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International Journal of Human-Computer Interaction 8

Editors:Gavriel Salvendy; Michael J. Smith; Masamitsu Oshima
Dates:1996
Volume:8
Publisher:Ablex Publishing Corporation
Standard No:ISSN 1044-7318
Papers:29
Links:Table of Contents
  1. IJHCI 1996 Volume 8 Issue 1
  2. IJHCI 1996 Volume 8 Issue 2
  3. IJHCI 1996 Volume 8 Issue 3
  4. IJHCI 1996 Volume 8 Issue 4

IJHCI 1996 Volume 8 Issue 1

Human-Virtual Environment Interaction

Forward: The Interface Will Not Disappear BIB 1-3
  Myron W. Krueger
Multimodal Virtual Reality: Input-Output Devices, System Integration, and Human Factors BIBA 5-24
  Grigore Burdea; Paul Richard; Philippe Coiffet
Virtual reality (VR) involves multimodal interactions with computer-simulated worlds through visual, auditory, and haptic feedback. This article reviews the state of the art in special-purpose input-output devices, such as trackers, sensing gloves, 3-D audio cards, stereo displays, and haptic feedback masters. The integration of these devices in local and network-distributed VR simulation systems is subsequently discussed. Finally, we present human-factor studies that quantify the benefits of several feedback modalities on simulation realism and sensorial immersion. Specifically, we consider tracking and dextrous manipulation task performance in terms of error rates and learning times when graphics, audio, and haptic feedback are provided.
Postural Instability Induced by Virtual Reality Exposure: Development of a Certification Protocol BIBA 25-47
  Robert S. Kennedy; Kay M. Stanney
Exposure to virtual environments often causes users to experience symptoms of motion sickness. An accessory manifestation of motion sickness symptoms is postural disequilibrium. If the postural disequilibrium that occurs persists beyond the time an individual is within the confines of the laboratory or system site, user safety could be compromised and products liability issues could be forthcoming. In this study, a portable, automated postural assessment system is developed that can be employed before and after exposure to a virtual reality (VR) system in order to certify that a user's balance on exiting the system is at least demonstrably as good as it was on entering. It is argued that if the "coming out" balance performance is sufficiently poorer than the "going in" balance, then the user should be retained until the pretest balance performance is regained. The results from a set of normative and validation experiments on postural equilibrium identified several reliable measures of stance that could serve as a basis for certification. Furthermore, a new automated video-based measure using only head movement showed that performance over sessions is stable and reliable. The head movement changes that occur with stimuli, such as alcohol and simulator exposure, are well behaved, predictable, and significant even with small samples. The implication is that the proposed objective measure of postural stability, in conjunction with procedures for obtaining self-reports of symptoms, can afford some measure of certification that exposure to a given VR system is without harm.
Navigating Large Virtual Spaces BIBA 49-71
  Rudolph P. Darken; John L. Sibert
As important as navigation is to human performance in virtual worlds, it is an often overlooked problem in the design process. This article reports an experiment intended to show that real-world wayfinding and environmental design principles are effective in designing virtual worlds that support skilled wayfinding behavior. The study measures participant performance on a complex searching task in a number of virtual worlds with differing environmental cues. The worlds are augmented with either a radial grid, a map, or both a grid and a map. The control condition provided no additional navigational cues. The results showed that navigational performance was superior under both map treatments as compared to the control and grid conditions. The grid was, however, shown to provide superior directional information as compared to the other conditions. The control condition provided the worst performance, with participants often becoming disoriented and experiencing extreme difficulty completing the tasks.
Task-Level Interaction with Virtual Environments and Virtual Actors BIBA 73-94
  David Zeltzer; Swetlana Gaffron
In many virtual environment (VE) applications, the VE system must be able to display accurate models of human figures that can perform routine behaviors and adapt to events in the virtual world. In order to achieve such adaptive, task-level interaction with virtual actors, it is necessary to model elementary human motor skills. SkillBuilder is a software system for constructing a set of motor behaviors for a virtual actor by designing motor programs for arbitrarily complicated skills. Motor programs are modeled using finite state machines, and a set of state machine transition and ending conditions for modeling motor skills has been developed. Using inverse kinematics and automatic collision avoidance, SkillBuilder was used to construct a suite of behaviors for simulating visually guided reaching, grasping, and head-eye tracking motions for a kinematically simulated actor consisting of articulated, rigid body parts. All of these actions have been successfully demonstrated in real time by permitting the user to interact with the virtual environment using a whole-hand input device.
The Virtual Academy: A Simulated Environment for Constructionist Learning BIBA 95-110
  J. Michael Moshell; Charles E. Hughes
The Virtual Academy is an educational model based on multiage teams of students and adults working through the Internet to build and use virtual worlds for educational purposes. These collaborations are mediated by a range of tools ranging from electronic mail to hypermedia and video links, and result in the creation of simulation-based role-playing adventure games within the ExploreNet software environment. ExploreNet is an Internet-based multimedia, multiuser domain constructed specifically for educational experimentation.
   This article describes the Virtual Academy Model, the ExploreNet software system, and an experiment conducted in the spring of 1995. The article describes the evolution of features of ExploreNet's user interface and their relevance to collaborative work by children.

IJHCI 1996 Volume 8 Issue 2

Articles

GENIUS: Generating Software-Ergonomic User Interfaces BIBA 115-144
  Hans-Jorg Bullinger; Klaus-Peter Fahnrich; Anette Weisbecker
GENIUS (GENerator for user Interfaces Using Software-ergonomic rules) comprises a method and the supporting tool environment for the generation of user interfaces from extended data models by means of software-ergonomic rules. The representation of the user interface is based on views defined for the data model. The basic dialogue structure is derived from the data model structure. This ensures the development of task-appropriate user interfaces by transferring the characteristics of the application domain and the user's tasks reflected in the data model to the dialogue structure. The automatic generation of the user interface from the defined views is carried out by a rule-based system with explicit design rules derived from existing guidelines. Output is generated for an existing user interface management system. The software-ergonomic rules in the generation process guarantee the consistent use of interaction objects and a uniformed dialogue structure. The use of the data model as the starting point for the generation of the user interface ensures the integration of software engineering and user interface design by the consistent use of data for application and user interface development. The generation with GENIUS reduces the development effort and improves the quality of the user interface.
A Theory of Command Language Dialogue for a Knowledge-Based Human-Computer Interaction BIBA 145-164
  Celestine A. Ntuen
The flexibility and usability of graphic-based HCIs can be increased by adding a natural language interface with command menus. Among the several other advantages, such embellishment offers the user an opportunity for direct expression of his or her behaviors, goals, intentions, and objectives along the continuum of the task knowledge. The existing graphic-based HCIs that operate on active symbologies and icons assume the user's mental models to correlate with perceptual and cognitive levels of the task understanding. This obviously increases mental loads and the frustration of the human adapting to the system. In reality, the system should be designed to adapt to the user's behavior and skill level. In order to improve the current design of graphic-based HCIs, we have formulated theories of command production language that will enhance the user's ability to interact with the system. The methods developed combine the theory of expert database with formal grammar to develop command-production rules using a natural language dictionary prototype. We show that the commands are linear, regular, and symmetric, although conforming to the formal rules of grammar.
The Importance of Package Features and Learning Factors for Ease of Use BIBA 165-187
  Jennifer D. E. Thomas
In the Information Systems community, the term ease of use has taken on many meanings and interpretations, and various factors said to contribute to it have been investigated. To determine whether studies in this area have focused on the right aspects, or need to be refocused, this study sought to ascertain whether some level of agreement exists among experienced users regarding the importance of various package design and assistance features for ease of use and the support they offer to identified learning dimensions. The results point to some degree of agreement among these users on the importance of individual features for ease of use, though they did not agree on all features. The panel agreed that the identified learning dimensions should be equally supported by package features. There was also reasonable agreement that certain features support certain learning dimensions. The results point to a need to refocus some of the research areas which have been considered important for ease of use and suggest new areas to pursue.
Cognitive Engineering Principles for Enhancing Human-Computer Performance BIBA 189-211
  Jill Gerhardt-Powals
Many computer systems today are not satisfactory to their users. Often the user interface does not receive the attention that it deserves, even though to the user, the interface is the most important part of the computer system. Further, many interfaces are not designed with reference to how humans process information. This research addressed this problem by designing and evaluating a cognitively engineered interface. Cognitive engineering of a human-computer interface is the leveraging of empirical findings from the cognitive sciences and application of those findings to the design of the interface. It was hypothesized that a cognitively engineered interface is superior to interfaces that are not cognitively engineered. Ten cognitive-design principles were extracted from the literature and explicitly applied to the design of an interface. Reaction time, accuracy, workload, and preference for this interface were experimentally determined and compared with that of two other interfaces. The other two interfaces were designed by separate teams for the same problem situation but were not, however, designed with explicit reference to the cognitive design principles. The cognitively engineered interface was found to be superior across all measurements. In fact, a postexperimental analysis also found a strong correlation between performance and the extent to which the 10 design principles were applied in each of the three interfaces. Therefore, based on the experimental results, I concluded that implementing a set of critical cognitive-design principles will produce a "cognitively friendly" interface.

IJHCI 1996 Volume 8 Issue 3

ML [Machine Learning] Meets HCI

Introduction: ML Meets HCI BIB 217-219
  Vassilis Moustakis
Survey of Expert Opinion: Which Machine Learning Method May be Used for Which Task? BIBA 221-236
  Vassilis Moustakis; Mark Lehto; Gavriel Salvendy
Determining the most appropriate Machine Learning (ML) method, system, or algorithm for a particular application is not trivial. This article reports on a survey of 103 experts specializing in ML who were asked to rate ML method appropriateness to intelligent tasks. Ratings were captured via a structured questionnaire including 12 ML methods and 9 task categories. Results showed that the experts mapped particular ML methods to task categories. Factor analysis revealed three fundamental factors, which explained most of the variance in the expert ratings. Machine learning methods could be grouped on the basis of these factors into six application categories, wherein one or more methods were deemed most appropriate by the evaluated group of experts. This, in turn, concludes that cooperation between alternative ML methods may be necessary to support one or more intelligent tasks.
Automated User Modeling for Intelligent Interface BIBA 237-258
  Kenichi Yoshida; Hiroshi Motoda
The analysis of user behavior is one important function of the user-adaptive interface. Such analysis enables understanding of the user's intention and releases the user from tedious tasks often required when using a nonadaptive interface. The acquisition of the user behavior model is crucial. Most studies meant to develop a user-adaptive interface system only analyze the sequence of user behaviors (i.e., command sequence) from which to automate the repetitions. Because the command sequence sometimes does not typify the user's behavior, the user model constructed only from the command sequence does not adequately reproduce the user behavior. This article presents a new framework that also analyzes the computational processes activated by the user commands to build the user behavior model. An important feature of the proposed framework is the analysis of data dependency between the user commands. A user-adaptive interface system, ClipBoard, was developed to show the adequacy of this framework. It analyzes the I/O relations between commands in the past task history, selects the next command, and creates scripts that enable complex task execution by a single command.
Teaching Intelligent Agents: The Disciple Approach BIBA 259-285
  Gheorghe Tecuci; Michael R. Hieb
The ability to build intelligent agents is significantly constrained by the knowledge acquisition effort required. Many iterations by human experts and knowledge engineers are currently necessary to develop knowledge-based agents with acceptable performance. We have developed a novel approach, called Disciple, for building intelligent agents that relies on an interactive tutoring paradigm, rather than the traditional knowledge engineering paradigm. In the Disciple approach, an expert teaches an agent through five basic types of interactions. Such rich interaction is rare among machine learning (ML) systems, but is necessary to develop more powerful systems. These interactions, from the point of view of the expert, include specifying knowledge to the agent, giving the agent a concrete problem and its solution that the agent is to learn a general rule for, validating analogical problems and solutions proposed by the agent, explaining to the agent reasons for the validation, and being guided to provide new knowledge during interaction. In this article, we illustrate these basic learning interactions between an expert and an intelligent agent in the context of teaching the agent for military training simulations.
Different Ways to Support Intelligent Assistant Systems by Use of Machine Learning Methods BIBA 287-308
  Jurgen Herrmann
Intelligent assistant systems provide an adequate organization of human-computer interaction for complex problem solving. These knowledge-based systems are characterized by a cooperative problem-solving procedure. User and system cooperate intensively to produce the aimed result. Machine learning methods can provide significant support for assistant systems. In this article, it is pointed out how assistant systems can be supported in various ways. For instance, machine learning methods can extend, revise, optimize, and adapt the knowledge base of an assistant system. In this way, they can contribute to the utility and maintainability of an intelligent assistant system. They can also increase the flexibility and effectiveness of human-computer interaction.
   The learning apprentice system COSIMA is presented which acquires knowledge about single problem-solving steps from observation of the user. Production rules for floorplanning, a sub-task of VLSI design, are acquired and refined cooperatively by different learning strategies.
A Machine Learning Approach to Knowledge Acquisitions from Text Databases BIBA 309-324
  Yasubumi Sakakibara; Kazuo Misue; Takeshi Koshiba
The rapid growth of data in large databases, such as text databases and scientific databases, requires efficient computer methods for automating analyses of the data with the goal of acquiring knowledges or making discoveries. Because the analyses of data are generally so expensive, most parts in databases remains as raw, unanalyzed primary data. Technology from machine learning (ML) will offer efficient tools for the intelligent analyses of the data using generalization ability. Generalization is an important ability specific to inductive learning that will predict unseen data with high accuracy based on learned concepts from training examples.
   In this article, we apply ML to text-database analyses and knowledge acquisitions from text databases. We propose a completely new approach to the problem of text classification and extracting keywords by using ML techniques. We introduce a class of representations for classifying text data based on decision trees; (i.e., decision trees over attributes on strings) and present an algorithm for learning them inductively. Our algorithm has the following features: It does not need any natural language processing technique and it is robust for noisy data. We show that our learning algorithm can be used for automatic extraction of keywords for text retrieval and automatic text categorization. We also demonstrate some experimental results using our algorithm on the problem of classifying bibliographic data and extracting keywords in order to show the effectiveness of our approach.
Sharing Knowledge with Robots BIBA 325-342
  Kazuo Hiraki; Yuichiro Anzai
Intelligent robots need to share knowledge with human beings for flexible interaction. However, the gap between low-level sensory data and abstract human knowledge makes it difficult to preencode robot behavior against human's various complex demands.
   This article presents a way of enabling robots to learn abstract concepts from sensory and perceptual data. In order to overcome the gap between the low-level sensory data and higher level concept description, a method called feature abstraction is used. Feature abstraction dynamically defines abstract sensors from primitive sensory devices and makes it possible to learn appropriate sensory-motor constraints. This method has been implemented on a real mobile robot as a learning system called Acorn-II. Acorn-II was evaluated with some empirical results and it was shown that the system can learn some abstract concepts more accurately than other existing systems.
The Application of Genetic Algorithms in a Career Planning Environment: CAPTAINS BIBA 343-360
  Eelco den Heijer; Pieter W. Adriaans
In this article, we present experiences with the Crew Availability Planning and Training System (CAPTAINS). CAPTAINS is a complex planning-aid system that assists professional career planners. This article describes the learning component of CAPTAINS -- the Learning Classifier System (LCS) -- which predicts the bids on functions of pilots. We also present experiments with the LCS and their results.

Book Reviews

"Dynamics in Ergonomics, Psychology, and Decisions: Introduction to Ergodynamics," by V. F. Venda and Y. V. Venda BIB 361-362
  Arne Aaras
"Dynamics in Ergonomics, Psychology, and Decisions: Introduction to Ergodynamics," by V. F. Venda and Y. V. Venda BIB 363-364
  Barrett S. Caldwell

IJHCI 1996 Volume 8 Issue 4

Articles

Mood Disturbances and Musculoskeletal Discomfort: Effects of Electronic Performance Monitoring Under Different Levels of VDT Data-Entry Performance BIBA 369-384
  Lawrence M. Schleifer; Traci L. Galinsky; Christopher S. Pan
The effects of electronic performance monitoring (EPM) work management on mood disturbances and musculoskeletal discomfort were evaluated under three levels of data-entry task performance. EPM work management (i.e., performance monitoring and feedback) was used to induce compliance with data-entry performance standards of greater than or equal to 200 keystrokes per minute and less than or equal to six errors per minute. Forty-seven female office workers who had difficulty maintaining the data-entry speed standard were assigned at random to EPM work management or no EPM work management. Participants in both work management conditions were divided into three keystroke performance groups (low, moderate, high). Self-ratings of mood disturbance and musculoskeletal discomfort were recorded at periodic intervals over three consecutive workdays. Regardless of the level of data-entry performance, the increase in perceived time pressure across the workdays was greater under EPM work management than under no EPM work management. Among workers who consistently failed to meet the performance standards (i.e., low and moderate performance), the increases in mood disturbances and musculoskeletal discomfort across the workdays were greater under EPM work management than under no EPM work management. These stress effects were more evident when keystroke rates were relatively close to the standard (moderate performance) than when they were far below the standard (low performance). The results suggest that EPM work management should be employed with performance standards that balance production requirements against the worker's skills and abilities.
The Effect of Degree of Upper Arm Flexion on Shoulder-Neck Discomfort at the VDT BIBA 385-399
  James A. Balliett; Marvin J. Dainoff; Leonard S. Mark
Two experiments investigated the effect of upper extremity posture on reported discomfort in the shoulder-neck region. In Experiment 1, 12 participants worked in two postures that only differed in the position of the arms. The "7° posture" required 7° of upper arm flexion and a 90° upper arm-forearm angle. The "30° posture" required 30° of upper arm flexion and a 90° upper arm-forearm angle. Location and intensity of discomfort were reported every 5 min while participants performed a simple tracking task at the computer. Experiment 2 was identical to the first except participants worked in one of the postures for both work sessions. The 30° posture generally resulted in more frequent and intense reports of shoulder-neck discomfort than the 7° posture. However, the 7° posture was not nearly as effective when it was assumed after the 30° posture. The implications of such carry over effects for VDT work in a seated posture are discussed.
A Longitudinal Study of Health Complaints in Professional Computer Work: Effects of Computer-Aided Design BIBA 401-420
  Svante Hovmark; Eva Frisk Wollberg; Stefan Nordqvist
Employees from the design and manufacturing departments of 4 companies participated in a longitudinal questionnaire and interview study of health complaints related to computer-aided design (CAD). Data was collected on 2 occasions at 4-year intervals. The severity of musculo-skeletal complaints, eye complaints and skin rashes were approximately the same on Occasions 1 and 2. No results demonstrated a relation between the amount of CAD work and the severity of health complaints. There were more musculo-skeletal and eye complaints reported by women than by men, whereas complaints were also more common among older CAD users than younger ones. Participants with a greater work load or less support from leaders reported a greater severity of musculo-skeletal complaints. Great work load and less leader support were not connected with the amount of CAD work.
Ergonomic, Job Task, and Psychosocial Risk Factors for Work-Related Musculoskeletal Disorders among Teleservice Center Representatives BIBA 421-431
  Edward J. Hoekstra; Joseph Hurrell; Naomi G. Swanson; Allison Tepper
A cross-sectional study was conducted to evaluate the association between work-related musculoskeletal disorders (WRMDs) and work conditions, perceived exhaustion, job dissatisfaction, and job-stress issues at two teleservice centers (TSCs). The study covered teleservice representatives who respond to toll-free calls for assistance. The work involves a computer or manual search for information, and data entry using keyboards. One facility had upgraded the furniture at the workstations; the other facility had not. A questionnaire survey among 114 teleservice representatives and an ergonomic evaluation were conducted to determine WRMDs and their risk factors and perceived job stress. A high prevalence of symptoms of WRMDs was found at both TSCs. Suboptimal ergonomic conditions were associated with neck, shoulder, elbow, and back WRMDs, as well as with increased job dissatisfaction. Perceived increased workload variability and lack of job control were associated with the occurrence of neck and back WRMDs, respectively. WRMDs were more frequently reported by teleservice representatives at the center with older furniture and suboptimal ergonomic conditions. WRMDs may be prevented by improving ergonomic conditions at workstations and addressing work-organization elements.
Dynamic Workflow Analysis in a Multiuser Task Context BIBA 433-455
  Gabriel McDermott; Conn Mulvihill
With the ongoing development of computer-mediated collaboration environments, computer-supported collaborative work (CSCW) systems are at hand. An emerging theme is the treatment of dynamic groups. The interest in this article is in the automated construction of dynamic policies for work-flow situations in cooperative environments. The system described in this article operates on the events that are recorded in solving workflow problems. These are analyzed in order to derive policies that may be used to guide future cooperative activities.
Empirical Evaluation of Performance Models of Pointing Accuracy and Speed with a PC Mouse BIBA 457-469
  Atsuo Murata
This study looks at the performance model of mouse movement from the following three viewpoints: (a) effects of the direction of movement on the performance model, (b) optimal formula to define the size of targets in the performance model, and (c) comparison of fit to the pointing time among five performance models. As a result, it was shown that the fit to the experimental data did not differ among four conditions of direction of movement. The contribution of the performance model was found to be the highest when the square of the area of a target is used as the size of a target. Moreover, the performance model based on the multiple-regression analysis was better than that based on Fitts's law.

Book Reviews

"Fundamentals of Artificial Neural Networks," by M. H. Hassoun BIB 471-472
  Baijun Zhao
"C and UNIX: Tools for Software Design," by M. L. Barrett and C. A. Wagner BIB 472-473
  Matthew G. Lerzak
"Extra-Ordinary Human Computer Interaction," by A. Edwards BIB 473-474
  Julie A. Jacko