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Light Pen Use and Practice Minimize Age and Hand Performance Differences in Pointing Tasks.

, , , and . Hum. Factors, 46 (3): 373-384 (2004)

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Input devices for web browsing: age and hand effects., , , and . Universal Access in the Information Society, 4 (1): 39-45 (2005)Light Pen Use and Practice Minimize Age and Hand Performance Differences in Pointing Tasks., , , and . Hum. Factors, 46 (3): 373-384 (2004)An Integrated Trial-Level Performance Measure: Combining Accuracy and RT to Express Performance During Learning., , , , and . CogSci, page 1029-1034. cognitivesciencesociety.org, (2019)Cognition-Enhanced Machine Learning for Better Predictions with Limited Data., , , , , , , and . Top. Cogn. Sci., 14 (4): 739-755 (2022)Additional acquisition sessions monotonically benefit retention and relearning., , , , and . CogSci, cognitivesciencesociety.org, (2021)Extending the Predictive Performance Equation to Account for Multivariate Performance., , , and . CogSci, cognitivesciencesociety.org, (2022)The Model Human Processor and the older adult: Parameter estimation and validation within a mobile phone task., and . Journal of Experimental Psychology, 13 (4): 224–248 (2007)Using K-means Clustering for Out-of-Sample Predictions of Memory Retention., , , and . CogSci, cognitivesciencesociety.org, (2020)DataShopping for Performance Predictions., , and . HCI (15), volume 9183 of Lecture Notes in Computer Science, page 12-23. Springer, (2015)Combining Cognitive and Machine Learning Models to Mine CPR Training Histories for Personalized Predictions., , , , , , and . EDM, International Educational Data Mining Society, (2021)