Publication statistics
Pub. period:1992-1996
Pub. count:6
Number of co-authors:8
Co-authors
Number of publications with 3 favourite co-authors:
Nancy J. Cooke:4Kelly J. Neville:3Emily Dibble:1 Productive colleagues
Anna L. Rowe's 3 most productive colleagues in number of publications:
Nancy J. Cooke:20Kelly J. Neville:5Jonathan French:3
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Anna L. Rowe
Publications by Anna L. Rowe (bibliography)
Cooke, Nancy J., Neville, Kelly J. and Rowe, Anna L. (1996): Procedural Network Representations of Sequential Data. In Human-Computer Interaction, 11 (1) pp. 29-68.
“Sequential data collected for usability testing, knowledge engineering, or cognitive task analysis are rich with information -- so much that interpretation can often be overwhelming. This dilemma can be viewed as a data reduction problem. PRONET (PROcedural NETworks), a method for reducing sequential data in terms of procedural networks, is introduced and then applied and evaluated in two case studies -- one involving human-computer interaction (HCI) in a simulated mission control operation at the National Aeronautics and Space Administration and the other involving avionics troubleshooting behavior for an intelligent tutor application. The method involves five steps -- collecting data, encoding data, generating transition matrices, conducting Pathfinder analysis, and interpreting procedural networks. The method employs the Pathfinder network scaling algorithm, which is particularly suited for asymmetric data. Evidence is presented to support the descriptive and predictive utility of this form of data reduction. In addition, lessons learned in applying PRONET to the two cases are discussed, applications of PRONET to HCI are described, and guidelines are offered for using PRONET in exploratory sequential data analysis.”
© All rights reserved Cooke et al. and/or Taylor and Francis
Rowe, Anna L., Miller, Todd M., Dibble, Emily and Steuck, Kurt (1995): Knowledge and Performance: Tracking the Development of Expertise. In: Proceedings of the Human Factors and Ergonomics Society 39th Annual Meeting 1995. p. 940.
“Performance in complex tasks may not be a monotonic function of experience. In several domains, an inverted U-shaped function has been observed, with increased error rates being associated with intermediate levels of experience. This contradicts the idea of a linear relationship between the development of expertise and performance levels. A simple monotonic increase in similarity to some ideal knowledge representation may not adequately describe changes in knowledge over time. Cross-sectional research on people with varying levels of expertise at complex tasks supports the idea of distinct stages in the development of expertise and helps account for an increase in errors as people develop new skills. We conducted a longitudinal study of ninth-grade biology students' understanding of certain ecology concepts. Students' mental representations of these concepts were measured three times during a 12-week course. Over the semester, similarity to the knowledge representation of a good student was more predictive of final grades than was similarity to the teachers' expert representation, as was predicted. According to the non-monotonic theory of knowledge development, expert representations are less powerful predictors of student performance because they do not adequately model student knowledge of the domain. These data support the non-monotonic theory of knowledge development by revealing the superiority of the good student representation over the teacher representation.”
© All rights reserved Rowe et al. and/or Human Factors Society
Cooke, Nancy J. and Rowe, Anna L. (1994): Evaluating Mental Model Elicitation Methods. In: Proceedings of the Human Factors and Ergonomics Society 38th Annual Meeting 1994. pp. 261-265.
“Researchers have developed and applied a number of methods for measuring mental models. Unfortunately not only is the mental model construct ill-defined, but the basic research associated with it offers little guidance concerning the selection of a method for a particular application. In this paper a program of research is presented that is designed address this shortcoming. Specifically, the research involves a comparative evaluation of methods to measure mental models on the basis of the relationship between the method's output (i.e., the mental model) and the criterion of primary importance to the problem (e.g., task performance, user acceptance). It is assumed that a method should be selected on the basis of its ability to generate output that is predictive of the criterion of interest. It is likely that because the methods tap different aspects of a mental model, they will predict performance well on some tasks and criteria, but not others. As an example of this approach, data are presented that help to select the best method for measuring technicians' mental models of an electronics troubleshooting task.”
© All rights reserved Cooke and Rowe and/or Human Factors Society
Rowe, Anna L. and Cooke, Nancy J. (1993): An Approach to Identifying Meaningful Action Patterns in Student-Tutor Interactions. In: Proceedings of the Human Factors and Ergonomics Society 37th Annual Meeting 1993. pp. 1281-1285.
“Part of the success of computerized intelligent tutoring systems will be associated with their ability to assess and diagnose students' knowledge in order to direct pedagogical interventions. What is needed is a methodology for identifying general relationships between on-line action patterns and patterns of knowledge derived off-line. Such a methodology would allow an assessment and diagnosis of knowledge, based only on student actions. The focus of this initial research is the development of a means of identifying meaningful action patterns in student-tutor interactions. Actions executed by subjects on a set of verbal troubleshooting tests (Nichols et al., 1989) were summarized using the Pathfinder network scaling procedure (Schvaneveldt, 1990). The results obtained from this work indicate that meaningful patterns of actions can be identified using the Pathfinder procedure. The network patterns are meaningful in the sense that they can differentiate high and low performers as defined by a previous scoring method. In addition, the networks reveal differences between high and low performers suggestive of targets for intervention.”
© All rights reserved Rowe and Cooke and/or Human Factors Society
Rowe, Anna L., French, Jonathan, Neville, Kelly J. and Eddy, Douglas R. (1992): The Prediction of Cognitive Performance Degradations during Sustained Operations. In: Proceedings of the Human Factors Society 36th Annual Meeting 1992. pp. 111-115.
“Opportunities for fatigue related accidents are greatest when extended duty cycles must be maintained. A means to plan for the influence of fatigue would be useful to best utilize crew resources. Equations were derived to predict performance degradations associated with fatigued cognitive abilities. During a 30-hour sleep deprivation study, nine male subjects were required to perform a 45-minute cognitive performance battery every 120 minutes. Plasma melatonin levels also were obtained. Cognitive performance measures sensitive to fatigue were determined and used to derive composite response time and accuracy scores. The equations that best described the composite scores included a linear component (hours awake weighting) and a circadian component (melatonin weighting). The respective prediction equations accounted for 33% of the variance in response time performance (p < .0001) and 18% of the variance in accuracy performance (p < .0005). Tests on the beta weights indicated that accuracy predictions were more enhanced by the circadian component than were those for response time. This work represents a mathematical description of fatigued performance that is sensitive to circadian cycles and requires minimal input data. The results might be used to recommend the best crew rest times and when additional crew should be employed as individual performance falls below critical thresholds during sustained operations.”
© All rights reserved Rowe et al. and/or Human Factors Society
Rowe, Anna L., Cooke, Nancy J., Neville, Kelly J. and Schacherer, Chris W. (1992): Mental Models of Mental Models: A Comparison of Mental Model Measurement Techniques. In: Proceedings of the Human Factors Society 36th Annual Meeting 1992. pp. 1195-1199.
“Although use of the mental model construct has proliferated in recent research, the construct lacks a clear definition and an agreed upon method of measurement. Furthermore, the reliability and validity of the different measurement techniques in use have not been established, thereby making generalizations across studies of mental models difficult. The purpose of the current project was to assess several methods of measuring mental models in terms of their reliability/stability over time. Subjects' mental models of the automobile engine system were elicited on two occasions separated by one week, using seven different knowledge elicitation techniques. Subjects' level of experience was also measured to allow comparisons between experts and novices. The results indicate that each of the measurement techniques tended to be reliable for both experts and novices. However, reliability tended to be greater for experts than novices. Additionally, experts tended to agree with each other more than did the novices. Some evidence also indicated that the results from the similarity ratings and subsequent Pathfinder analysis converged with those from the structured interviews.”
© All rights reserved Rowe et al. and/or Human Factors Society
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