Making it easier for older people to talk to smart homes: the effect of early help prompts

It is well known that help prompts shape how users talk to spoken dialogue systems. This study investigated the effect of help prompt placement on older users’ interaction with a smart home interface. In the dynamic help condition, help was only given in response to system errors; in the inherent help condition, it was also given at the start of each task. Fifteen older and sixteen younger users interacted with a smart home system using two different scenarios. Each scenario consisted of several tasks. The linguistic style users employed to communicate with the system (interaction style) was measured using the ratio of commands to the overall utterance length (keyword ratio) and the percentage of content words in the user’s utterance that could be understood by the system (shared vocabulary). While the timing of help prompts did not affect the interaction style of younger users, it was early task-specific help supported older users in adapting their interaction style to the system’s capabilities. Well-placed help prompts can significantly increase the usability of spoken dialogue systems for older people.     

Pull-down versus traditional menu types: an empirical comparison

An experiment was conducted to test the performance of pull-down versus traditional or explicit menus. Sixty subjects, including novice and experienced computer users, manipulated both types of menus to complete banking tasks similar to those found on Automatic Teller M achines. The order of the menus was randomly varied to control for learning effects. Across both types of users, traditional-style menus elicited fewer errors than did pull-down menus; however, no significant difference was found in the time to complete the banking task. Experienced users outperformed novice users in the amount of time taken to complete the task regardless of menu type, though no difference was found in the number of errors committed by both user types.     

Pull-down versus traditional menu types: An empirical comparison

An experiment was conducted to test the performance of pull-down versus traditional or explicit menus. Sixty subjects, including novice and experienced computer users, manipulated both types of menus to complete banking tasks similar to those found on Automatic Teller M achines. The order of the menus was randomly varied to control for learning effects. Across both types of users, traditional-style menus elicited fewer errors than did pull-down menus; however, no significant difference was found in the time to complete the banking task. Experienced users outperformed novice users in the amount of time taken to complete the task regardless of menu type, though no difference was found in the number of errors committed by both user types.     

The role and design of screen images in software documentation

Abstract Software documentation for the novice user typically must try to achieve at least three goals: to support basic knowledge and skills development; to prevent or support the handling of mistakes, and to support the joint handling of manual, input device and screen. This paper concentrates on the latter goal. Novice users often experience split‐attention problem due to the need to (almost) simultaneously attend to different media. Existing research indicates that split‐attention problems can be prevented or reduced by the presence of screen images in the manual. Research is yet unclear about the optimal design of these pictures. This study examines three design styles. Forty‐eight novice users received one of the three manual based on these styles. The manuals were an introduction to Windows 95. The users of the most successful manual needed 25% less training time and had a 60% better retention. The most important characteristics of the design style of this manual were its use of full screen images (instead of partial ones) and a two‐column lay‐out in which the instructions and screen images were presented side‐by‐side in a left‐to‐right reading order. The discussion focuses on the tension that exists between theory and practice. Special attention is given to the contributions of a taxonomy of screen images and cognitive load theory.     

Training Novice Users in Developing Strategies for Responding to Errors When Browsing the Web

Novice users frequently make errors when learning a new computer task and spend a large portion of their time trying to recover from errors. Three methods for helping novice users respond to errors have been presented in the literature: error management training, exploratory training, and conceptual models. In error management training, errors are presented as opportunities for learning, and users are instructed in strategies for coping with errors. In exploration, users are given an overview of their environment and are taught how to navigate through their task environment. Conceptual models are graphical or mathematical representations of a system that correspond closely to the real-world system. This experiment tested the effectiveness of these different approaches on training novice users to use the Internet. In this experiment, users received 3 hr of training on the World Wide Web and then were asked to perform a set of information retrieval tasks. Performance was measured in two ways: task performance and performance time. Participants who received exploratory training had significantly higher task performance. Participants who received exploration and conceptual models, both individually and together, were able to complete the tasks in less time. Error management had no significant effect on the performance of participants. In the task application of Web browsing, exploration seems to be the most appropriate training method for novice users.     

Analysis and Classification of Human Driving Behaviour in an Urban Environment*

Intelligent vehicle systems have introduced the need for designers to consider user preferences so as to make several kinds of driving features as driver friendly as possible. This requirement raises the problem of how to suitably analyse human performance so they can be implemented in automatic driving tasks. The framework of the present work is an adaptive cruise control with stop and go features for use in an urban setting. In such a context, one of the main requirements is to be able to tune the control strategy to the driver’s style. In order to do this, a number of different drivers were studied through the statistical analysis of their behaviour while driving. The aim of this analysis is to decide whether it is possible to determine a driver’s behaviour, what signals are suitable for this task and which parameters can be used to describe a driver’s style. An assignment procedure is then introduced in order to classify a driver’s behaviour within the stop and go task being considered. Finally, the findings were analysed subjectively and compared with a statistically objective one.     

Web designers and web users: Influence of the ergonomic quality of the web site on the information search

Despite rapid growth in the number of web sites, there is still a significant number of ergonomic problems which hinder web users. Many studies focus on analysing cognitive processes and difficulties experienced by web users, but very few are interested in web designers’ difficulties or in comparing their respective activities. Towards this end, the two experimental studies presented in this article compare the strategies developed both by professional web designers and (novice vs. experienced) web users while searching for information on web sites of varying ergonomic quality. More precisely, we investigated whether web designers can effectively use their own strategies as web users when designing web sites. We presented a comparison of novice web users, experienced web users and professional web designers searching behavior and cognitive load when using ergonomic and non-ergonomic web sites. In addition, we asked web designers to predict the strategy used by novice web users. Based on the results obtained in the two experiments, we conclude that web designers are not able to predict strategies of novice users and do not behave like novice users. Consequently, ways for supporting web designers in developing a user-centered activity are necessary, and certain ways are suggested at the end of this article.     

Experience with user-centred requirements engineering

This paper describes the application of human–computer interaction (HCI) principles and methods to requirements engineering in a case study development of a visualisation tool, ADVISES, to support epidemiological research. The development approach consisted of scenario-based design and analysis of the users’ tasks and mental model of the domain. Prototyping and storyboarding techniques were used to explore design options with users as well as specifying functionality for two versions of the software to meet the needs of novice and expert users. Application of HCI functional allocation heuristics to guide system requirements decisions is explained. An evaluation of the prototype was carried out to assess the extent to which the expert model would support public health professionals in their analysis activities. The results of the design exploration requirements analysis study are reported. The implications of scenario-based design exploration, functional allocation and software architecture are discussed.     

Are Two Better Than One? A Comparison Between Single- and Dual-Monitor Work Stations in Productivity and User’s Windows Management Style

Multiple monitors are commonly used in the workplace nowadays. This study compares user productivity and windows management style (WMS) on single- and dual-monitor work stations for engineering tasks of three complexity levels. Four productivity measures including task time, cursor movement, the number of window switches, and the number of mouse clicks were compared. The results showed that dual-monitor setting resulted in significantly less window switches and mouse clicks. Most users preferred dual-monitor setting. To understand how users manage multiple windows in completing their tasks, a new WMS categorization method is proposed, toggler and resizer, and user behavior was categorized into one of these two styles. More users adopted “toggler” style, but as the task complexity level increased, some “toggler” style users switched to “resizer” style.     

Investigating one-handed and two-handed inter-device interaction

Using a mobile device together with a large shared screen supports collaborative tasks and potentially prevents interference among users. In order to evaluate the usability of inter-device interaction, this paper compared two fundamental inter-device interaction styles, i.e., one-handed and two-handed interaction. The one-handed interaction style only uses one hand to select an object from a large display device while the two-handed interaction style needs the cooperation of two hands to realize a selection. A framework was developed to implement these two interaction styles. Based on the framework, a pretest-posttest, repeated-measures study was conducted to compare their differences. All participants went through eight tasks, which were differentiated by both the selection order (sequential or random order) and the density level (sparse or dense layout), using both interaction styles. During the study, both the completion time and the error rate in each task with each interaction style were recorded. In addition, the IBM Post-Study Usability Questionnaire (PSSUQ) was used to evaluate the subjective satisfaction on each interaction style. The overall PSSUQ score indicates that both interaction styles receive positive feedback with high user satisfaction. The study also revealed that the one-handed interaction took less time to complete tasks (i.e., more efficient) than the two-handed interaction, while the two-handed interaction style had a lower error rate than the one-handed interaction, and especially so in a dense layout.     

A comparison of visual ability and its importance awareness between novice and experienced drivers

The visual ability factors of peripheral perception, visual reaction and visual pursuit ability are important for safe driving. Thus, this study explored the influence of driving experience on these visual ability factors. Sixty-five drivers, including novice and experienced drivers, participated in this study. The visual ability levels of the three factors were measured by the Vienna Test System. In addition, driver's awareness of the three factors' importance for safe driving was measured by questionnaire items. Results showed that out of the three factors, drivers' peripheral perception ability was correlated significantly with their driving experience. Experienced drivers had higher peripheral perception ability than that of novice drivers. In addition, compared with novice drivers, experienced drivers believed that peripheral perception was more important whereas visual reaction was less important. It is suggested that higher attention should be paid to peripheral perception in driving training and novice drivers should increase their importance awareness for this factor.     

Learners’ navigation behavior identification based on trace analysis

Identifying learners’ behaviors and learning preferences or styles in a Web-based learning environment is crucial for organizing the tracking and specifying how and when assistance is needed. Moreover, it helps online course designers to adapt the learning material in a way that guarantees individualized learning, and helps learners to acquire meta-cognitive knowledge. The goal of this research is to identify learners’ behaviors and learning styles automatically during training sessions, based on trace analysis. In this paper, we focus on the identification of learners’ behaviors through our system: Indicators for the Deduction of Learning Styles. We shall first present our trace analysis approach. Then, we shall propose a ‘navigation type’ indicator to analyze learners’ behaviors and we shall define a method for calculating it. To this end, we shall build a decision tree based on semantic assumptions and tests. To validate our approach, and improve the proposed calculation method, we shall present and discuss the results of two experiments that we conducted.     

Effects of user experience,working posture and joint hardness on powered nutrunner torque reactions

Powered hand tools produce reaction forces that may be associated with upper extremity musculoskeletal disorders. The handle displacement, grip force and upper limb muscle activity (electromyography (EMG)) due to the effects of operator experience, working height and distance, type of tool and fastener joint hardness were measured in this study with 15 experienced and 15 novice nutrunner users. The results show that when pistol grip handles were used to work on a horizontal surface, experienced users allowed an average handle displacement of 7.9°, while novice users allowed 11.5°. Average EMG scaled by reference voluntary contraction (RVC) at forearm flexors, forearm extensors and biceps were greater for experienced users (318% RVC, 285% RVC, 143% RVC, respectively) than for novice users (246% RVC, 219% RVC, 113% RVC, respectively). Experienced users exerted more grip force than novice users when using right angle handles, but less force when using pistol grip handles. The results suggest that it is possible to minimize tool handle displacement by adapting the workplace layout to permit different working postures for each user group.     

Learning rate and subjective mental workload in five truck driving tasks

Both learning curve models and subjective mental workload are useful tools for determining the length of training for new workers and predicting future task performance. An experiment was designed to collect the task completion times and subjective mental workload of five driving tasks including (a) reverse into garage, (b) 3-point turn, (c) parallel parking, (d) S-curve and (e) up-down-hill. The results indicated that task completion times of truck driving can be predicted with a learning curve. Practice significantly reduced the mental workload rating. However, the novice trainees tended to have a more significant reduction because, compared to experienced trainees, they tended to give greater or lower workload scores than the experienced trainees before and after practice, respectively. The current study may not be complete enough to provide guidelines for a training programme, but it is adequate to suggest that learning rate and workload measure can serve as indexes for factoring in the individual differences.

Practitioner summary: Learning curves can be used to determine the length of training for new workers and performance standards for a particular task. Learning rate and mental workload were found to be important measures for comparing individual differences in order to better design a training programme. However, mental workload must be evaluated by experienced participants.     

Driving comfort,enjoyment and acceptance of automated driving – effects of drivers’ age and driving style familiarity

Automated driving has the potential to improve the safety and efficiency of future traffic and to extend elderly peoples’ driving life, provided it is perceived as comfortable and joyful and is accepted by drivers. Driving comfort could be enhanced by familiar automated driving styles based on drivers’ manual driving styles. In a two-stage driving simulator study, effects of driving automation and driving style familiarity on driving comfort, enjoyment and system acceptance were examined. Twenty younger and 20 older drivers performed a manual and four automated drives of different driving style familiarity. Acceptance, comfort and enjoyment were assessed after driving with standardised questionnaires, discomfort during driving via handset control. Automation increased both age groups’ comfort, but decreased younger drivers’ enjoyment. Younger drivers showed higher comfort, enjoyment and acceptance with familiar automated driving styles, whereas older drivers preferred unfamiliar, automated driving styles tending to be faster than their age-affected manual driving styles.

Practitioner Summary: Automated driving needs to be comfortable and enjoyable to be accepted by drivers, which could be enhanced by driving style individualisation. This approach was evaluated in a two-stage driving simulator study for different age groups. Younger drivers preferred familiar driving styles, whereas older drivers preferred driving styles unaffected by age.     

User sensitive research in e-learning: exploring the role of individual user characteristics

The increasing need for active and accessible learning in the inclusive knowledge society drives the demand for e-learning that engages users much more effectively than ever before. In this context, it is crucial to conduct research that embraces innovation in user sensitive design, or else influential individual user differences may be overlooked. The objective of this paper is to explore the creation of successful e-learning systems that are able to increase users’ learning performance and enhance their personal learning experiences. The paper reports two converging and complimentary approaches, namely case studies and experimentation. First, case studies are used to explore the extent to which effective e-learning systems comply with eight specific factors. Of the eight, accessibility, individual differences and student modeling turn out to be the weakest points in current practice. Second, an empirical study investigates the influences of user individual user differences on users’ learning outcomes in an e-learning environment. The experiment found that individual differences in motivation to learn and expectations about e-learning significantly impacted users’ learning achievements. Third, based on these studies, improvements in research methodology are identified towards greater consideration of user sensitive research issues, thus enabling us to outline improved experimental procedures. Further experiment results should provide us with better insights into the arguments needed to carefully assess benefits of developing and involving a user model in an e-learning application. Consequently, evaluation and justification could now encompass both system performance as well as user performance.     

Effects of user experience, working posture and joint hardness on powered nutrunner torque reactions

Powered hand tools produce reaction forces that may be associated with upper extremity musculoskeletal disorders. The handle displacement, grip force and upper limb muscle activity (electromyography (EMG)) due to the effects of operator experience, working height and distance, type of tool and fastener joint hardness were measured in this study with 15 experienced and 15 novice nutrunner users. The results show that when pistol grip handles were used to work on a horizontal surface, experienced users allowed an average handle displacement of 7.9 degrees, while novice users allowed 11.5 degrees. Average EMG scaled by reference voluntary contraction (RVC) at forearm flexors, forearm extensors and biceps were greater for experienced users (318% RVC, 285% RVC, 143% RVC, respectively) than for novice users (246% RVC, 219% RVC, 113% RVC, respectively). Experienced users exerted more grip force than novice users when using right angle handles, but less force when using pistol grip handles. The results suggest that it is possible to minimize tool handle displacement by adapting the workplace layout to permit different working postures for each user group.     

An ontological modelling of user requirements for personalised information provision

The knowledge economy offers opportunity to a broad and diverse community of information systems users to efficiently gain information and know-how for improving qualifications and enhancing productivity in the work place. Such demand will continue and users will frequently require optimised and personalised information content. The advancement of information technology and the wide dissemination of information endorse individual users when constructing new knowledge from their experience in the real-world context. However, a design of personalised information provision is challenging because users’ requirements and information provision specifications are complex in their representation. The existing methods are not able to effectively support this analysis process. This paper presents a mechanism which can holistically facilitate customisation of information provision based on individual users’ goals, level of knowledge and cognitive styles preferences. An ontology model with embedded norms represents the domain knowledge of information provision in a specific context where users’ needs can be articulated and represented in a user profile. These formal requirements can then be transformed onto information provision specifications which are used to discover suitable information content from repositories and pedagogically organise the selected content to meet the users’ needs. The method is provided with adaptability which enables an appropriate response to changes in users’ requirements during the process of acquiring knowledge and skills.     

Learning programming via worked-examples: Relation of learning styles to cognitive load

This paper describes an experiment that compared learners with contrasting learning styles, Active vs. Reflective, using three different strategies for learning programming via worked-examples: Paired-method, Structure-emphasising, and Completion. The quality of the learners’ acquired cognitive schemata was assessed in terms of their post-test performance. The experiment investigated variations in learners’ cognitive load, taking both the learning strategies and the learners’ learning styles into account. Overall, the results of the experiment were inconsistent. In comparing the effects of the strategies during the learning phase, the study found significant differences in cognitive load. Unexpectedly, no differences were then detected either in cognitive load or in performance during the post-test (post-test). In comparing the effects of the learning styles during the learning phase and the transfer phase, medium effect sizes suggested that learning style may have had an effect on cognitive load. However, no significant difference was observed in performance during the post-test.     

Understanding persistence in the use of Online Fitness Communities: Comparing novice and experienced users

Mobile and wearable technologies facilitate physiological data collection for health and wellness purposes. Users typically access these data via Online Fitness Community (OFC) platforms (e.g., Fitbit, Strava, RunKeeper). These platforms present users with functionalities centered on self-monitoring, social networking and enjoyment. In order to fully benefit from these functionalities, users need to make a habit out of integrating OFC use into their everyday workout routines. However, research suggests that users often fail to use OFCs over a longer period of time. This study sheds light on the factors that explain persisted OFC use. To that end, the study compares novice and experienced users in terms of their OFC use motives and how these motives contribute to the habitual integration of OFCs into everyday workout routines. Based on the survey responses of 394 OFC users, a multi-sample structural equation model indicates that self-regulatory and social motives directly predict habitual OFC use, and that enjoyment and self-regulatory motives indirectly predict habitual OFC use, by driving the perceived usefulness of OFCs. Moderation analysis revealed that, for novice users, self-regulatory motives are the prime drivers of habitual OFC use, while social motives and enjoyment are more important for experienced users.