Interactive Effects in Blended Learning Mode: Exploring Hybrid Data Sources and Iterative Linkages
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Interactive Effects in Blended Learning Mode: Exploring Hybrid Data Sources and Iterative Linkages

Authors: Hock Chuan, Lim

Abstract:

This paper presents an approach for identifying interactive effects using Network Science (NS) supported by Social Network Analysis (SNA) techniques. Based on general observations that learning processes and behaviors are shaped by the social relationships and influenced by learning environment, the central idea was to understand both the human and non-human interactive effects for a blended learning mode of delivery of computer science modules. Important findings include (a) the importance of non-human nodes to influence the centrality and transfer; (b) the degree of non-human and human connectivity impacts learning. This project reveals that the NS pattern and connectivity as measured by node relationships offer alternative approach for hypothesis generation and design of qualitative data collection. An iterative process further reinforces the analysis, whereas the experimental simulation option itself is an interesting alternative option, a hybrid combination of both experimental simulation and qualitative data collection presents itself as a promising and viable means to study complex scenario such as blended learning delivery mode. The primary value of this paper lies in the design of the approach for studying interactive effects of human (social nodes) and non-human (learning/study environment, Information and Communication Technologies (ICT) infrastructures nodes) components. In conclusion, this project adds to the understanding and the use of SNA to model and study interactive effects in blended social learning.

Keywords: Blended learning, network science, social learning, social network analysis, study environment.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3455643

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References:


[1] M. Milad, "The Pedagogical Development of Blended Learning," in English Language Teaching Research in the Middle East and North Africa, Cham, 2019.
[2] M. Kearney, K. Burden and S. Schuck, "Disrupting Education Using Smart Mobile Pedagogies," in Didactics of Smart Pedagogy, Cham, 2019.
[3] A. Palalas and C. Gitsaki, "Making Blended Learning Work," in International Association for Blended Learning in Partnership with the Center for Educational Innovation, , Zayed University, UAE, 2019.
[4] B. Alexander, K. Ashford-Rowe, N. Barajas-Murph, G. Dobbin, J. Knott, M. McCormack, J. Pomerantz, R. Seilhamer and N. Weber, "EDUCAUSE Horizon Report 2019 Higher Education Edition," EDU19, 2019.
[5] O. F. Olafare, "Blended Learning: Integratinng Technology into Instruction," International Journal for Innovative Technology Integration in Education (2019):, vol. 1, pp. 1-248, 2019.
[6] A. Pera, "The social aspects of technology-enhanced learning situations," Geopolitics, History, and International Relations, vol. 5, no. 2, pp. 118-123, 2013.
[7] A. L. Whiteside, "Introducing the social presence model to explore online and blended learning experiences," Online Learning, vol. 19, no. 2, p. n2, 2015.
[8] W. N. T. W. Hussin, J. Harun and N. A. Shukor, "Online Interaction in Social Learning Environment towards Critical Thinking Skill: A Framework," Journal of Technology and Science Education, vol. 9, no. 1, pp. 4-12, 2019.
[9] J. P. Spillane, M. Hopkins and T. M. Sweet, "School district educational infrastructure and change at scale: Teacher peer interactions and their beliefs about mathematics instruction," American educational research journal, vol. 55, no. 3, pp. 532-571, 2018.
[10] C. Fernandez-Llamas, M. A. Conde, F. J. Rodríguez-Lera, F. J. Rodríguez-Sedano and F. García, "May I teach you? Students' behavior when lectured by robotic vs. human teachers," Computers in Human Behavior, vol. 60, pp. 460-469, 2018.
[11] J. Kanero, V. Geçkin, C. Oranç, E. Mamus, A. C. Küntay and T. Göksun, "Social robots for early language learning: Current evidence and future directions," Child Development Perspectives, vol. 12, no. 3, pp. 146-151, 2018.
[12] A. Vespignani, "Twenty years of network science," Nature, vol. 528, 2018.
[13] A. M. Schmidt and J. Kevin Ford, "Learning within a learner control training environment: The interactive effects of goal orientation and metacognitive instruction on learning outcomes," Personnel Psychology, vol. 56, no. 2, pp. 405-429, 2003.
[14] P. Pinger, K. Rakoczy, M. Besser and E. Klieme, "Interplay of formative assessment and instructional quality—interactive effects on students’ mathematics achievement," Learning Environments Research, vol. 21, no. 1, pp. 61-79, 2018.
[15] X. Gao, R. Gong, T. Shu, X. Xie, S. Wang and S.-C. Zhu, "VRKitchen: an Interactive 3D Virtual Environment for Task-oriented Learning," arXiv preprint arXiv:1903.05757, 2019.
[16] R. N. Uppot, B. Laguna, C. J. McCarthy, G. De Novi, A. Phelps, E. Siegel and J. Courtier, "Implementing Virtual and Augmented Reality Tools for Radiology Education and Training, Communication, and Clinical Care," Radiology, vol. 291, no. 3, pp. 570-580, 2019.
[17] D. Novick, M. Afravi, A. Camacho, A. Rodriguez and L. Hinojos, "Pedagogical-Agent Learning Companions in a Virtual Reality Educational Experience," in International Conference on Human-Computer Interaction, Cham, 2019.
[18] R. Kanawati and M. Atzmueller, "Modeling and Mining Feature-Rich Networks," in Companion Proceedings of The 2019 World Wide Web Conference, 2019.