Scientists and information: II. Personal factors in information behaviour
Journal of Documentation
Learning styles and performance in the introductory programming sequence
SIGCSE '02 Proceedings of the 33rd SIGCSE technical symposium on Computer science education
The challenge of information visualization evaluation
Proceedings of the working conference on Advanced visual interfaces
IEEE Computer Graphics and Applications
Acting with Technology: Activity Theory and Interaction Design (Acting with Technology)
Acting with Technology: Activity Theory and Interaction Design (Acting with Technology)
Defining Insight for Visual Analytics
IEEE Computer Graphics and Applications
Using Personality Factors to Predict Interface Learning Performance
HICSS '10 Proceedings of the 2010 43rd Hawaii International Conference on System Sciences
The effects of neuroticism on pair programming: an empirical study in the higher education context
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
GVis: a scalable visualization framework for genomic data
EUROVIS'05 Proceedings of the Seventh Joint Eurographics / IEEE VGTC conference on Visualization
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These current comparative studies expLore the impact of individual differences in personality factors on interface interaction and Learning performance behaviors in both an interactive visualization and a menu-driven web table in two studies. Participants were administered three psychometric measures designed to assess locus of Control, Big Five Extraversion, and Big Five Neuroticism. Participants were then asked to complete procedural learning tasks in each interface. Results demonstrated that all three measures predicted completion times. Additionally, analyses demonstrated that personality factors also predicted the number of insights participants reported whiLe completing the tasks in each interface. Furthermore, we used the psychometric findings in conjunction with a follow-up psychometric survey with a further 50 participants to build initial user profiles based on the cognitive task being undertaken. We discuss how these findings advance our ongoing research in the Personal Equation of Interaction.