The Impact of Using Collaborative Learning Platforms on Increasing Student Creativity
Article Sidebar
-
Collaboration, Creativity, Platform
Abstract
One of the student-centred learning (SCL) methods is collaborative learning. In collaborative learning, students are required to actively participate in learning together or in groups. And collaborative learning is also based on the needs of students to improve the quality of learning. This research is conducted to find out how the use of collaborative learning platforms can help students become more creative in collaborative activities. By understanding the different types of collaborative learning platforms, teachers and parents are able to incorporate the role of technology in students' learning process. In conducting this research, researchers used quantitative methods in the implementation of the research. The data obtained by researchers was obtained through distributing questionnaires presented by researchers through a goggle from application. The distribution of this questionnaire was carried out by researchers online, which then the results of the acquisition of the distribution of this questionnaire will be processed using an SPSS application. From this research, the researcher can conclude that the impact of using a collaborative learning platform on increasing student creativity shows positive results. With the use of collaborative learning platform, it can visualise abstract and complex concepts, opening opportunities for students to develop their imagination and creativity through rich visual exposure. Based on the results of this study, it shows that collaborative learning platform can enhance students' creativity as it allows students to interact more actively and interactively during the learning process. In addition, rich visual exposure enables better understanding and enhances students' creativity and imagination.
Full text article
References
Al-Samarraie, H., & Saeed, N. (2018). A systematic review of cloud computing tools for collaborative learning: Opportunities and challenges to the blended-learning environment. Computers & Education, 124, 77–91. https://doi.org/10.1016/j.compedu.2018.05.016
Alsamhi, S., Ma, O., Ansari, M., & Gupta, S. (2019). Collaboration of Drone and Internet of Public Safety Things in Smart Cities: An Overview of QoS and Network Performance Optimization. Drones, 3(1), 13. https://doi.org/10.3390/drones3010013
Anderson, T., & Rivera-Vargas, P. (2020). A Critical look at Educational Technology from a Distance Education Perspective. Digital Education Review, 37, 208–229. https://doi.org/10.1344/der.2020.37.208-229
Annosi, M. C., Brunetta, F., Bimbo, F., & Kostoula, M. (2021). Digitalization within food supply chains to prevent food waste. Drivers, barriers and collaboration practices. Industrial Marketing Management, 93, 208–220. https://doi.org/10.1016/j.indmarman.2021.01.005
Blalock, A. E., & Akehi, M. (2018). Collaborative Autoethnography as a Pathway for Transformative Learning. Journal of Transformative Education, 16(2), 89–107. https://doi.org/10.1177/1541344617715711
Brandt, J.-O., Bürgener, L., Barth, M., & Redman, A. (2019). Becoming a competent teacher in education for sustainable development: Learning outcomes and processes in teacher education. International Journal of Sustainability in Higher Education, 20(4), 630–653. https://doi.org/10.1108/IJSHE-10-2018-0183
Chen, X., Zou, D., Cheng, G., & Xie, H. (2020). Detecting latent topics and trends in educational technologies over four decades using structural topic modeling: A retrospective of all volumes of Computers & Education. Computers & Education, 151, 103855. https://doi.org/10.1016/j.compedu.2020.103855
Collias, D., Marshall, R., Collins, S. P., Beisel, C. L., & Noireaux, V. (2019). An educational module to explore CRISPR technologies with a cell-free transcription-translation system. Synthetic Biology, 4(1), ysz005. https://doi.org/10.1093/synbio/ysz005
Daya, A., & Laher, S. (2020). Exploring the Influence of Educators’ Access to and Attitudes towards Educational technology on the Use of Educational Technology in Johannesburg Schools. Africa Education Review, 17(1), 159–180. https://doi.org/10.1080/18146627.2018.1490154
Ginsberg, A., Gasman, M., & Castro Samayoa, A. (2021). “A Learning Process Versus a Moment”: Engaging Black Male Teacher Education Candidates in Culturally Sustaining Pedagogy at Jackson State University. The Teacher Educator, 56(2), 171–193. https://doi.org/10.1080/08878730.2020.1846830
Haus-Reve, S., Fitjar, R. D., & Rodríguez-Pose, A. (2019). Does combining different types of collaboration always benefit firms? Collaboration, complementarity and product innovation in Norway. Research Policy, 48(6), 1476–1486. https://doi.org/10.1016/j.respol.2019.02.008
Hernández-Sellés, N., Muñoz-Carril, P.-C., & González-Sanmamed, M. (2022). Roles del docente universitario en procesos de aprendizaje colaborativo en entornos virtuales. RIED-Revista Iberoamericana de Educación a Distancia, 26(1), 39–58. https://doi.org/10.5944/ried.26.1.34031
Hong, S. B., & Han, J. (2023). Early childhood preservice teachers’ learning about children’s metacognitive thinking processes and constructivist pedagogy. Early Years, 1–16. https://doi.org/10.1080/09575146.2023.2179960
Huang, S. (2021). Design and Development of Educational Robot Teaching Resources Using Artificial Intelligence Technology. International Journal of Emerging Technologies in Learning (iJET), 16(05), 116. https://doi.org/10.3991/ijet.v16i05.20311
Idris, K. M., Eskender, S., Yosief, A., Demoz, B., & Andemicael, K. (2020). Exploring Headway Pedagogies in Initial Teacher Education Through Collaborative Action Research into Processes of Learning: Experiences from Eritrea. Nordic Journal of Comparative and International Education (NJCIE), 4(3–4), 139–156. https://doi.org/10.7577/njcie.3746
Isohätälä, J., Näykki, P., & Järvelä, S. (2020). Cognitive and Socio-Emotional Interaction in Collaborative Learning: Exploring Fluctuations in Students’ Participation. Scandinavian Journal of Educational Research, 64(6), 831–851. https://doi.org/10.1080/00313831.2019.1623310
Järvelä, S., Gaševi?, D., Seppänen, T., Pechenizkiy, M., & Kirschner, P. A. (2020). Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning. British Journal of Educational Technology, 51(6), 2391–2406. https://doi.org/10.1111/bjet.12917
Jederlund, U., & Von Rosen, T. (2022). Changes in Students’ School Trust as a Reflection of Teachers’ Collective Learning Processes: Findings from a Longitudinal Study. Scandinavian Journal of Educational Research, 66(7), 1161–1182. https://doi.org/10.1080/00313831.2021.1982764
Li, A., Zheng, C., Zhang, L., & Li, X. (2022). Glance and gaze: A collaborative learning framework for single-channel speech enhancement. Applied Acoustics, 187, 108499. https://doi.org/10.1016/j.apacoust.2021.108499
Liying, H., & Ismail, K. (2023). Identifying the contribution of technology innovation in driving sustainability in higher educational institutions through political influence, performance-based budgeting, organizational culture. Economic Research-Ekonomska Istraživanja, 36(2), 2142265. https://doi.org/10.1080/1331677X.2022.2142265
Loes, C. N., Culver, K. C., & Trolian, T. L. (2018). How Collaborative Learning Enhances Students’ Openness to Diversity. The Journal of Higher Education, 89(6), 935–960. https://doi.org/10.1080/00221546.2018.1442638
Luo, Q., Li, C., Luan, T. H., & Shi, W. (2020). Collaborative Data Scheduling for Vehicular Edge Computing via Deep Reinforcement Learning. IEEE Internet of Things Journal, 7(10), 9637–9650. https://doi.org/10.1109/JIOT.2020.2983660
Manathunga, K., & Hernández?Leo, D. (2018). Authoring and enactment of mobile pyramid?based collaborative learning activities. British Journal of Educational Technology, 49(2), 262–275. https://doi.org/10.1111/bjet.12588
Melander, L. (2018). Customer and Supplier Collaboration in Green Product Innovation: External and Internal Capabilities. Business Strategy and the Environment, 27(6), 677–693. https://doi.org/10.1002/bse.2024
Mora, H., Signes-Pont, M. T., Fuster-Guilló, A., & Pertegal-Felices, M. L. (2020). A collaborative working model for enhancing the learning process of science & engineering students. Computers in Human Behavior, 103, 140–150. https://doi.org/10.1016/j.chb.2019.09.008
Nachlieli, T., & Tabach, M. (2022). Classroom learning as a deritualization process: The case of prospective teachers learning to solve arithmetic questions. The Journal of Mathematical Behavior, 65, 100930. https://doi.org/10.1016/j.jmathb.2021.100930
Qureshi, M. A., Khaskheli, A., Qureshi, J. A., Raza, S. A., & Yousufi, S. Q. (2023). Factors affecting students’ learning performance through collaborative learning and engagement. Interactive Learning Environments, 31(4), 2371–2391. https://doi.org/10.1080/10494820.2021.1884886
Rodriguez, C., Hudson, R., & Niblock, C. (2018). Collaborative learning in architectural education: Benefits of combining conventional studio, virtual design studio and live projects. British Journal of Educational Technology, 49(3), 337–353. https://doi.org/10.1111/bjet.12535
Sun, Z., Lin, C., Wu, M., Zhou, J., & Luo, L. (2018). A tale of two communication tools: Discussion?forum and mobile instant?messaging apps in collaborative learning. British Journal of Educational Technology, 49(2), 248–261. https://doi.org/10.1111/bjet.12571
Vlastra, W., Chandrasekhar, J., Muñoz-Garcia, A. J., Tchétché, D., De Brito, F. S., Barbanti, M., Kornowski, R., Latib, A., D’Onofrio, A., Ribichini, F., Baan, J., Tijssen, J. G. P., Trillo-Nouche, R., Dumonteil, N., Abizaid, A., Sartori, S., D’Errigo, P., Tarantini, G., Lunardi, M., … Delewi, R. (2019). Comparison of balloon-expandable vs. self-expandable valves in patients undergoing transfemoral transcatheter aortic valve implantation: From the CENTER-collaboration. European Heart Journal, 40(5), 456–465. https://doi.org/10.1093/eurheartj/ehy805
Wang, P., Liu, H., Wang, L., & Gao, R. X. (2018). Deep learning-based human motion recognition for predictive context-aware human-robot collaboration. CIRP Annals, 67(1), 17–20. https://doi.org/10.1016/j.cirp.2018.04.066
Yu, X., Peng, Q., Xu, L., Jiang, F., Du, J., & Gong, D. (2021). A selective ensemble learning based two-sided cross-domain collaborative filtering algorithm. Information Processing & Management, 58(6), 102691. https://doi.org/10.1016/j.ipm.2021.102691
Authors
Copyright (c) 2024 Rizky Wardhani, Dedi Zulkarnain Pulungan, Thitus Gilaa
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.