TY - GEN
T1 - Using naturalistic typing to update architecture typing constants
AU - Burns, Marc T.
AU - Ritter, Frank E.
AU - Zhang, Xiaolong Luke
N1 - Funding Information:
Portions of this work were funded by ONR (N00014-15-1-2275 & N00014-11-1-0275). Chris Dancy, P. Greg Plumb, and Jon Morgan helped gather this data. We thank our colleagues who gave us their time and keystroke logs, and Ysabelle Coutu and Dan Guzek for comments on this paper.
Publisher Copyright:
Copyright © TRECVID 2016.All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2016
Y1 - 2016
N2 - Despite the near-ubiquity of graphic user interfaces for navigating the digital and virtual space, relatively little is known about their naturalistic usage. We start to address two questions. First, how do people use computers outside of laboratory studies? This includes what we can we determine about user behavior by analyzing detailed user logs. Second, can we update the constants in user and cognitive models for predicting typing time based on naturalistic behavior? We thus recorded naturalistic logs of 45 users over 219 sessions providing 1,865 hours of behavior (average session=8.18 hours). The analyses of keystroke times are sensitive to the definition of typing (e.g., how close keys are to be counted as continuous typing), and comparisons will need to provide clear definitions or tradeoff curves. Using this data, we updated the typing and homing constants of the Keystroke-Level Model (Card, Moran, & Newell, 1983), a theory of interface behavior used to provide constants for many cognitive architectures. The results suggest that people are typing faster than previously believed based on the 1983 KLM predictions; homing (moving one’s hand from mouse to keyboard and keyboard to mouse) occur frequently, and now appear to be different events and thus require separate constants.
AB - Despite the near-ubiquity of graphic user interfaces for navigating the digital and virtual space, relatively little is known about their naturalistic usage. We start to address two questions. First, how do people use computers outside of laboratory studies? This includes what we can we determine about user behavior by analyzing detailed user logs. Second, can we update the constants in user and cognitive models for predicting typing time based on naturalistic behavior? We thus recorded naturalistic logs of 45 users over 219 sessions providing 1,865 hours of behavior (average session=8.18 hours). The analyses of keystroke times are sensitive to the definition of typing (e.g., how close keys are to be counted as continuous typing), and comparisons will need to provide clear definitions or tradeoff curves. Using this data, we updated the typing and homing constants of the Keystroke-Level Model (Card, Moran, & Newell, 1983), a theory of interface behavior used to provide constants for many cognitive architectures. The results suggest that people are typing faster than previously believed based on the 1983 KLM predictions; homing (moving one’s hand from mouse to keyboard and keyboard to mouse) occur frequently, and now appear to be different events and thus require separate constants.
UR - http://www.scopus.com/inward/record.url?scp=85058960476&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058960476&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85058960476
T3 - Proceedings of ICCM 2016 - 14th International Conference on Cognitive Modeling
SP - 169
EP - 174
BT - Proceedings of ICCM 2016 - 14th International Conference on Cognitive Modeling
A2 - Reitter, David
A2 - Ritter, Frank E.
PB - The Pennsylvania State University
T2 - 14th International Conference on Cognitive Modeling, ICCM 2016
Y2 - 3 August 2016 through 6 August 2016
ER -