‘Tokenized’ Dynamic Diagrams: An Approach for Improving Mental Model Construction?
Category
Conference Proceedings
Authors
Boucheix, J-M., Lowe, R.K.
Year
2020
Title
‘Tokenized’ Dynamic Diagrams: An Approach for Improving Mental Model Construction?
Journal / book / conference
Diagrammatic Representation and Inference. book Proceedings of the 11th International Conference, Diagrams 2020, Tallinn, Estonia, August 24–28, 2020. LNAI 12169: Lecture Notes in Artificial Intelligence and Computer Science
Abstract
The Animation Processing Model (APM) is concerned with perceptual and cognitive processes that are central to constructing a high quality mental model from a dynamic depiction of complex subject matter [1]. Mental model theory [2, 3] posits that tokens are fundamental to how the mind represents knowledge – they are the raw material from which mental models are composed. Conventionally-designed comprehensive’
animations depict their subject matter in an essentially literalmanner with characteristics that have little in common with hypothesized properties of tokens [4]. One possible approach for optimizing the effectiveness of animations would be to design them so that internal ‘tokenization’ of the externally presented information is facilitated.
Pages
481-484