Cognitive Load Effects on End User Understanding of Conceptual Models: An Experimental Analysis

According to Cognitive Load Theory (CLT), presenting information in a way that cognitive load falls within the limitations of working memory can improve speed and accuracy of understanding, and facilitate deep understanding of information content. This paper describes a laboratory experiment which investigates the effects of reducing cognitive load on end user understanding of conceptual models. Participants were all naive users, and were given a data model consisting of almost a hundred entities, which corresponds to the average-sized data model encountered in practice. One group was given the model in standard Entity Relationship (ER) form and the other was given the same model organised into cognitively manageable “chunks”. The reduced cognitive load representation was found to improve comprehension and verification accuracy by more than 50%, though conflicting results were found for time taken. The practical significance of this research is that it shows that managing cognitive load can improve end user understanding of conceptual models, which will help reduce requirements errors. The theoretical significance is that it provides a theoretical insight into the effects of complexity on understanding of conceptual models, which have previously been unexplored. The research findings have important design implications for all conceptual modelling notations.

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