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Research on Learning Resource Design Model Based on Mobile Learning

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Abstract

The mobile learning resource is the basis of mobile learning, and its quality may directly affect the effectiveness of mobile learning. At present, the domestic mobile learning resources are characterized by lack of quantity, mostly lingual contents and simple content structure, and some of the resources have become direct relocation of network learning resources, so it is hard for them to meet the real demands of mobile learners. Therefore, the research on design and development of high-quality mobile learning resources suitable for learners is of great significance to the popularization and promotion of mobile learning. Based on customer needs, the Customer Value Theory maximizes the business competitiveness and value while enhancing the customer satisfaction and loyalty. In the implementation process of mobile education, learners are not only the object of education, but also the customers who enjoy educational services. In this study, the Customer Value Theory is introduced to the design of mobile learning resources, orientation is taken for learners, and the mobile learning resources that meet the needs of learners are designed and developed. It has been proved that the design of mobile value products based on customer value can effectively meet the needs of mobile learning.

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Correspondence to Fang Li .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, F., Lang, F., Lu, Z. (2018). Research on Learning Resource Design Model Based on Mobile Learning. In: Liu, S., Glowatz, M., Zappatore, M., Gao, H., Jia, B., Bucciero, A. (eds) e-Learning, e-Education, and Online Training. eLEOT 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 243. Springer, Cham. https://doi.org/10.1007/978-3-319-93719-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-93719-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93718-2

  • Online ISBN: 978-3-319-93719-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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