Predictive human performance modeling made easy

Although engineering models of user behavior have enjoyed a rich history in HCI, they have yet to have a widespread impact due to the complexities of the modeling process. In this paper we describe a development system in which designers generate predictive cognitive models of user behavior simply by demonstrating tasks on HTML mock-ups of new interfaces. Keystroke-Level Models are produced automatically using new rules for placing mental operators, then implemented in the ACT-R cognitive architecture. They interact with the mock-up through integrated perceptual and motor modules, generating behavior that is automatically quantified and easily examined. Using a query-entry user interface as an example [19], we demonstrate that this new system enables more rapid development of predictive models, with more accurate results, than previously published models of these tasks. Author Keywords Cognitive modeling, GOMS, KLM. ACM Classification Keywords

• Type: Conference
• Year: 2004
• Where: CHI
• Authors: Bonnie E. John, Konstantine C. Prevas, Dario D. Salvucci, Kenneth R. Koedinger
• Keywords: ACT-R Cognitive Architecture, CHI 2004, Human Computer Interaction, Keywords Cognitive Modeling, Predictive Cognitive Models