Research Questions

  • How do learners process animations that depict complex dynamic subject matter differently when presented with 1) a highly realistic animation; 2) a professionally designed animation; and 3) a compositional animation based on the Animation Processing Model?
  • How can we leverage crowdsourcing to assess these animations at a large scale, using a novel web-based interactive assessment tool?

Publication

Research in progress.

Highlights

  • Ant locomotion, a complex dynamic mechanism, will be depicted in three animated visual stimuli: 1) highly realistic, 2) professionally designed, and 3) APM-based animations
  • A web-based 3D manipulable ant model will be used as a measurement instrument, accessible to the public
  • Our study hopes to uncover effective design principles that are applicable across a range of subject areas

Helping learners compose high quality mental models of dynamic content

Contributors

Project summary

Animated scientific visualizations are now commonly used to present unfamiliar and complex dynamic subject matter to learners. It is widely assumed that by making dynamic information explicit, such animations are intrinsically effective in helping learners acquire high quality internal representations (mental models) of the to-be-learned subject matter. However, recent research shows that the educational potential of animations is too often not fulfilled. Understanding how learners actually process dynamic visualizations is likely to be fundamental to rethinking the design of animated media. In particular, we need to consider what type of external representation could foster the processes required for learners to build the best possible internal representation.

The five-phase Animation Processing Model (APM) specifies the processing activities learners need to carry out in order to build a mental model from a complex animation. It particularly targets the type of animations that currently dominate education – those that present a comprehensive depiction of the visuospatial and temporal characteristics of the referent subject matter.

These orthodox educational animations tend to be of two main types (i) realistic animations whose sole purpose is to go no further than faithfully portraying the subject matter’s appearance and behaviour (ii) professionally designed animations that not only provide this necessary information about appearance and behaviour, but also include features (such as added cues or different views) specifically intended to support learner processing. According to the APM, the processing of either of these comprehensive forms of animation requires learners first to decompose the continuous dynamic flux of presented information to extract its individual component event units (i.e., graphic entities plus their associated temporal changes). The event units thus extracted (APM Phase 1 processing) provide the raw material for use in the other four processing phases through which a mental model of the referent content is progressively composed in the learner’s mind.

Unfortunately, learner decomposition of the animation can go seriously astray due to factors such as mismatches between perceptual salience (how noticeable information is) and thematic relevance (the information’s importance). Although the resulting event unit extraction problems are most severe with realistic animations which contain no perceptual guidance for the learner, they can still be considerable with professionally designed animations that try to provide such guidance. Because Phase 1 decomposition problems result in poor raw material for subsequent composition processes, they compromise the quality of the learner’s ultimate mental model. One possible way to avoid these negative effects would be to relieve learners of the need to decompose the external representation at all by providing them with a ready decomposed raw material that is optimised for composing high quality mental models. In this novel compositional approach, optimal raw material would be provided to learners in the form of relation sets. These are small groupings of event units whose characteristics are specifically designed to facilitate mental model building processes by tailoring the external representation to the constraints and proclivities of the human information processing system.

Diagram depicting various relationsets of ant locomotion

Funding

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