Is enriching static-simultaneous visualizations with motion-indicating arrows helpful for learning about locomotion patterns?

Is enriching static-simultaneous visualizations with motion-indicating arrows helpful for learning about locomotion patterns? Birgit Imhof (b.imhof@iwm-kmrc.de) Katharina Scheiter (k.scheiter@iwm-kmrc.de) Jorg Edelmann (edelmann@gris.uni-tuebingen.de) Julian von Ulardt (julian.von-ulardt@student.uni-tuebingen.de) Peter Gerjets (p.gerjets@iwm-kmrc.de) Knowledge Media Research Center, Konrad-Adenauer-Strasse 40, 72072 Tuebingen, Germany Abstract In the current study, multiple static-simultaneous visualizations were combined with motion-indicating arrows and were compared either to multiple static-simultaneous visualizations without arrows, which proved to be effective in former studies concerning static visualizations, or to a single static visualization enriched with motion-indicating arrows. Seventy-one students were randomly assigned to the three conditions. Learning outcomes were measured by pictorial tests at three difficulty levels. Contrary to our expectations the results showed that the combined condition (multiple static- simultaneous visualizations with arrows) was worse than both other conditions on the critical intermediate tests. Therefore, it seems that multiple static-simultaneous visualizations without any further enriching components and single static visualizations with motion-indicators have their own facilitating effects on fostering mental animation. These effects are possibly caused either by supporting comparisons among simultaneously presented multiple pictures or by showing the dynamic information (more) explicitly and thereby stimulating and guiding mental imagery of the movements, respectively. Keywords: learning; multiple static-simultaneous visualizations; enriching static visualizations; motion- indicating arrows; spatial ability. Learning about Locomotion Patterns Learning about biological locomotion patterns is a task that addresses a highly dynamic process rendering it essential to acquire a correct understanding of the continuity of different movements. Recognizing locomotion patterns is essential for human beings, since a prolific interaction with the environment relies on fast, exact interpretations of objects and their movements (Chatterjee, Freyd, & Shiffrar, 1996). The use of dynamic visualizations seems to be an appropriate strategy to convey knowledge about locomotion patterns (i.e., dynamic processes; e.g., Hoffler & Leutner, 2007; Tversky, Bauer-Morrison, & Betrancourt, 2002). The option to explicitly depict changes over time and space in dynamic visualizations offers learners the possibility to directly observe the continuity of these changes (Lowe, 2003). Thus, there is no need for learners to infer changes, as it would be the case with static pictures (cf. mental animation; Hegarty, 1992). On the other hand, dynamic visualizations may impose high perceptual and cognitive demands onto learners. First, these demands are caused by the transience of dynamic visualizations, where learners have to keep previously shown information in memory to integrate it with later information (e.g., Hegarty, 2004; Lowe, 1999). Moreover, there are often several things going on at the same time in dynamic visualizations and therefore learners have to divide their attention among multiple locations in the display. This is particularly a problem, if the relevant aspects are not the most salient ones, because then learners almost automatically may be distracted by other salient, but irrelevant dynamic aspects (Lowe, 2003). For these reasons, dynamic visualizations may sometimes yield equal performance compared to static visualizations or under specific circumstances static visualizations may even prove to be superior (e.g., Mayer et al., 2005). One may argue that static visualizations can be helpful for understanding continuous changes, despite the fact that they do not show these changes explicitly, if they are designed in a way that facilitates mental animation (e.g., Paas, Van Gerven, & Wouters, 2007). There are, at least, two different possible solutions to facilitate mental animation in static visualizations. Firstly, depicting multiple states by means of multiple static pictures seems to be an adequate strategy to present information in static visualizations in a way that facilitates mental animation, because with multiple pictures different positions of objects relevant for mentally reconstructing the movements can be shown explicitly (e.g., Imhof et al., 2010). Information on these different positions is likely to be required to infer the continuity by means of interpolation between the depicted states of relevant objects and their positions. Secondly, another strategy to facilitate mental animation in static visualizations is to enrich them with motion-indicating arrows (e.g., Munzer, Seufert, & Brunken, 2009). This can be helpful to indicate the continuous changes in static visualizations. Instead of interpolating between different states, learners are encouraged to extract and process the information of the