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Guidelines for Evaluating Mobile Applications: A Semiotic-Informed Approach

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Abstract

Portable devices have been experimented for data acquisition in different domains, e.g., logistics and census data acquisition. Nevertheless, their large-scale adoption depends on the development of effective applications with a careful interaction design. In this work, we revisit existing strategies for mobile application design and evaluation and use the Semiotic Ladder from Organizational Semiotics as an artifact to organize a set of guidelines. We propose a set of semiotic-informed guidelines with questions for evaluation of mobile application interfaces. We also propose a methodology for the evaluation of mobile application interfaces based on the proposed guidelines set. We demonstrate the use of the proposed methodology in the evaluation of four mobile application interfaces designed for phenological data acquisition in the field.

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Notes

  1. 1.

    http://www.recod.ic.unicamp.br/ephenology/ (As of March 2015).

  2. 2.

    Details from field site and sample methods can be found elsewhere [37, 38].

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Acknowledgments

This research was supported by the FAPESP – Microsoft Research Virtual Institute (grants #2010/52113-5 and #2013/50155-0). LPCM, CB, and RST receive a Productivity Research Fellowship from CNPq (grants #306243/2010-5, #308618/2014-9 and #306587/2009-2). BA receives a PhD fellowship from FAPESP (grant #2014/00215-0). Also, we also thank CNPq, CAPES, and FAPESP (grants #2007/52015-0, #2007/59779-6, #2009/18438-7, and #2010/51307-0). We would like also to thank the HCI and Phenology experts for their help and participation in the evaluation process.

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Correspondence to Flavio Nicastro .

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Nicastro, F., Pereira, R., Alberton, B., Morellato, L.P.C., Baranauskas, C., Torres, R.d.S. (2015). Guidelines for Evaluating Mobile Applications: A Semiotic-Informed Approach. In: Hammoudi, S., Maciaszek, L., Teniente, E., Camp, O., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2015. Lecture Notes in Business Information Processing, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-29133-8_26

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  • DOI: https://doi.org/10.1007/978-3-319-29133-8_26

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