Jump to ContentJump to Main Navigation
Show Summary Details
In This Section


Journal of Interactive Media

Editor-in-Chief: Ziegler, Jürgen

3 Issues per year

See all formats and pricing
In This Section
Volume 14, Issue 2 (Aug 2015)


Modeling Interruption and Resumption in a Smartphone Task: An ACT-R Approach

Maria Wirzberger
  • Corresponding author
  • DFG Research Training Group “CrossWorlds”, TU Chemnitz, Chemnitz, Germany.
  • Email:
/ Prof. Dr.-Ing. Nele Russwinkel
  • Cognitive Modeling in dynamic Human-Machine Systems, TU Berlin, Berlin, Germany
  • Email:
Published Online: 2015-07-12 | DOI: https://doi.org/10.1515/icom-2015-0033


This research aims to inspect human cognition when being interrupted while performing a smartphone task with varying levels of mental demand. Due to its benefits especially in the early stages of interface development, a cognitive modeling approach is used. It applies the cognitive architecture ACT-R to shed light on task-related cognitive processing. The inspected task setting involves a shopping scenario, manipulating interruption via product advertisements and mental demands by the respective number of people shopping is done for. Model predictions are validated through a corresponding experimental setting with 62 human participants. Comparing model and human data in a defined set of performance-related parameters displays mixed results that indicate an acceptable fit – at least in some cases. Potential explanations for the observed differences are discussed at the end.

Keywords: ACT-R; Cognitive Modeling; Interruption; Mobile Interaction

  • Altmann, E.M and J.G. Trafton. 2002. Memory for goals: an activation-based model, Cogn. Sci. 26: 39–83.

  • Anderson, J.R. 2007. How can the human mind occur in the physical universe? Oxford University Press, New York.

  • Anderson, J.R. and C. Lebiere. (1998). The atomic components of thought. Erlbaum, Mahwah, NJ.

  • Anderson, J.R., L.M. Reder and C. Lebiere. 1996. Working memory: activation limitations on retrieval, Cogn. Psychol. 30: 221–256.

  • Borst, J.P. and J.R. Anderson. 2015. Using the ACT-R cognitive architecture in combination with fMRI data. In: (B.U. Forstmann and E.-J. Wagenmakers, eds) An Introduction to model-based cognitive neuroscience. Springer Science + Business Media, New York, pp. 339–352

  • Borst, J.P., N.A. Taatgen and H. van Rijn. 2015. What makes interruptions disruptive? A process-model account of the effects of the problem state bottleneck on task interruption and resumption. In: Proceedings of the CHI 2015, April 18–23 2015. ACM Press, Seoul, Republic of Korea.

  • Brixey, J.J., D.J. Robinson, C.W. Johnson, T.R. Johnson, J.P. Turley and J. Zhang. 2007. A concept analysis of the phenomenon interruption. Adv. Nurs. Sci. 30(1): E26–E42. [Crossref]

  • Cowan, N. 2010. The magical mystery four: how is working memory capacity limited, and why? Curr. Dir. Psychol. Sci. 19(1): 51–57. [Web of Science]

  • Cowan, N., C.C. Morey and Z. Chen, (in press). The legend of the magical number seven. In: (S. Della Sala, ed) Tall tales about the brain: things we think we know about the mind, but ain’t so. Oxford University Press.

  • Gillie, T. and D.E. Broadbent. 1989. What makes interruptions disruptive? A study of length, similarity, and complexity, Psychol. Res. 50: 243–406.

  • Gray, W.D., R.M. Young and S.S. Kirschenbaum. 1997. Introduction to this special issue on cognitive architectures and human-computer interaction. Hum.-Comput. Int. 12: 301–309.

  • Marewski, J.N. and K. Mehlhorn. 2011. Using the ACT-R architecture to specify 39 quantitative process models of decision making. Judgm. Decis. Mak. 6: 439–519.

  • McFarlane, D.C. and K.A. Latorella. 2002. The scope and importance of human interruption in human–computer interaction design. Hum.-Comput. Int. 17: 1–61.

  • Miller, G.A. 1956. The magical number seven plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63: 81–97.

  • Prezenski, S. and N. Russwinkel. 2014. Combining cognitive ACT-R models with usability testing reveals users mental model while shopping with a smartphone application. International Journal on Advances in Intelligent Systems, 7(3–4): 700–715.

  • Salvucci, D.D. and N.A. Taatgen. 2010. The multitasking mind. Oxford University Press, New York.

  • Schunn, C.D. and D. Wallach. 2005. Evaluating goodness-of-fit in comparison of models to data. In: (W. Tack, ed) Psychologie der Kognition: Reden und Vortraege anlaesslich der Emeritierung von Werner Tack. University of Saarland Press, Saarbruecken, pp. 115–154

  • Statista. 2015a. Anzahl der Smartphone-Nutzer in Deutschland in den Jahren 2009 bis 2015 (in Millionen) [Amount of smartphone users in Germany from 2009 to 2015 in millions]. Retrieved from http://de.statista.com/statistik/daten/studie/198959/umfrage/anzahl-der-smartphonenutzer-in-deutschland-seit-2010/ [17 June 2015].

  • Statista 2015b. Prognose zur Anzahl der Smartphone-Nutzer weltweit von 2012 bis 2018 (in Milliarden) [Predicted amount of smartphone users worldwide from 2012 to 2018 in billions]. Retrieved from http://de.statista.com/statistik/daten/studie/309656/umfrage/prognose-zur-anzahl-der-smartphone-nutzer-weltweit/ [17 June 2015].

  • Trafton, J.G., E.M. Altmann, D.P. Brock and F.E. Mintz. 2003. Preparing to resume an interrupted task: effects of prospective goal encoding and retrospective rehearsal. Int. J. Hum.-Comput. St. 58: 583–603.

  • Wickens, C.D., J.G. Hollands, S. Banbury and R Parasuraman. 2013. Engineering psychology and human performance. 4th edition. Pearson Education, Upper Saddle River, New Jersey.

About the article

Maria Wirzberger

Maria Wirzberger, M. Sc. works as research assistant within the interdisciplinary DFG Research Training Group “CrossWorlds” at the TU Chemnitz. In 2012, she received a B. Sc. in Psychology from the University of Hagen, and completed the master’s program Human Factors at the TU Berlin in 2014. Her current PhD project focusses on connecting cognitive modeling and instructional design by exploring the construct of cognitive load with the cognitive architecture ACT-R.

Prof. Dr.-Ing. Nele Russwinkel

Nele Russwinkel holds a junior professorship for Cognitive Modeling in dynamic Human-Machine Systems at the TU Berlin. Based on a B. Sc. and M. Sc. in Cognitive Science from the University of Osnabrueck and some experience in industry, she held a scholarship within the DFG Research Training Group “ProMeTeI” at the TU Berlin, where she obtained her PhD in 2009. Besides others, her research is concerned with cognitive modeling of human-computer interaction on purposes of usability, embodied spatial cognition and time estimation.

Published Online: 2015-07-12

Published in Print: 2015-08-01

Citation Information: i-com, ISSN (Online) 2196-6826, ISSN (Print) 1618-162X, DOI: https://doi.org/10.1515/icom-2015-0033. Export Citation

Comments (0)

Please log in or register to comment.
Log in