Shin’ichi Fukuzumi

User-Centered Design and Evaluation --- The Big Picture

This paper provides a high-level overview of the field of usability evaluation as context for a panel Systematization, Modeling and Quantitative Evaluation of Human Interface in which several authors report on a collaborative effort to apply CogTool, an automated usability evaluation method, to mobile phone interfaces and to assess whether usability predictions made by CogTool correlate with user subjective impressions of usability. If the endeavor, which is still underway at the time of writing, is successful, then CogTool may be applied economically within the product development lifecycle to reduce the risk of usability problems.

Empirical Comparison of Task Completion Time between Mobile Phone Models with Matched Interaction Sequences

CogTool is a predictive evaluation tool for user interfaces. We wanted to apply CogTool to an evaluation of two mobile phones, but, at the time of writing, CogTool lacks the necessary (modeling baseline) observed human performance data to allow it to make accurate predictions about mobile phone use. To address this problem, we needed to collect performance data from both novice users and expert users interactions to plug into CogTool. Whilst novice users for a phone are easy to recruit, in order to obtain observed data on expert users performance, we had to recruit owners of our two target mobile phone models as participants. Unfortunately, it proved to be hard to find enough owners of each target phone model. Therefore we asked if multiple similar models that had matched interaction sequences could be treated as the same model from the point of view of expert performance characteristics. In this paper, we report an empirical experimental exercise to answer this question. We compared identical target task completion time for experts across two groups of similar models. Because we found significant differences in some of the task completion times within one group of models, we would argue that it is not generally advisable to consider multiple phone models as equivalent for the purpose of obtaining observed data for predictive modeling.

Development of Quantitative Usability Evaluation Method

A variety of evaluation methods are practiced in order to make more appealing and improve the usability of computer systems. The authors have developed a quantitative usability evaluation method that uses a checklist that outlines an evaluation procedure and clarifies judging standards. This paper describes this quantitative usability evaluation method that is not influenced by an evaluators subjective impression. Moreover, such clear and precise definitions makes checklist-based evaluations more repeatable (thus more reliable) and less affected by differences among evaluators. The effectiveness of our checklist has been evaluated by the experiments with novice and experienced evaluators. This article reports the method and results of the experiments.

Problems in Usability Improvement Activity by Software Engineers

We develop a support environment for software engineers that combine human centered design (HCD) policy with system development process to improve usability. We verified this support environment experimentally, and we observed that software engineers could not carry out works corresponding to “Analyze context of use”, which is one of HCD activities and is usually done easily by usability engineers. Through this verification process, we found that there is some difficult task about HCD activities for software engineers to carry out.

Clarification of Customers’ “Demand” in Development Process

HCD is a method to give better UX to stakeholders and to provide system and product with high usability for users and stakeholders. When system and product with high usability could be developed, it is easy to verify their usability by usability test. However, it is difficult to check whether these products or system achieve that a user wants to really do it which required in UX white paper. To verify what is thing that users want to do, we discuss what is necessary for development process by analyzing how to take in customer needs to specification from the view point of software engineering and HCD. We propose a phase “acquisition of user demand” before “clarification of user needs” and “specification of user requirements” which are activities of HCD process.

Modeling How to Understand a Target System: Bridging the Gap Between Software Engineers and Usability Experts

In order to investigate the reasons why software engineers fail in design activities concerning usability, we devised a method to model the features of how to understand a target system. It is the method to visualize differences of system understanding between a software engineer and a usability expert from three aspects, namely qualitative difference, quantitative difference, and difference in recognition to the understanding. Moreover we devised three layer model diagram which consists of system function layer, task and workflow layer and user practice field layer, for describing system understanding. We conducted the experiment and interview for software engineers and analyzed them applying this method. This analysis revealed that software engineers who failed in the activities have a tendency to understand tasks correspond to functions, in addition to understanding an entire system from functions. These suggested that their function-based understandings and little recognition to system users and user practice in the field in their everyday design activities are included in their failure reason.

Clarification of Kansei Elements of Attractiveness Related to Usability for Long Term Mobile Phone Users

Recently, in the IT products area, it has become difficult to distinguish among products by function. Usability is one of the most important user requirements for products. And we assume that the other important factor related to distinctiveness among products is Kansei (human sensibility). One of the elements for usability from the viewpoint of Kansei is attractiveness. IT product manufacturers need to consider the user’s Kansei when developing products. By clarifying the mechanism involved in Kansei and by developing a quantitative Kansei element evaluation method, we will be able to develop attractive IT products continuously. We targeted long term users, and we ran a subjective evaluation experiment for attractiveness related to usability including a questionnaire concerning the factors that influenced the judgment of the evaluation and we clarified some of the elements of human interface that influenced Kansei elements of attractiveness related to usability. The results indicate that when people use mobile phones considering accessibility to some function, they feel “kinetic”, “dynamic”, and “refreshing” and when they use mobile phones considering errors when sending an e-mail or making a call, they feel “three dimensional”, “impressive”, “surprising”, “epoch-making”, and “natural” and want to use them. The results also indicate that when they use mobile phones considering ease of inputting text, they feel “good operability”, “hard to make an error”, “controllable as one likes”, “stress-free”, and “want to keep using”.

Issues of Indexing User Experience

Usability and User experience are also important factors for not only suppliers but also users when product, system and service are developed and operated. Though these are often confused, concepts are different. Also about measurement and evaluation, the former targets product, system and service themselves, the latter targets experience using them which includes users. This paper proposes that UX shall be evaluate whether it is “good” or it is “bad” not whether it is “high” or it is “low”. Expected value by before using and real experience value by during/after use are made these a function respectively. And index of UX is a difference between them. From this, to reduce a gap between high expected value and real experience value becomes to provide good UX for developers and providers.

How to Find a Recipe for Success of Popular Smart Phone Applications

The number of smartphone appliances is increasing rapidly. However, it is divided into a popular application and an application not so popular. There must be some recipe for success in the application that is gaining popularity and continuously using by customers.

Influence of “Feel Appetite” by Food Image

In order to understand the structure of food image for “feeling appetite” when user sees the image, words related to “appetite” were extracted experimentally and clustered based on human information processing. Five scale evaluation for 33 items in four clusters, they are “feeling”, “first impression”, “estimation by vision”, “image of the meal scene”, were carried out. The result is obtained that “cool”, “fresh”, “healthy” are not influent to “appetite”.