Abstract
The aim of this investigation is to identify and understand the relations between the people’s mental models and their performance and usability perception about a complex interactive system (Twitter). Our study includes the participation of thirty college students where each of them was asked to perform a number of activities with Twitter, and to draw graphical representations of the mental model about it. The participants have either none or at least a year of expertise using Twitter. We identified three typical types of mental models used by participants to describe Twitter and found that the level of expertise had a major impact on performance rather than the mental model style defining the understanding about the system. Furthermore, and in contrast, we found that usability perception was affected by the level of expertise.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Moreira, M.A., Greca, I.M., Palmero, M.L.R.: Mental models and conceptual models in the teaching & learning of science. Revista Brasileira de Investigação em Educação em Ciencias 2(3), 84–96 (2002)
Krapas, S., Queiroz, G., Colinvaux, D., Franco, C., Alves, F.: Modelos: Uma análise de sentidos na literatura de pesquisa em ensino de ciências. Investigações em Ensino de Ciências 2(3), 185–205 (1997)
Johnson-Laird, P.N., Girotto, V., Legrenzi, P.: Mental models: A gentle guide for outsiders. Sistemi Intelligenti 9(68), 33 (1998)
Brandt, D.S., Uden, L.: Insight into mental models of novice Internet searchers. Communications of the ACM 46(7), 133–136 (2003)
Michael, J.A.: Mental models and meaningful learning. Journal of Veterinary Medical Education 31(1), 1–5 (2004)
Hmelo-Silver, C.E., Pfeffer, M.G.: Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and func-tions. Cognitive Science 28(1), 127–138 (2004)
Moray, N.: Intelligent aids, mental models, and the theory of machines. International Journal of Man-Machine Studies 27(5), 619–629 (1987)
Bevan, N.: International standards for HCI and usability. International Journal of Human-Computer Studies 55(4), 533–552 (2001)
Ahn, Y.Y., Han, S., Kwak, H., Moon, S., Jeong, H.: Analysis of topological characteristics of huge online social networking services. In: Proceedings of the 16th International Conference on World Wide Web, pp. 835–844. ACM (2007)
Staggers, N., Norcio, A.F.: Mental models: Concepts for human-computer inter-action research. International Journal of Man-Machine Studies 38(4), 587–605 (1993)
Dixon, R.A., Johnson, S.D.: Experts vs. Novices: Differences in How Mental Representations are Used in Engineering Design (2011)
Kieras, D.E., Bovair, S.: The role of a mental model in learning to operate a device. Cognitive Science 8(3), 255–273 (1984)
Zhang, Y.: The influence of mental models on undergraduate students’ searching behavior on the Web. Information Processing & Management 44(3), 1330–1345 (2008)
Borgman, C.L.: The user’s mental model of an information retrieval system: An experiment on a prototype online catalog. International Journal of Man-Machine Studies 24(1), 47–64 (1986)
Thatcher, A., Greyling, M.: Mental models of the Internet. International Journal of Industrial Ergonomics 22(4), 299–305 (1998)
Liu, I.L., Cheung, C.M., Lee, M.K.: Understanding Twitter usage: What drive people continue to tweet. In: PACIS 2010 Proceedings, pp. 927–939 (2010)
Hargittai, E., Litt, E.: The tweet smell of celebrity success: Explaining variation in Twitter adoption among a diverse group of young adults. New Media & Society 13(5), 824–842 (2011)
Bangor, A., Kortum, P., Miller, J.: Determining what individual SUS scores mean: Adding an adjective rating scale. Journal of Usability Studies 4(3), 114–123 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
González, V.M., Juárez, R. (2013). How Do You Understand Twitter?: Analyzing Mental Models, Understanding and Learning about Complex Interactive Systems. In: Collazos, C., Liborio, A., Rusu, C. (eds) Human Computer Interaction. CLIHC 2013. Lecture Notes in Computer Science, vol 8278. Springer, Cham. https://doi.org/10.1007/978-3-319-03068-5_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-03068-5_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03067-8
Online ISBN: 978-3-319-03068-5
eBook Packages: Computer ScienceComputer Science (R0)