Extending predictive models of exploratory behavior to broader populations

Shari Trewin; John Richards; Rachel Bellamy; Bonnie E. John; Cal Swart; David Sloan

doi:10.1007/978-3-642-21672-5_17

Extending predictive models of exploratory behavior to broader populations

Shari Trewin, John Richards, Rachel Bellamy, Bonnie E. John, Cal Swart, David Sloan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Universal Access in Human-Computer Interaction. Design for All and eInclusion
Subtitle of host publication	6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I
Editors	Constantine Stephanidis
Place of Publication	Berlin
Publisher	Springer
Pages	149-158
Number of pages	10
ISBN (Electronic)	9783642216725
ISBN (Print)	9783642216718
DOIs	https://doi.org/10.1007/978-3-642-21672-5_17
Publication status	Published - 2011
Event	6th International Conference on Universal Access in Human-Computer Interaction - Orlando, United States Duration: 9 Jul 2011 → 14 Jul 2011 http://www.hcii2011.org/

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Volume	6765

Conference

Conference	6th International Conference on Universal Access in Human-Computer Interaction
Abbreviated title	UAHCI 2011
Country/Territory	United States
City	Orlando
Period	9/07/11 → 14/07/11
Other	Held as Part of HCI International 2011
Internet address	http://www.hcii2011.org/

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10.1007/978-3-642-21672-5_17

Cite this

Trewin, S., Richards, J., Bellamy, R., John, B. E., Swart, C., & Sloan, D. (2011). Extending predictive models of exploratory behavior to broader populations. In C. Stephanidis (Ed.), Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I (pp. 149-158). (Lecture notes in computer science; Vol. 6765). Springer . https://doi.org/10.1007/978-3-642-21672-5_17

Trewin, Shari ; Richards, John ; Bellamy, Rachel et al. / Extending predictive models of exploratory behavior to broader populations. Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I. editor / Constantine Stephanidis. Berlin : Springer , 2011. pp. 149-158 (Lecture notes in computer science).

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title = "Extending predictive models of exploratory behavior to broader populations",

abstract = "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.",

author = "Shari Trewin and John Richards and Rachel Bellamy and John, \{Bonnie E.\} and Cal Swart and David Sloan",

year = "2011",

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language = "English",

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pages = "149--158",

editor = "Stephanidis, \{Constantine \}",

booktitle = "Universal Access in Human-Computer Interaction. Design for All and eInclusion",

note = "6th International Conference on Universal Access in Human-Computer Interaction , UAHCI 2011 ; Conference date: 09-07-2011 Through 14-07-2011",

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Trewin, S, Richards, J, Bellamy, R, John, BE, Swart, C & Sloan, D 2011, Extending predictive models of exploratory behavior to broader populations. in C Stephanidis (ed.), Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I. Lecture notes in computer science, vol. 6765, Springer , Berlin, pp. 149-158, 6th International Conference on Universal Access in Human-Computer Interaction , Orlando, United States, 9/07/11. https://doi.org/10.1007/978-3-642-21672-5_17

Extending predictive models of exploratory behavior to broader populations. / Trewin, Shari; Richards, John; Bellamy, Rachel et al.
Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I. ed. / Constantine Stephanidis. Berlin: Springer , 2011. p. 149-158 (Lecture notes in computer science; Vol. 6765).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Swart, Cal

AU - Sloan, David

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N2 - 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.

AB - 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.

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Trewin S, Richards J, Bellamy R, John BE, Swart C, Sloan D. Extending predictive models of exploratory behavior to broader populations. In Stephanidis C, editor, Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I. Berlin: Springer . 2011. p. 149-158. (Lecture notes in computer science). doi: 10.1007/978-3-642-21672-5_17

Extending predictive models of exploratory behavior to broader populations

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