Educational Technology Research and Development

, Volume 65, Issue 5, pp 1135–1151 | Cite as

Designing computer-based learning contents: influence of digital zoom on attention

  • Manuela GlaserEmail author
  • Dominik Lengyel
  • Catherine Toulouse
  • Stephan Schwan
Research Article


In the present study, we investigated the role of digital zoom as a tool for directing attention while looking at visual learning material. In particular, we analyzed whether minimal digital zoom functions similarly to a rhetorical device by cueing mental zooming of attention accordingly. Participants were presented either static film clips, film clips with minimal zoom-ins, or film clips with minimal zoom-outs while eye movements were recorded. We hypothesized that minimal zoom-ins should lead to more gaze coherence, to longer dwell times as an indicator of more elaborative processing, and to fewer transitions as an indicator of less mental integration. Zoom-outs, on the other hand, were expected to have opposite effects. Results showed that zoom-ins increase gaze coherence and dwell times on the center parts of the depictions while decreasing transitions of pictorial elements from the center and the context areas. In contrast, patterns of results from zoom-outs and static presentations were similar to a large degree, indicating that zoom-ins and zoom-outs do not operate in a complementary fashion. Theoretical and practical implications of the present results are discussed.


Zoom Camera Attention Eye-tracking Cueing Gaze coherence 


Compliance with ethical standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in the study involving human participation were in accordance with the ethical standards of the DGPs (Deutsche Gesellschaft für Psychologie, German Psychological Society) and the APA (American Psychological Association) and have been approved by the local Institutional Review Board.


  1. Amadieu, F., Mariné, C., & Laimay, C. (2011). The attention-guiding effect and cognitive load in the comprehension of animations. Computers in Human Behavior, 27, 36–40. doi: 10.1016/j.chb.2010.05.009.CrossRefGoogle Scholar
  2. Bordwell, D. (1985). Narration in the fiction film. Wisconsin: University of Wisconsin Press.Google Scholar
  3. Bordwell, D., & Thompson, K. (2012). Film art: An introduction. New York: McGraw-Hill.Google Scholar
  4. Chandler, P., & Sweller, J. (1991). Cognitive theory and the format of instruction. Cognition and Instruction, 8, 293–332. doi: 10.1207/s1532690xci0804_2.CrossRefGoogle Scholar
  5. Cohen, J. (1977). Statistical power analysis for the behavioral sciences. New York: Academic Press.Google Scholar
  6. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. doi: 10.1037/0033-2909.112.1.155.CrossRefGoogle Scholar
  7. Cutting, J. E., Brunick, K. L., DeLong, J. E., Iricinschi, C., & Candan, A. (2011a). Quicker, faster, darker: Changes in Hollywood film over 75 years. i-Perception, 2, 569–576. doi: 10.1068/i0441aap.CrossRefGoogle Scholar
  8. Cutting, J. E., DeLong, J. E., & Brunick, K. L. (2011b). Visual activity in Hollywood film: 1935 to 2005 and beyond. Psychology of Aesthetics, Creativity, and the Arts, 5(2), 115–125. doi: 10.1037/a0020995.CrossRefGoogle Scholar
  9. Dinh, H. Q., Walker, N., Song, C., Kobayashi, A., & Hodges, L. F. (1999). Evaluating the importance of multi-sensory input on memory and the sense of presence in virtual environments. Proceedings of the IEEE Virtual Reality, 1999, 222–228. doi: 10.1109/vr.1999.756955.CrossRefGoogle Scholar
  10. Dorr, M., Martinetz, T., Gegenfurtner, K. R., & Barth, E. (2010). Variability of eye-movements when viewing dynamic natural scenes. Journal of Vision, 10(10), 28, 1–17. doi: 10.1167/10.10.28.
  11. Eriksen, C. W., & James, J. D. (1986). Visual attention within and around the field of focal attention: A zoom lens model. Perception and Psychophysics, 40(4), 225–240. doi: 10.3758/BF03211502.CrossRefGoogle Scholar
  12. Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size estimates: Current use, calculations, and interpretation. Journal of Experimental Psychology: General, 141(1), 2–18. doi: 10.1037/a0024338.CrossRefGoogle Scholar
  13. Garsoffky, B., Huff, M., & Schwan, S. (2007). Changing viewpoints during dynamic events. Perception, 36(3), 366–374. doi: 10.1068/p5645.CrossRefGoogle Scholar
  14. Glaser, M. (2015). Popular knowledge communication in history magazines from a receptional psychology point of view. In S. Popp, J. Schumann, & M. Hannig (Eds.), Commercialised history: Popular history magazines in Europe (pp. 165–193). Frankfurt am Main: Peter Lang GmbH Internationaler Verlag der Wissenschaften.Google Scholar
  15. Glaser, M., Garsoffky, B., & Schwan, S. (2012). What do we learn from docutainment? Processing hybrid television documentaries. Learning and Instruction, 22, 37–46. doi: 10.1016/j.learninstruc.2011.05.006.CrossRefGoogle Scholar
  16. Glaser, M., & Schwan, S. (2015). Explaining pictures: How verbal cues influence processing of pictorial learning material. Journal of Educational Psychology, 107(4), 1006–1018. doi: 10.1037/edu0000044.CrossRefGoogle Scholar
  17. Hasson, U., Landesman, O., Knappmeyer, B., Vallines, I., Rubin, N., & Heeger, D. J. (2008). Neurocinematics: The neuroscience of film. Projections, 2(1), 1–26. doi: 10.3167/proj.2008.020102.CrossRefGoogle Scholar
  18. Heimann, K., Umilta, M. A., Guerra, M., & Gallese, V. (2014). Moving mirrors: A high-density EEG study investigating the effect of camera movements on motor cortex activation during action observation. Journal of Cognitive Neuroscience, 26(9), 2087–2101. doi: 10.1162/jocn_a_00602.CrossRefGoogle Scholar
  19. Hirumi, A., Kleinsmith, A., Johnsen, K., Kubovec, S., Eakins, M., Bogert, K., et al. (2016). Advancing virtual patient simulations through design research and interPLAY: Part I: Design and development. Educational Technology Research and Development,. doi: 10.1007/s11423-016-9429-6.Google Scholar
  20. Höffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: A meta-analysis. Learning and Instruction, 17, 722–738. doi: 10.1016/j.learninstruc.2007.09.013.CrossRefGoogle Scholar
  21. Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & van de Weijer, J. (2011). Eye tracking. A comprehensive guide to methods and measures. Oxford: Oxford University Press.Google Scholar
  22. Kipper, P. (1986). Television camera movement as a source of perceptual information. Journal of Broadcasting & Electronic Media, 30(3), 295–307. doi: 10.1080/08838158609386625.CrossRefGoogle Scholar
  23. Lan, Y.-J., Fang, S.-Y., Legault, J., & Li, P. (2015). Second language acquisition of Mandarin Chinese vocabulary: Context of learning effects. Educational Technology Research and Development, 63, 671–690. doi: 10.1007/s11423-015-9380-y.CrossRefGoogle Scholar
  24. Lengyel, D., & Toulouse, C. (2011a). Darstellung von Unschärfe in archäologischem Wissen. In A. Scholl, V. Kästner & R. Grüssinger (Eds.), Antikensammlung Staatliche Museen Berlin. Pergamon. Panorama der antiken Metropole (pp. 82–86, weitere Abbildungen S. 68, 69, 73, 77, 78, 79, 146, 165, 252–254, 261–263, 266, 273, 275, 307). Petersberg: Imhof.Google Scholar
  25. Lengyel, D., & Toulouse, C. (2011b). Darstellung von unscharfem Wissen in der Rekonstruktion historischer Bauten. In K. Heine, K. Rheidt, F. Henze, & A. Riedel (Eds.), Von Handaufmaß bis High Tech III. 3D in der historischen Bauforschung (pp. 182–186). Darmstadt/Mainz: Philipp von Zabern.Google Scholar
  26. Lowe, R., & Boucheix, J.-M. (2011). Cueing complex animations: Does direction of attention foster learning processes? Learning and Instruction, 21, 650–663. doi: 10.1016/j.learninstruc.2011.02.002.CrossRefGoogle Scholar
  27. Mayer, R. E. (2009). Multimedia learning. Cambridge: Cambridge University Press. doi: 10.1017/cbo9780511811678.CrossRefGoogle Scholar
  28. Mayer, R. E. (2014). The Cambridge handbook of multimedia learning (2nd ed.). Cambridge: Cambridge University Press. doi: 10.1017/cbo9781139547369.CrossRefGoogle Scholar
  29. Meyerhoff, H. S., Huff, M., & Schwan, S. (2013). Linking perceptual animacy to attention: Evidence from the chasing detection paradigm. Journal of Experimental Psychology: Human Perception and Performance, 39(4), 1003–1015. doi: 10.1037/a0030839.Google Scholar
  30. Müller, N. G., Bartelt, O. A., Donner, T. H., Villringer, A., & Brandt, S. A. (2003). A physiological correlate of the “zoom lens” of visual attention. The Journal of Neuroscience, 23(9), 3561–3565.Google Scholar
  31. Munger, M. P., Dellinger, M. C., Lloyd, T. G., Johnson-Reid, K., Tonelli, N. J., Wolf, K., et al. (2006). Representational momentum in scenes: Learning spatial layout. Memory & Cognition, 34(7), 1557–1568. doi: 10.3758/BF03195919.CrossRefGoogle Scholar
  32. Nakanishi, H., Kato, K., & Ishiguro, H. (2011). Zoom cameras and movable displays enhance social telepresence. In CHI 2011. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 63–72). New York: Association for Computing Machinery. doi: 10.1145/1978942.1978953.
  33. Pasfield-Neofitou, S., Huang, H., & Grant, S. (2015). Lost in second life: Virtual embodiment and language learning via multimodal communication. Educational Technology Research and Development, 63, 709–726. doi: 10.1007/s11423-015-9384-7.CrossRefGoogle Scholar
  34. Poltoratski, S., & Tong, F. (2014). Hysteresis in the dynamic perception of scenes and objects. Journal of Experimental Psychology: General, 143(5), 1875–1892. doi: 10.1037/a0037365.CrossRefGoogle Scholar
  35. Richardson, J. T. E. (2011). Eta squared and partial eta squared as measures of effect size in educational research. Educational Research Review, 6, 135–147. doi: 10.1016/j.edurev.2010.12.001.CrossRefGoogle Scholar
  36. Richter, J., Scheiter, K., & Eitel, A. (2016). Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis. Educational Research Review, 17, 19–36. doi: 10.1016/j.edurev.2015.12.003.CrossRefGoogle Scholar
  37. Salomon, G. (1994). Interaction of media, cognition, and learning. Hillsdale, NJ: Erlbaum.Google Scholar
  38. Salomon, G., & Cohen, A. A. (1977). Television formats, mastery of mental skills, and the acquisition of knowledge. Journal of Educational Psychology, 69(5), 612–619. doi: 10.1037/0022-0663.69.5.612.CrossRefGoogle Scholar
  39. Samida, S. (2009). Zwischen Scylla und Charybdis. Digitale Visualisierungsformen in der Archäologie. In M. Hessler & D. Mersch (Eds.), Logik des Bildlichen. Zur Kritik der ikonischen Vernunft (pp. 258–274). Bielefeld: transcript Verlag.Google Scholar
  40. Schaefer, R. J. (1997). Editing strategies in television news documentaries. Journal of Communications, 47(4), 69–88. doi: 10.1111/j.1460-2466.1997.tb02726.x.CrossRefGoogle Scholar
  41. Schwan, S., & Papenmeier, F. (in press). Learning from animations: From 2D to 3D? In R. Plötzner & R. Lowe (Eds.), Learning from dynamic visualizations: Innovations in research and application. Berlin: Springer.Google Scholar
  42. Smith, T. J. (2012). The attentional theory of cinematic continuity. Projections, 6(1), 1–27. doi: 10.3167/proj.2012.060102.CrossRefGoogle Scholar
  43. Smith, T. J., & Henderson, J. M. (2008). Attentional synchrony in static and dynamic scenes. Journal of Vision, 8(6), 773. doi: 10.1167/8.6.773.CrossRefGoogle Scholar
  44. Tseng, P.-H., Carmi, R., Cameron, I. G. M., Munoz, D. P., & Itti, L. (2009). Quantifying center bias of observers in free viewing of dynamic natural scenes. Journal of Vision, 9(7), 1–16. doi: 10.1167/9.7.4.CrossRefGoogle Scholar
  45. Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: Can it facilitate? International Journal of Human-Computer Studies, 57, 247–262. doi: 10.1006/ijhc.2002.1017.CrossRefGoogle Scholar
  46. Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., et al. (2016). Emotion elicitation: A comparison of pictures and films. Frontiers in Psychology, 7, 180. doi: 10.3389/fpsyg.2016.00180.CrossRefGoogle Scholar
  47. van Gog, T. (2014). The signaling (or cueing) principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 263–278). Cambridge: Cambridge University Press. doi: 10.1017/CBO9781139547369.014.Google Scholar
  48. van Merriënboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 53(3), 5–13. doi: 10.1007/BF02504793.CrossRefGoogle Scholar
  49. Zacharia, Z. C., Manoli, C., Xenofontos, N., de Jong, T., Pedaste, M., van Riesen, S. A. N., et al. (2015). Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: A literature review. Educational Technology Research and Development, 63, 257–302. doi: 10.1007/s11423-015-9370-0.CrossRefGoogle Scholar

Copyright information

© Association for Educational Communications and Technology 2016

Authors and Affiliations

  • Manuela Glaser
    • 1
    Email author
  • Dominik Lengyel
    • 2
    • 3
  • Catherine Toulouse
    • 2
    • 3
  • Stephan Schwan
    • 1
  1. 1.Leibniz-Institut für WissensmedienTuebingenGermany
  2. 2.Brandenburgische Technische Universität Cottbus-SenftenbergCottbusGermany
  3. 3.Brandenburgische Technische Universität Cottbus-SenftenbergCottbusGermany

Personalised recommendations