doi.org/10.1016/j.socscimed.2020.112906
Seyfi, S., Hall, C. M., Vo-Thanh, T., & Zaman, M. (2023). How does digital media engagement influence sustainability-driven political consumerism among Gen Z tourists? Journal of Sustainable Tourism, 31(11), 2441–2459. https://doi.org/10.1080/09669582.2022.2112588
Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die? Journal of Business Research, 117, 280–283. https://doi.org/10.1016/j.jbusres.2020.05.059
The Galaxy Community, Afgan, E., Nekrutenko, A., Grüning, B. A., Blankenberg, D., Goecks, J., Schatz, M. C., Ostrovsky, A. E., Mahmoud, A., Lonie, A. J., Syme, A., Fouilloux, A., Bretaudeau, A., Nekrutenko, A., Kumar, A., Eschenlauer, A. C., DeSanto, A. D., Guerler, A., Serrano-Solano, B., … Briggs, P. J. (2022). The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Research, 50(W1), W345–W351. https://doi.org/10.1093/nar/gkac247
Tuli, S., Basumatary, N., Gill, S. S., Kahani, M., Arya, R. C., Wander, G. S., & Buyya, R. (2020). HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments. Future Generation Computer Systems, 104, 187–200. https://doi.org/10.1016/j.future.2019.10.043
Veleva, V. (2021). The role of entrepreneurs in advancing sustainable lifestyles: Challenges, impacts, and future opportunities. Journal of Cleaner Production, 283, 124658. https://doi.org/10.1016/j.jclepro.2020.124658
Wankhade, M., Rao, A. C. S., & Kulkarni, C. (2022). A survey on sentiment analysis methods, applications, and challenges. Artificial Intelligence Review, 55(7), 5731–5780. https://doi.org/10.1007/s10462-022-10144-1
Weiss, M., Jacob, F., & Duveiller, G. (2020). Remote sensing for agricultural applications: A meta-review. Remote Sensing of Environment, 236, 111402. https://doi.org/10.1016/j.rse.2019.111402
Wray?Lake, L., & Abrams, L. S. (2020). Pathways to Civic Engagement Among Urban Youth of Color. Monographs of the Society for Research in Child Development, 85(2), 7–154. https://doi.org/10.1111/mono.12415
Yan, L., Zhang, H.-T., Goncalves, J., Xiao, Y., Wang, M., Guo, Y., Sun, C., Tang, X., Jing, L., Zhang, M., Huang, X., Xiao, Y., Cao, H., Chen, Y., Ren, T., Wang, F., Xiao, Y., Huang, S., Tan, X., … Yuan, Y. (2020). An interpretable mortality prediction model for COVID-19 patients. Nature Machine Intelligence, 2(5), 283–288. https://doi.org/10.1038/s42256-020-0180-7
Yang, S., Lee, J. W., Kim, H.-J., Kang, M., Chong, E., & Kim, E. (2021). Can an online educational game contribute to developing information literate citizens? Computers & Education, 161, 104057. https://doi.org/10.1016/j.compedu.2020.104057
Yang, Y., Chen, H., Heidari, A. A., & Gandomi, A. H. (2021). Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts. Expert Systems with Applications, 177, 114864. https://doi.org/10.1016/j.eswa.2021.114864
Zhu, G., Wang, Y., & Huang, K. (2020). Broadband Analog Aggregation for Low-Latency Federated Edge Learning. IEEE Transactions on Wireless Communications, 19(1), 491–506. https://doi.org/10.1109/TWC.2019.2946245
Authors
Copyright (c) 2024 Ali Mufron, Dara Vann
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
