A cognitive model of the roles of diagrammatic representation in supporting unpractised reasoning about probability

Barone, Rossano (2016) A cognitive model of the roles of diagrammatic representation in supporting unpractised reasoning about probability. Doctoral thesis (PhD), University of Sussex.

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Abstract

Cognitive process accounts of the advantages conferred by diagrams in problem solving and reasoning have typically attempted to explain an idealised user or a reasoning system that has equivalent to practised knowledge of the task with the target representation. The thesis investigates the question of how diagrams support users in the process of solving unpractised problems in the domain of probability. The research question is addressed by the design and analysis of an empirical study and cognitive model.

The main experiment required participants (N=8) to solve a set of unpractised probability problems presented by combined text and diagram. Think-aloud and eye-movement protocols together with given solutions were used to infer the content and process of problem interpretation, solution interpretation and task execution strategies employed by participants. The data suggested that the diagram was used to facilitate problem solving in three different ways by: (a) supporting sub-problem identification, (b) supporting prior knowledge of diagrammatic sub-schemes used for interpreting a solution and (c) supporting the process of interpreting and testing the specific meaning of given problem instructions and self-generated solution instructions.

These empirical data were used to develop cognitive models of canonical strategies of the three identified phenomena:

• Sub-problem identification advantages are accounted for by proposing that the spatial semantics of diagrams coupled with competences of the visual-spatial processing system and opportunities for demonstrative interpretation strategies increase the probability of goal-relevant data being made available to central cognition for further processing.
• Framing advantages are accounted for by proposing that represented diagrammatic sub-schemes (e.g. part-whole portions, icon-arrays, 2D containers etc.) facilitate access to existing prior knowledge used to frame, derive, and reason about information analogically within that scheme.
• Advantages in instruction interpretation are related to the specificity of diagrams which support the opportunity to demonstratively test and evaluate the referential meaning of an instruction.

The cognitive model also investigates and evaluates assumptions about the prior knowledge for solving unpractised probability problems; a representational scheme for addressing the co-ordination of sub-goals; a deictic problem representation to support online processing of environmental information, a meta-cognitive processing scheme to address self-argumentation and intention tracking and visual and spatial competences to address the requirements of diagrammatic reasoning. The implications of the cognitive model are discussed with regard to existing accounts of diagrammatic reasoning, probability problem solving (PPS), and unpractised problem solving.

Item Type: Thesis (Doctoral)
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: B Philosophy. Psychology. Religion > BF Psychology > BF0309 Consciousness. Cognition Including learning, attention, comprehension, memory, imagination, genius, intelligence, thought and thinking, psycholinguistics, mental fatigue
Depositing User: Library Cataloguing
Date Deposited: 30 Jun 2016 11:41
Last Modified: 30 Jun 2016 11:41
URI: http://sro.sussex.ac.uk/id/eprint/61658

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