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Extending CIAM Methodology to Support Mobile Application Design and Evaluation: A Case Study in m-Learning

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9320))

Abstract

Traditionally, the development of systems supporting group work has been considered a complex task because multiple aspects have to be considered. As a consequence, it is necessary to apply methodological processes in order to reach successful and usable systems. CIAM is a methodological approach for developing groupware user interfaces by modeling aspects of collaboration and interaction. CIAM addresses the joint modeling of collaboration and human-computer interaction aspects, guiding the engineers through several modeling stages, starting from the analysis of the context of the group work until obtaining an interactive task model. In its initial proposal, CIAM does not deal directly with evaluation mechanisms and processes of the artifacts produced when this methodology is applied. In addition, CIAM is not primarily focused on the mobile computing paradigm. Thus, the objective of this paper is to describe how CIAM is being improved in order to provide more complete support for modeling and evaluation of collaborative applications based on mobile computing and especially the modeling of applications supporting Mobile Learning (or m-Learning).

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Acknowledgments

This work has been partially supported by Project EDUCA-Prog of the Ministry of Science and Innovation (TIN2011-29542-C02-01 and TIN2011-29542-C02-02), and the InteGROUP Project (PEII-2014-021-P) of the Government of Castilla-La Mancha (JCCM).

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Correspondence to Miguel A. Redondo .

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Redondo, M.A., Molina, A.I., Navarro, C.X. (2015). Extending CIAM Methodology to Support Mobile Application Design and Evaluation: A Case Study in m-Learning. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_2

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  • DOI: https://doi.org/10.1007/978-3-319-24132-6_2

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