SOCIAL LEARNING MECHANISMS AND REFLECTIVE ENGAGEMENT IN CROWDSOURCED DESIGN SKILL DEVELOPMENT: A QUASI-EXPERIMENTAL STUDY
DOI:
https://doi.org/10.55197/qjssh.v7i2.1158Keywords:
social learning theory, observational learning, peer modeling, self-efficacy, crowdsourced designAbstract
This paper has investigated the effectiveness of structured social learning processes in crowdsourced design environments in terms of skill development. The study relied on the Social Learning Theory and focused on the impact of observational learning and peer modeling on the design performance and evaluated the possibility of self-efficacy mediating the impact. A quasi-experimental pretest- posttest design was used with 180 design students, and they were placed in control, observational learning, peer modeling, and combined intervention conditions. Analysis of covariance controlling baseline scores was used to analyze posttest performance. The findings revealed a large overall group effect, which revealed that structured learning processes enhanced design skill development. Premeditated comparisons showed that observational learning and peer modeling were significantly better than the control group and the combined intervention showed the greatest increases in performance. The mediation analysis based on bootstrapped indirect effects showed that the relationship between intervention conditions and performance improvement was mediated by self-efficacy, in part. These results can be used to generalize Social Learning Theory to asynchronous crowdsourced design settings and to show that deliberate learning architecture can be used to improve cognitive performance and psychological ability within competitive digital settings. The research offers practical value in terms of designing crowdsourcing platforms and organized teaching methods that contribute to the long-term skill acquisition.
References
[1] Abri, A.A. (2021): Exploring EFL Learners' Comments on Web-Based Peer Feedback: Local and Global Revisions. – English Language Teaching 14(6): 114-124.
[2] Afuah, A., Tucci, C.L. (2012): Crowdsourcing as a solution to distant search. – Academy of Management Review 37(3): 355-375.
[3] AlGhamdi, R. (2025): Bridging learning gaps through Discord: peer-to-peer learning in computer graphics education. – Learning and Teaching in Higher Education Gulf Perspectives 19(1): 49-65.
[4] Bandura, A. (1986): Social foundations of thought and action: A social cognitive theory. – Prentice-Hall 617p.
[5] Bhandari, A., Chumbley, S., Turner, B. (2023): Assessing student and coach learning experiences with virtual collegiate soil judging contest during covid-19 pandemic. – Education Sciences 13(7): 11p.
[6] Daher, W., Sabbah, K., Abuzant, M. (2021): Affective engagement of higher education students in an online course. – Emerging Science Journal 5(4): 545-558.
[7] Gao, Y., Wang, X., Li, X., Yin, H., Ma, Q., Guo, Y. (2024): Learning experiences of medical imaging undergraduates participating in the “Creative H&E” project incorporating design thinking: a qualitative study. – Research Square 17p.
[8] Pham, N. (2023): Organizing the contest “Experiencing stem in natural science” for students at Nguyen Tu secondary school, Co Linh city, Dong Thap province. – Dong Thap University Journal of Science 12(3): 81-88.
[9] Tallone, L., Ribeiro, S., Albuquerque, A. (2023): Is individual competition in translator training compatible with collaborative learning? The case of the MTIE Translation Award. – Language Learning in Higher Education 13(1): 201-211.
[10] Håkansson, S., Turner, E., Lecaros, C.W. (2021): Active and transformational engagement with writing feedback: using reflection as a tool to access literary disciplinary knowledge. – Nordic Journal of English Studies 20(2): 24p..
[11] Hou, J., Chen, P., Gu, B. (2021): Does exposure to shared solutions lead to better outcomes? an empirical investigation in online crowdsourcing contests. – In Proceedings of the 54th Hawaii International Conference on System Sciences 10p.
[12] Mellon, M., Van Dierdonck, H., Morjaria, L., Bracken, K., Sibbald, M. (2024): Reflecting on peer feedback in problem-based learning: implementing a group function tool. – Cureus 16(12): 11p.
[13] Pilara, M.R.R.D., Edilberto, Z.A. (2022): Student’s online engagement using idea exemplar: A direction towards the level of competency in the performing arts of grade 10 physical education students. – International Journal of Research Publications 105(1): 782-810.
[14] Wenger, E. (1999): Communities of practice: Learning, meaning, and identity. – Cambridge university Press 336p.
[15] Ye, J., Jensen, M. (2022): Effects of introducing an online community on a crowdsourcing contest platform. – Information Systems Journal 32(6): 1203-1230.
[16] Yu, Q., Schunn, C. (2025): Which experiences are consistently associated with other regulations of peer feedback length? – Journal of Educational Psychology 117(6): 918-938.
[17] Zhao, Y., Zhu, Q. (2014): Evaluation on crowdsourcing research: Current status and future direction. – Information Systems Frontiers 16(3): 417-434.
[18] Zuhrie, M., Buditjahjanto, I., Nurlaela, L., Basuki, I. (2021): Do educational robotics competitions impact students’ learning? – Journal of Physics Conference Series 1810(1): 9p.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 RAINAL HIDAYAT WARDI, RAHMAN ROSMAN, SABZALI MUSA KHAN, KHAIRI KHALID, UMMI ZINNIRAH MOHD YUSOF
This work is licensed under a Creative Commons Attribution 4.0 International License.
