Queuing Network Modeling of Transcription Typing

Wu, Changxu; Liu, Yili

doi:10.1145/1352782.1352788

Cited by 63 publications

(70 citation statements)

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“…Theories of typing typically assume an important role for schematic representations in the control of keystroke execution (John, 1996;Rumelhart & Norman, 1982;Salthouse, 1986;Wu & Liu, 2008). Schemas refer to node-like summary representation coding the details of motor effectors movements.…”

Section: Discussionmentioning

confidence: 99%

“…In domains such as skilled typing, the focus of our current investigations, successful task performance relies on a series of specific, well-practiced movement patterns for keystroke execution (Rieger, 2004). Models of typing (John, 1996;Rumelhart & Norman, 1982;Salthouse, 1986;Wu & Liu, 2008) assume that reliable keystroke execution is controlled by stable schemas developed through years of practice. Our experiments test the notion that skilled typing could be controlled by episodic memory processes involved in coding the details of individual typing experiences.…”

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confidence: 99%

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Episodic contributions to sequential control: Learning from a typist's touch.

Crump¹,

Logan²

2010

Journal of Experimental Psychology: Human Perception and Perfor

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Sequential control over routine action is widely assumed to be controlled by stable, highly practiced representations. Our findings demonstrate that the processes controlling routine actions in the domain of skilled typing can be flexibly manipulated by memory processes coding recent experience with typing particular words and letters. In two experiments, we extended Masson's (1986) procedure for measuring item-specific learning in the context of acquiring an unfamiliar skill to the highly skilled domain of typing. Skilled typists' performance improved during practice with typing words composed from a specific set of letters. In a transfer phase, performance was fastest for trained words, followed by new words composed of trained letters, and slowest for new words composed of untrained letters. The finding that recent episodic experience with typing particular words and letters influences skilled typing performance holds widespread implications for theories of typing, sequence learning, and motor control.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Episodic contributions to sequential control: Learning from a typist's touch.

Crump¹,

Logan²

2010

Journal of Experimental Psychology: Human Perception and Perfor

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“…In other words, once the task procedures of each individual task are implemented in the model, the model will generate dual-task performance by letting the two streams of entities representing the two individual tasks in a dual task run through the model. With this modeling approach, we have successfully modeled a range of complex tasks, including driving (Liu et al, 2006;Wu & Liu, 2007a) and transcription typing (Wu & Liu, 2008). The PRP modeling work reported in this article is one of our modeling efforts along this direction, focusing on the most basic and fundamental aspect of multitask performance and using closed-form mathematical equations as the modeling method.…”

Section: Discussionmentioning

confidence: 99%

Queuing network modeling of the psychological refractory period (PRP).

Wu¹,

Liu²

2008

Psychological Review

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The psychological refractory period (PRP) is a basic but important form of dual-task information processing. Existing serial or parallel processing models of PRP have successfully accounted for a variety of PRP phenomena; however, each also encounters at least 1 experimental counterexample to its predictions or modeling mechanisms. This article describes a queuing network-based mathematical model of PRP that is able to model various experimental findings in PRP with closed-form equations including all of the major counterexamples encountered by the existing models with fewer or equal numbers of free parameters. This modeling work also offers an alternative theoretical account for PRP and demonstrates the importance of the theoretical concepts of "queuing" and "hybrid cognitive networks" in understanding cognitive architecture and multitask performance.Keywords: psychological refractory period (PRP), cognitive architecture, queuing network, multitask performance, serial and parallel processing Performing multiple tasks at the same time is common in daily life; for example, drivers can steer a car and at the same time talk with friends in the car, and telephone operators can answer customer phone calls and type textual information into a computer. Among the wide range of multiple task situations, the psychological refractory period (PRP) is one of the most basic and simplest forms of a dual-task situation. In a PRP experiment, two reactiontime (RT) tasks are presented close together in time, and participants are asked to perform the two tasks as quickly as possible. Typically, participants' response to the second of the two RT tasks is performed more slowly than to the first when the interval between the presentation times of these two tasks is short. PRP has been studied in laboratories over 100 years, from the behavioral (Creamer, 1963;Kantowitz, 1974;Oberauer & Kliegl, 2004;Pashler, 1984Pashler, , 1994bSchumacher et al., 1999;Solomons & Stein, 1896;Welch, 1898;Welford, 1952) to the neurological level (Jiang, Saxe, & Kanwisher, 2004;Sommer, Leuthold, & Schubert, 2001). It is also the subject of extensive theoretical work and the focal point of an important theoretical controversy between several computational models of cognition. There are several important cognitive models of PRP, including the response-selection bottleneck (RSB) or central bottleneck model proposed by Pashler (1984Pashler ( , 1990Pashler ( , 1994aPashler ( , 1994bPashler ( , 1994c, the executive-process interactive control (EPIC) model proposed by Kieras (1997a, 1997b), and the model based on the ACT-R/perceptual-motor system (ACT-R/PM) proposed by Byrne and Anderson (2001). Each of these models is able to account for some of the important aspects of PRP; however, each appears to encounter at least one experimental counterexample to its predictions (Jiang et al., 2004;Meyer & Kieras, 1997a, 1997bOberauer & Kliegl, 2004;Ruthruff, Pashler, & Klaassen, 2001). Therefore, the questions remain about how to model these experimental results, provide...

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“…From this perspective, years of practice are necessary to build up the requisite procedural knowledge, but that knowledge will not be explicitly available. In typewriting, the paradox of skill is resolved by proposing a hierarchical control system with two nested feedback loops: an inner loop that translates words into keystrokes and controls the movements of the fingers and hands, and an outer loop that connects to language generation and comprehension processes and provides the inner loop with a string of words to type (Crump & Logan, in press -a; Logan & Crump, 2009;Shaffer, 1975; see also John, 1996;Rumelhart & Norman, 1982;Salthouse, 1986;Wu & Liu, 2008). Logan and Crump (2009) suggested that the inner and outer loops are informationally encapsulated, so that the outer loop has no explicit knowledge of what the inner loop is doing.…”

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confidence: 99%