Wan Chul Yoon

A framework for evaluating the usability of mobile phones based on multi-level, hierarchical model of usability factors

As a mobile phone has various advanced functionalities or features, usability issues are increasingly challenging. Due to the particular characteristics of a mobile phone, typical usability evaluation methods and heuristics, most of which are relevant to a software system, might not effectively be applied to a mobile phone. Another point to consider is that usability evaluation activities should help designers find usability problems easily and produce better design solutions. To support usability practitioners of the mobile phone industry, we propose a framework for evaluating the usability of a mobile phone, based on a multi-level, hierarchical model of usability factors, in an analytic way. The model was developed on the basis of a set of collected usability problems and our previous study on a conceptual framework for identifying usability impact factors. It has multi-abstraction levels, each of which considers the usability of a mobile phone from a particular perspective. As there are goal-means relationships between adjacent levels, a range of usability issues can be interpreted in a holistic as well as diagnostic way. Another advantage is that it supports two different types of evaluation approaches: task-based and interface-based. To support both evaluation approaches, we developed four sets of checklists, each of which is concerned, respectively, with task-based evaluation and three different interface types: Logical User Interface (LUI), Physical User Interface (PUI) and Graphical User Interface (GUI). The proposed framework specifies an approach to quantifying usability so that several usability aspects are collectively measured to give a single score with the use of the checklists. A small case study was conducted in order to examine the applicability of the framework and to identify the aspects of the framework to be improved. It showed that it could be a useful tool for evaluating the usability of a mobile phone. Based on the case study, we improved the framework in order that usability practitioners can use it more easily and consistently.

Age- and experience-related user behavior differences in the use of complicated electronic devices

In this study, we observed the behavior of younger adults (20-29 years old) and middle-aged adults (46-59 years old) interacting with complicated electronic devices. Two recently released multi-functional multimedia devices, namely PMPs (portable multimedia players) and MP3 players were used in the observations. We examined various aspects of interaction behaviors in terms of performance, strategies, error consequences, physical operation methods, and workload. Our analysis of age-related differences included differences in background knowledge as an important independent factor. The results revealed that differences in age meaningfully affected the observed error frequency, the number of interaction steps, the rigidity of exploration, the success of physical operation methods, and subjective perception of temporal demand and performance. In contrast, trial-and-error behavior and frustration levels were influenced by background knowledge rather than age. These novel findings provide important new insights into user interaction characteristics between different age groups and may facilitate the design of age group-appropriate interfaces for complicated electronic devices.

Establishing strict dominance between alternatives with special type of incomplete information

Abstract A special model for establishing dominance with decision makers incomplete information is proposed in multi-attribute decision problem under certainty. Incomplete information is a set of linear inequalities about utilities as well as attribute weights. Since a general model presented in a prior work uses a linear programming technique, a number of linear programs should be solved for checking dominance. With the proposed method, we can check strict dominance between alternatives by simple matrix operation without solving linear programs, thus reducing computational time.

The effects of presenting functionally abstracted information in fault diagnosis tasks

Abstract With respect to the design of visual information display (VID) for process control, this study experimentally evaluated the effectiveness of functionally abstracted information in the task of fault diagnosis. The benefits of functional properties of work domain have been emphasized by ecological interface design (EID), a relatively new design framework for human–machine interfaces. According to the concept of EID, multilevel information representation based on abstraction hierarchy of work domain is expected to be advantageous for supporting the operators problem solving. To investigate the advantage of EID application, an experiment was conducted using a computer-based simulation of the secondary cooling system of nuclear power plants. Three interfaces were compared: the first representing only the physical properties of the process, the second representing purpose-related generalized functions (GFs) in addition to the physical properties, and the third representing abstract functions (AFs) governing the GFs in addition to the physical properties. The results showed that the diagnostic performance was improved by displaying functionally abstracted information at both levels, and that the usefulness of the abstract information was dependent on the complexity of the diagnosis problems.

Deep-reasoning fault diagnosis: an aid and a model

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the humans casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding. >

Design of information content and layout for process control based on goal-means domain analysis

Abstract: With regard to the design of information content in information display, it is often claimed that the abstraction hierarchy (AH) of the work domain should be considered as a basis for identifying and structuring the information content. The primary advantage of AH-based analysis and design is that functionally abstracted information can systematically be identified and provided to the operator, which has rarely been presented in traditional displays. This study evaluated the effectiveness of providing functional information, which was abstracted and represented based on goal–means analysis along the AH, to the operator in two task situations (fault diagnosis and operation). The results showed that the operator’s performance was improved with the high-level information, and the latter’s utility became greater when the goal–means relations between information at different abstraction levels were exhibited. From the results, three design principles for information display can be drawn. First, information should be identified and displayed at multiple abstraction levels. Second, the goal–means relations among the abstraction levels should be explicitly presented, especially for analytical cognitive tasks. Third, information layout should support information integration along decomposition structure within an abstraction level as well as along abstraction levels.

Structured information analysis for human reliability analysis of emergency tasks in nuclear power plants

Abstract Being supported by scarce empirical data, most of the performance influencing factors in human reliability analysis (HRA) have to be assessed on the basis of the analysts knowledge on the human performance in given tasks and their context. Therefore, the outcome of HRA may only be warranted by a proper application of their knowledge based on sufficient information about the tasks and situations. However, most of the HRA methodologies, including the newly developed ones, focus on the provision of cognitive models, error mechanisms, error types and analysis method while leaving the information collection mostly in the hands of the analyst. This paper suggests structured information analysis (SIA), which helps HRA analysts in collecting and structuring such information on tasks and contexts. The SIA consists of three parts: the scenario analysis, the goal-means analysis, and the cognitive function analysis. An expert evaluation showed that this three-part information analysis allowed more expressiveness and hence more confidence on the error prediction than ASEP HRA.

Designing a human-robot interaction framework for home service robot

This paper presents a human-robot interaction framework that outlines a general structure of future home service robots that are expected to assist humans in their home-based daily activities. We describe three interaction modules - multimodal, cognitive, and emotional interaction modules. Each module takes a different role in the process of human robot interaction. The purpose of multi-modal interaction is to make the interaction convenient for the human, the cognitive interaction is for cooperative sharing of tasks, and the emotional interaction is to maintain a close relationship. The general concept for the systematical software integration and the relationships among the three modules are described.

Development and evaluation of a computer-aided system for analyzing human error in railway operations

As human error has been recognized as one of the major contributors to accidents in safety-critical systems, there has been a strong need for techniques that can analyze human error effectively. Although many techniques have been developed so far, much room for improvement remains. As human error analysis is a cognitively demanding and time-consuming task, it is particularly necessary to develop a computerized system supporting this task. This paper presents a computer-aided system for analyzing human error in railway operations, called Computer-Aided System for Human Error Analysis and Reduction (CAS-HEAR). It supports analysts to find multiple levels of error causes and their causal relations by using predefined links between contextual factors and causal factors as well as links between causal factors. In addition, it is based on a complete accident model; hence, it helps analysts to conduct a thorough analysis without missing any important part of human error analysis. A prototype of CAS-HEAR was evaluated by nine field investigators from six railway organizations in Korea. Its overall usefulness in human error analysis was confirmed, although development of its simplified version and some modification of the contextual factors and causal factors are required in order to ensure its practical use.

Supporting the cognitive process of user interface design with reusable design cases

User interface (UI) design is one of the most challenging problem-solving activities that the modern industry faces.The cognitive complexity of design problems and the time pressure due to shortened product life cycles force designers to pursue efficient processes and strategies. For efficiency, UI designers can benefit from their prior design experience that associates target user tasks with available interface means.The practical design activity thus tends to be case-based rather than analytic and linearly deductive.In this paper we develop a framework for a case-based design aid that enables effective reuse of prior design cases in a way that is compatible with practical strategies of designers. In the centre of the framework lies designcase representation at multiple levels of abstraction.The multi-level representation supports the bi-directional and opportunistic strategies of UI designers by enabling easy retrieval of cases at a focused abstraction level and strategy-compatible navigation to related design cases at other levels. A diagrammatic interaction model and a retrieval algorithm based on the model to represent and select design cases are described. It is experimentally verified that the multi-level representation of design cases with the diagrammatic model is useful to UI designers. The overall framework is implemented in a prototype system and the usefulness of the system is shown by examples.