Personalization of multi-parameter hearing aids involves an initial fitting followed by a manual knowledge-based trial-and-error fine-tuning from ambiguous verbal user feedback. The result is an often suboptimal HA setting whereby the full potential of modern hearing aids is not utilized. This article proposes an interactive hearing-aid personalization system that obtains an optimal individual setting of the hearing aids from direct perceptual user feedback. Results obtained with ten hearing-impaired subjects show that ten to twenty pairwise user assessments between different settings-equivalent to 5-10 min-is sufficient for personalization of up to four hearing-aid parameters. A setting obtained by the system was significantly preferred by the subject over the initial fitting, and the obtained setting could be reproduced with reasonable precision. The system may have potential for clinical usage to assist both the hearing-care professional and the user.

Due to the large amount of options offered by the vast number of adjustable parameters in modern digital hearing aids, it is becoming increasingly daunting-even for a fine-tuning professional-to perform parameter fine tuning to satisfactorily meet the preference of the hearing aid user. In addition, the communication between the fine-tuning professional and the hearing aid user might muddle the task. In the present paper, an interactive system is proposed to ease and speed up fine tuning of hearing aids to suit the preference of the individual user. The system simultaneously makes the user conscious of his own preferences while the system itself learns the user's preference. Since the learning is based on probabilistic modeling concepts, the system handles inconsistent user feedback efficiently. Experiments with hearing impaired subjects show that the system quickly discovers individual preferred hearing-aid settings which are consistent across consecutive fine-tuning sessions for each user.

This article provides a table with summary statistics for the thirteen usability laboratories described in the papers in this special issue. It also gives an introduction to the main uses of usability laboratories in usability engineering and surveys some of the issues related to practical use of user testing and CAUSE tools for computer-aided usability engineering.

Users who were between 70 and 75 years old with a mean age of 71·8 years were tested using a paint program that could generate a variety of sound effects to accompany and differentiate the paint tools. Even though the sound effects seemed enjoyable to several younger interface analysts, the older users testing the program with sound effects did not find the program more enjoyable than those testing it in a silent mode. Also, the older test users found the interface more difficult to use when they were exposed to the sounds, possibly because they were overwhelmed by the multimedia effects.

Article Free Access Share on Designing usable systems under real-world constraints: a practitioners forum Authors: Robert M. Mulligan View Profile , Mary Dieli View Profile , Jakob Nielsen View Profile , Steven Poltrock View Profile , Daniel Rosenberg View Profile , Susan Erlich Rudman View Profile Authors Info & Claims CHI '92: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsJune 1992 Pages 149–152https://doi.org/10.1145/142750.142777Online:01 June 1992Publication History 7citation529DownloadsMetricsTotal Citations7Total Downloads529Last 12 Months11Last 6 weeks7 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Usability specialists were better than non-specialists at performing heuristic evaluation, and “double experts” with specific expertise in the kind of interface being evaluated performed even better. Major usability problems have a higher probability than minor problems of being found in a heuristic evaluation, but more minor problems are found in absolute numbers. Usability heuristics relating to exits and user errors were more difficult to apply than the rest, and additional measures should be taken to find problems relating to these heuristics. Usability problems that relate to missing interface elements that ought to be introduced were more difficult to find by heuristic evaluation in interfaces implemented as paper prototypes but were as easy as other problems to find in running systems.

Five groups of developers with experience in the design of character-based user interfaces were taught graphical user interface design through a short workshop with a focus on practical design exercises using low-tech tools derived from the PICTIVE method. Several usability problems were found in the designs by applying the heuristic evaluation method, and feedback on these problems constituted a way to make the otherwise abstract usability principles concrete for the designers at the workshop. Based on these usability problems and on observations of the design process, we conclude that object-oriented interactions are especially hard to design and that the developers were influenced by the graphical interfaces of personal computers with which they had interacted as regular users.

Abstract time and at a more or less leisurely pace. For conference The 117 manuscripts submitted for the Hypertext’91 conference were assigned to members of the review committee, using a variety of automated methods based on information retrieval principles and Latent Semantic Indexing. Fifteen reviewers provided exhaustive ratings for the submitted abstracts, indicating how well each abstract matched their interests. The automated methods do a fairly good job of assigning relevant papers for review, but they are still somewhat poorer than assignments made manually by human experts and substantially poorer than an assignment perfectly matching the reviewers ’ own ranking of the papers. A new automated assignment method called “n of 2rz” achieves better performance than human experts by sending reviewers more papers than they actually have to review and then allowing them to choose part of their review load themselves.

User interface standards can be hard to use for developers.In a laboratory experiment, 26 students achieved only 71 % compliance with a two page standard; many violations were due to influence from previous experience with nonstandard systems.In a study of a real company's standard, developers were only able to find 4 of 12 actual deviations in a sample system, and three real products broke between 7 and 12 of the 22 mandatory rules in the standard.Designers were found to rely heavily on the examples in the standard and their experience with other user interfaces.

Article Free Access Share on Designing for international use (panel) Editor: Jakob Nielsen Technical University of Denmark, Department of Computer Science, DK-2800 Lyngby Copenhagen, Denmark Technical University of Denmark, Department of Computer Science, DK-2800 Lyngby Copenhagen, DenmarkView Profile Authors Info & Claims CHI '90: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsMarch 1990 Pages 291–294https://doi.org/10.1145/97243.97298Published:01 March 1990Publication History 12citation668DownloadsMetricsTotal Citations12Total Downloads668Last 12 Months49Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Heuristic evaluation is an informal method of usability analysis where a number of evaluators are presented with an interface design and asked to comment on it. Four ex-periments showed that individual evaluators were mostly quite bad at doing such heuristic evaluations and that they only found between 20 and 51 % of the usability problems in the interfaces they evaluated. On the other hand, we could aggregate the evaluations from several evaluators to a single evaluation and such aggregates do rather well, even when they consist of only three to five people.

A large number of models and definitions of the term ‘model’ are used in the field of human-computer interaction. A taxonomy of the relevant models together with a proposed set of names for the most commonly used types of models is presented. This framework offers a more systematic approach to the use of HCI models than the patch-work of different definitions currently used. Further, a notation is introduced to classify the different kinds of models in a systematic and readable way. The basic for this taxonomy is the definition of the actors of interest in building the models: the user, the designer, the computer system, the researcher, the task domain, the world, and the manual. Each model has one subject (owner) which is one of these actors. Each model also has an object which may be either an actor, a combination of actors, or another model. For example, a metaphor may be considered as a model of the user's actual conceptual model of the computer system (i.e. a class UUC-model: a user's model of a user's model of a computer).

A group of users in Copenhagen were asked to evaluate how important a number of user interface characteristics were for them. The results show high importance of efficient daily use and of possibilities for exploratory learning while tutorial materials were of less importance. Users also were asked to evaluate four usability aspects of a number of popular programs. Results show that the quality pleasant to work with has the largest impact on evaluations of overall user‐friendliness while users seem able to view usability independently from the number of features in an application.

In a field study of use of integrated business software by business professionals, we found several characteristics of the real-world situation leading to the under-utilization of integrated software and being of importance for its human factors. Professionals work in a heterogeneous software environment filled with practical problems, they follow “satisficing” strategies of sub-optimal usage, and they have problems migrating to more advanced uses. Current levels of software integration do not always adequately or easily support the “task integration” requirements of real tasks such as handling many small things.