We describe the motivation for research aimed at extending predictive cognitive modeling of non-expert users to a broader population. Existing computational cognitive models have successfully predicted the navigation behavior of users exploring unfamiliar interfaces in pursuit of a goal. This paper explores factors that might lead to significant between-group differences in the exploratory behavior of users, with a focus on the roles of working memory, prior knowledge, and information-seeking strategies. Validated models capable of predicting novice goal-directed exploration of computer interfaces can be a valuable design tool. By using data from younger and older user groups to inform the development of such models, we aim to expand their coverage to a broader range of users. © 2011 Springer-Verlag.
CITATION STYLE
Trewin, S., Richards, J., Bellamy, R., John, B. E., Swart, C., & Sloan, D. (2011). Extending predictive models of exploratory behavior to broader populations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6765 LNCS, pp. 149–158). https://doi.org/10.1007/978-3-642-21672-5_17
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