Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform

Fan Zhang

doi:10.12973/eurasia.2017.00726a

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Fan Zhang ¹ ^*

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¹ School of Economics and Finance, Xi’an Jiaotong University, CHINA
^* Corresponding Author

Abstract

Many researchers are trying to teach in the Smart Cloud Platform(SCP), but most of them either describe it on the conceptual level or realize it on the technical level. The development of the Pedagogical Interaction Model(PIM) has important educational significance and provides guidance for teaching in the emerging cloud learning environment. This study designs the PIM based on the SCP and further applies it in the class teaching of a junior high school. A total of 94 subjects from two classes were selected. One class was taught in SCP, and the other was taught in the traditional class. The pre-test shows both classes have little statistical significance in physics scores. After treating in the SCP for half a semester, the score of the treatment group was significantly higher than that of the control group which means the use of the PIM proposed in this paper can improve students' academic performance. The PIM has promising outlook in improving deep collaboration, communication, and personalized learning.

Keywords

smart cloud platform
pedagogical interaction model
connectivism
teaching support system

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

https://doi.org/10.12973/eurasia.2017.00726a

EURASIA J Math Sci and Tech Ed, 2017 - Volume 13 Issue 7, pp. 2911-2922

Publication date: 18 Jun 2017

Article Views: 326

Article Downloads: 56

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References

Anshari, M., Alas, Y., & Guan, L. S. (2016). Developing online learning resources: Big data, social networks, and cloud computing to support pervasive knowledge. Education and Information Technologies, 21(6), 1663-1677. doi:10.1007/s10639-015-9407-3.
Barnett, J., McPherson, V., & Sandieson, R. M. (2013). Connected teaching and learning: The uses and implications of connectivism in an online class. Australasian Journal of Educational Technology, 29(5). doi:10.14742/ajet.243.
Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98-118. doi:10.19173/irrodl.v12i3.902.
Chang, Y. S., Chen, S. Y., Yu, K. C., Chu, Y. H., & Chien, Y. H. (2015). Effects of cloud‐based m‐learning on student creative performance in engineering design. British Journal of Educational Technology. doi:10.1111/bjet.12343.
Clarà, M., & Barberà, E. (2013). Learning online: massive open online courses (MOOCs), connectivism, and cultural psychology. Distance Education, 34(1), 129-136. doi:10.1080/01587919.2013.770428.
Dempster, E., Williams, M. H., Burger, A., & Taylor, H. (2005). A tool for supporting the teaching of parallel database systems. IEEE Transactions on Education, 48(2), 238-247. doi:10.1109/TE.2004.842895.
Ding, J., Xiong, C., & Liu, H. (2015). Construction of a digital learning environment based on cloud computing. British Journal of Educational Technology, 46(6), 1367-1377. doi:10.1111/bjet.12208.
Donlan, L. (2014). Exploring the views of students on the use of Facebook in university teaching and learning. Journal of Further and Higher Education, 38(4), 572-588. doi:10.1080/0309877X.2012.726973.
Gao, S., & Wang, J. (2014). Teaching transformation under centralized curriculum and teacher learning community: Two Chinese chemistry teachers' experiences in developing inquiry-based instruction. Teaching and Teacher Education, 44, 1-11. doi:10.1016/j.tate.2014.07.008.
Goldie, J. G. S. (2016). Connectivism: A knowledge learning theory for the digital age? Medical teacher, 38(10), 1064-1069. doi: 10.3109/0142159X.2016.1173661.
Hew, T.-S., & Kadir, S. L. S. A. (2016). Behavioural intention in cloud-based VLE: An extension to Channel Expansion Theory. Computers in Human Behavior, 64, 9-20. doi:10.1016/j.chb.2016.05.075.
Junco, R., Elavsky, C. M., & Heiberger, G. (2013). Putting twitter to the test: Assessing outcomes for student collaboration, engagement and success. British Journal of Educational Technology, 44(2), 273-287. doi:10.1111/j.1467-8535.2012.01284.x.
Kizito, R. N. (2016). Connectivism in Learning Activity Design: Implications for Pedagogically-Based Technology Adoption in African Higher Education Contexts. The International Review of Research in Open and Distributed Learning, 17(2). doi:10.19173/irrodl.v17i2.2217.
Kong, S. C. (2010). Using a web-enabled video system to support student–teachers’ self-reflection in teaching practice. Computers & Education, 55(4), 1772-1782. doi:10.1016/j.compedu.2010.07.026.
Kumar, S., & Daniel, B. K. (2016). Integration of learning technologies into teaching within Fijian Polytechnic Institutions. International Journal of Educational Technology in Higher Education, 13(1), 36. doi:10.1186/s41239-016-0036-8.
Lee, A. (2015). Authentication scheme for smart learning system in the cloud computing environment. Journal of Computer Virology and Hacking Techniques, 11(3), 149-155. doi:10.1007/s11416-015-0240-4.
Liao, J., Wang, M., Ran, W., & Yang, S. J. (2014). Collaborative cloud: a new model for e-learning. Innovations in Education and Teaching International, 51(3), 338-351. doi:10.1080/14703297.2013.791554.
Lin, Y.-T., Wen, M.-L., Jou, M., & Wu, D.-W. (2014). A cloud-based learning environment for developing student reflection abilities. Computers in Human Behavior, 32, 244-252. doi:10.1016/j.chb.2013.12.014.
Pireva, K., Kefalas, P., Dranidis, D., Hatziapostolou, T., & Cowling, A. (2014). Cloud e-learning: A new challenge for multi-agent systems. Agent and Multi-Agent Systems: Technologies and Applications, 277-287. doi:10.1007/978-3-319-07650-8_28.
Recupero, D. R., Castronovo, M., Consoli, S., Costanzo, T., Gangemi, A., Grasso, L., . . . Presutti, V. (2016). An innovative, open, interoperable citizen engagement cloud platform for smart government and users’ interaction. Journal of the Knowledge Economy, 7(2), 388-412. doi:10.1007/s13132-016-0361-0.
Reese, S. A. (2015). Online learning environments in higher education: Connectivism vs. dissociation. Education and Information Technologies, 20(3), 579-588. doi:10.1007/s10639-013-9303-7.
Sevimli, E. (2016). Do calculus students demand technology integration into learning environment? case of instructional differences. International Journal of Educational Technology in Higher Education, 13(1), 37. doi:10.1186/s41239-016-0038-6.
Su, C. H., Tzeng, G.-H., & Hu, S.-K. (2016). Cloud e-learning service strategies for improving e-learning innovation performance in a fuzzy environment by using a new hybrid fuzzy multiple attribute decision-making model. Interactive Learning Environments, 24(8), 1812-1835. doi:10.1080/10494820.2015.1057742.
Tanaka, H., Sakriani, S., Neubig, G., Toda, T., Negoro, H., Iwasaka, H., & Nakamura, S. (2016). Teaching Social Communication Skills Through Human-Agent Interaction. ACM Transactions on Interactive Intelligent Systems (TiiS), 6(2), 18. doi:10.1145/2937757.
Wang, M., Chen, Y., & Khan, M. J. (2014). Mobile cloud learning for higher education: A case study of Moodle in the cloud. The International Review of Research in Open and Distributed Learning, 15(2). doi:10.19173/irrodl.v15i2.1676.
Wang, Z., Anderson, T., Chen, L., & Barbera, E. (2016). Interaction pattern analysis in cMOOCs based on the connectivist interaction and engagement framework. British Journal of Educational Technology. doi:10.1111/bjet.12433.
Xie, T., Zheng, Q., & Zhang, W. (2016). A behavioral sequence analyzing framework for grouping students in an e-learning system. Knowledge-Based Systems, 111, 36-50. doi:10.1016/j.knosys.2016.08.001.
Zhao, H., & Sullivan, K. P. (2016). Teaching presence in computer conferencing learning environments: Effects on interaction, cognition and learning uptake. British Journal of Educational Technology. doi:10.1111/bjet.12383.

How to cite this article

Vancouver

Zhang F. Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform. EURASIA J Math Sci and Tech Ed. 2017;13(7):2911-22. https://doi.org/10.12973/eurasia.2017.00726a

APA

Zhang, F. (2017). Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform. EURASIA Journal of Mathematics, Science and Technology Education, 13(7), 2911-2922. https://doi.org/10.12973/eurasia.2017.00726a

AMA

Zhang F. Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform. EURASIA J Math Sci and Tech Ed. 2017;13(7), 2911-2922. https://doi.org/10.12973/eurasia.2017.00726a

Chicago

Zhang, Fan. "Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform". EURASIA Journal of Mathematics, Science and Technology Education 2017 13 no. 7 (2017): 2911-2922. https://doi.org/10.12973/eurasia.2017.00726a

Harvard

Zhang, F. (2017). Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform. EURASIA Journal of Mathematics, Science and Technology Education, 13(7), pp. 2911-2922. https://doi.org/10.12973/eurasia.2017.00726a

MLA

Zhang, Fan "Designing and Applying a Pedagogical Interaction Model in the Smart Cloud Platform". EURASIA Journal of Mathematics, Science and Technology Education, vol. 13, no. 7, 2017, pp. 2911-2922. https://doi.org/10.12973/eurasia.2017.00726a