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Human Factors

Web:
hfes.org/publications/HFJournal.html
Publisher:
Human Factors Society
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Example publications from this periodical

The following articles are from "Human Factors":

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Volume 24
Issue 3

Mandal, A. C. (1982): Correct Height of School Furniture. In Human Factors, 24 (3) pp. 257-....

Volume 26
Issue 4

Carroll, John M. and Carrithers, C. (1984): Blocking learner error states in a training-wheels system. In Human Factors, 26 (4) pp. 377-389.

Volume 40

Ziefle, Martina (1998): Effects of display resolution on visual performance. In Human Factors, 40 (4) pp. 554-568.

Volume 41
Issue 1

Bay, Susanne and Ziefle, Martina (2005): Children Using Cellular Phones. The Effects of shortcomings in user Interface Design. In Human Factors, 41 (1) pp. 158-168.

Volume 45

Peebles, David J. and Cheng, Peter C-H. (2003): Modelling the effect of task and graphical representations on response latencies in a graph-reading task. In Human Factors, 45 (1) pp. 28-45.

Volume 46
Issue 2

Luximon, A. and Goonetilleke, Ravindra S. (2004): Foot Shape Modeling. In Human Factors, 46 (2) pp. 304-315. Available online

This study is an attempt to show how a "standard" foot can be parameterized using foot length, foot width, foot height and a measure of foot curvature so that foot shape can be predicted using these simple anthropometric measures. The prediction model was generated using forty Hong Kong Chinese males, and the model was validated using a different group of twenty-five Hong Kong Chinese males. The results show that each individual foot shape may be predicted to a mean accuracy of 2.1 mm for the left foot and 2.4 mm for the right foot. Application of this research includes the potential design and development of custom footwear without the necessity of expensive three-dimensional scanning of feet.

© All rights reserved Luximon and Goonetilleke and/or Human Factors Society

Volume 47
Issue 1

Sutter, Christine and Ziefle, Martina (2005): Users' Expertise: A biasing Factor for Performance and Usability of Notebook Input Devices. In Human Factors, 47 (1) pp. 169-187.

Volume 49
Issue 5

Capra, Miranda G. (2005): Factor analysis of card sort data: an alternative to hierarchical cluster analysis. In Human Factors, 49 (5) pp. 691-695.

Software and product designers use card sorting to understand item groups and relationships. In the usability community, a common method of formal statistical analysis for open card sort data is hierarchical cluster analysis, which results in a tree of the items sorted into distinct, nested clusters. Hierarchical cluster analysis is appropriate for highly structured settings, like software menus. However, many situations call for softer clusters, such as designing websites where multiple pages link to the same target page. Factor analysis summarizes the categories created in card sorts and generates clusters that can overlap. This paper explains how to prepare card sort data for statistical analysis, describes the results of factor analysis and how to interpret them, and discusses when hierarchical cluster analysis and factor analysis are appropriate.

© All rights reserved Capra and/or Human Factors Society

Issue 4

Oetjen, Sophie and Ziefle, Martina (2007): The Effects of LCDs Anisotropy on the Visual Performance of Users of Different Ages.. In Human Factors, 49 (4) pp. 619-627.

Objective: The present study examined the visual discrimination speed and accuracy while using an LCD and a CRT display. Background: LCDs have ergonomic advantages, but their main disadvantage is that they provide inconsistent photometric measures depending on the viewing angle (anisotropy). Method: Independent variables were screen type (LCD and CRT), viewing angle (0, 11, 41, 50, and 56) and user's age (teenagers, young adults, and middle-aged adults). Dependent variables were speed and accuracy in a visual discrimination task and user's ratings. Results: The results corroborated the negative impact of LCD anisotropy. Visual discrimination times were by 7.6% slower when an LCD was used instead of a CRT. Performance differences increased with increasing viewing angle for both screens, but performance decrements were larger for the LCD. Young adults showed the best visual performance, as compared with teenagers and middle-aged adults. Effects of anisotropy were found for all age groups, although the performance of middle-aged adults was affected more when extended viewing angles were adopted. Conclusion: LCD anisotropy is a limiting factor for visual performance, especially in work settings where fast and accurate reactions are necessary. Application: The outcomes of this research allow ergonomic guidelines for electronic reading.

© All rights reserved Oetjen and Ziefle and/or Human Factors Society

Oetjen, Sophie and Ziefle, Martina (2007): The Effects of LCDs Anisotropy on the Visual Performance of Users of Different Ages. In Human Factors, 49 (4) .

Volume 50

Neth, Hansjorg, Khemlani, Sangeet S. and Gray, Wayne D. (2008): Neth, H., Khemlani, S.S., & Gray, W.D. (2008). Feedback Design for the Control of a Dynamic Multitasking System: Dissociating Outcome Feedback from Control Feedback. In Human Factors, 50 (4) p. 643651. Available online

Objective: We distinguish outcome feedback from control feedback to show that suboptimal performance in a dynamic multitasking system may be caused by limits inherent to the information provided rather than human resource limits. Background: Tardast is a paradigm for investigating human multitasking behavior, complex system management, and supervisory control. Prior research attributed the suboptimal performance of Tardast operators to poor strategic task management. Methods: We varied the nature of performance feedback in the Tardast paradigm to compare continuous, cumulative feedback (global feedback) on performance outcome with feedback limited to the most recent system state (local feedback). Results: Participants in both conditions improved with practice, but those with local feedback performed better than those with global feedback. An eye gaze analysis showed increased visual attention directed toward the feedback display in the local feedback condition. Conclusion: Predicting performance in the control of a dynamic multitasking system requires understanding the interactions between embodied cognition, the task being performed, and characteristics of performance feedback. In the current case, at least part of what had been diagnosed as a deficit caused by limited cognitive resources has been shown to be data limited. Application: Perfect outcome feedback can provide inadequate control feedback.Instances of suboptimal performance can be alleviated by better feedback design that takes into account the temporal dynamics of the human-system interaction.

© All rights reserved Neth et al. and/or Human Factors Society

Issue 3

Gray, Wayne D. (2008): Cognitive architectures: Choreographing the dance of mental operations with the task environments. In Human Factors, 50 (3) pp. 497-505.

Objective: In this paper, I present the ideas and trends that have given rise to the use of cognitive architectures in human factors, provide a cognitive-engineering-oriented taxonomy of these architectures, and a snapshot of their use for cognitive engineering. Background: Architectures of cognition have had a long history in human factors but a brief past. The long history entails a 50 yr preamble, whereas the explosion of work in the current decade reflects the brief past. Understanding this history is key to understanding the current and future prospects for applying cognitive science theory to human factors practice. Method: The review defines three formative eras in cognitive engineering research; the 1950s, 1980s, and now. Results: In the first era the fledging fields of Cognitive Science and Human Factors emphasized characteristics of the dancer, the limited capacity or bounded rationality view of the mind, and the ballroom, the task environment. The second era emphasized the dance; i.e., the dynamic interaction between mental operations and task environment. The third era has seen the rise of cognitive architectures as tools for choreographing the dance of mental operations within the complex environments posed by human factors practice. Conclusions: Hybrid architectures present the best vector for introducing Cognitive Science theories into a renewed engineering-based Human Factors. Application: The taxonomy provided in the paper may provide guidance on when and whether to apply a cognitive science or a hybrid architecture to a human factors issue.

© All rights reserved Gray and/or Human Factors Society

Volume 59
Issue 4

Oetjen, Sophie and Ziefle, Martina (2007): The Effects of LCD Anisotropy on the Visual Performance of Users of different Ages. In Human Factors, 59 (4) pp. 619-627.

Objective: The present study examined the visual discrimination speed and accuracy while using an LCD and a CRT display. Background: LCDs have ergonomic advantages, but their main disadvantage is that they provide inconsistent photometric measures depending on the viewing angle (anisotropy). Method: Independent variables were screen type (LCD and CRT), viewing angle (0, 11, 41, 50, and 56) and user's age (teenagers, young adults, and middle-aged adults). Dependent variables were speed and accuracy in a visual discrimination task and user's ratings. Results: The results corroborated the negative impact of LCD anisotropy. Visual discrimination times were by 7.6% slower when an LCD was used instead of a CRT. Performance differences increased with increasing viewing angle for both screens, but performance decrements were larger for the LCD. Young adults showed the best visual performance, as compared with teenagers and middle-aged adults. Effects of anisotropy were found for all age groups, although the performance of middle-aged adults was affected more when extended viewing angles were adopted. Conclusion: LCD anisotropy is a limiting factor for visual performance, especially in work settings where fast and accurate reactions are necessary. Application: The outcomes of this research allow ergonomic guidelines for electronic reading.

© All rights reserved Oetjen and Ziefle and/or Human Factors Society

 

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Page maintainer: The Editorial Team
How to cite/reference this page
URL: http://www.interaction-design.org/references/periodicals/human_factors.html

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