The influence of conceptual user models on the creation and interpretation of diagrams representing reactive systems

In system design, many diagrams of many different types are used. Diagrams communicate design aspects between members of the development team, and between these experts and the non-expert customers and future users. Mastering the creation of diagrams is often a challenging task, judging by particular errors persistently found in diagrams created by undergraduate computer science students. We assume a possible misalignment between human perception and cognition on the one hand and the diagrams’ structure and syntax on the other. This article presents the results of an investigation of such a misalignment. We focus on the deployment of so-called 'conceptual user models' (mental models, created by users in their mind) at the creation of diagrams. We propose a taxonomy for mental mappings, used for categorization of representations. We describe an experiment where naive and novice subjects created one or several diagrams of a familiar task. We use our taxonomy for analysing these diagrams, both for the represented task structure and the symbols used. The results indeed show a mismatch between mental models and currently used diagram techniques

Representational decisions when learning population dynamics with an instructional simulation

DEMIST is a multi-representational simulation environment that supports understanding of the representations and concepts of population dynamics. We report on a study with 18 subjects with little prior knowledge that explored if DEMIST could support their learning and asked what decisions learners would make about how to use the many representations that DEMIST provides. Analysis revealed that using DEMIST for one hour significantly improved learners' understanding of population dynamics though their knowledge of the relation between representations remained weak. It showed that learners used many of DEMIST's features. For example, they investigated the majority of the representational space, used dynalinking to explore the relation between representations and had preferences for representations with different computational properties. It also revealed that decisions made by designers impacted upon what is intended to be a free discovery environment