This study proposes an adaptive heuristic evaluation method that tailors heuristics to evaluators and applies it to the usability evaluation of augmented reality (AR) applications to examine its effectiveness. The performance of the evaluation methods was assessed based on the usability problems discovered and their severity, and the differences were analyzed using the McNemar test. Results showed that the adaptive method considering evaluators’ heuristic satisfaction effectively identified screen design problems and problems related to the relationship between virtual objects and real-world objects in high-interaction AR interfaces. However, it was less effective in detecting problems related to virtual objects. The adaptive method based on the evaluators’ AR experience levels showed lower performance than the adaptive method considering heuristic satisfaction. This study demonstrates that the adaptive method reflecting evaluators’ heuristic satisfaction outperforms traditional method in specific aspects.

The advancement of artificial intelligence technology has enabled chatbots to mimic human conversations to the point of being nearly indistinguishable from humans. This study investigates the impact of chatbot proactivity on user experience, considering task types and user characteristics. Experiments were conducted using proactive and non-proactive chatbots for business-related and non-business-related tasks, evaluating user characteristics (age, gender, AI experience level, education level, personality traits) and user experience (perceived usefulness, perceived ease of use, perceived satisfaction, trust). The results showed that proactive chatbots were positively evaluated in terms of perceived usefulness, perceived satisfaction, and trust, but no significant difference was found in perceived ease of use compared to non-proactive chatbots. Additionally, task types and user personality traits (extraversion, agreeableness) significantly influenced user experience. This study highlights the critical role of chatbot proactivity in providing satisfying interaction experiences and emphasizes the importance of designing chatbots considering task and user characteristics.

Heuristic evaluation is a famous usability inspection method often used in the assessment of Augmented Reality (AR) systems. Usability heuristics can be characterized as general or specific to a domain. During comparative studies between a new and a traditional set of heuristics, the focus is often around performance metrics (number of problems, time, errors), and little attention is given to the experience itself (i.e., evaluator’s overall satisfaction toward utilization of the set of heuristics). In addition, limited research has been done on the application of heuristics to evaluate interfaces with different levels of interaction, along with how a longer set of low-level heuristics compares against a traditionally-sized set of high-level heuristics. In this study, recruited participants (mostly university students) performed a heuristic evaluation using either a set of 110 specific heuristics (SH) or a set of 23 general heuristics (GH) to evaluate two versions of an AR application, designed with a low and a high level of interactivity. Big Five personality traits, prior experience with AR or Virtual Reality systems, and various usability data (e.g., subjective ratings related to the usability of heuristics and AR application, number of unique problems, and severity ratings) were collected through questionnaires and utilized during statistical analysis. Results show that even though the employment of the set of GH produced higher overall satisfaction of evaluators, the set of SH resulted in a significantly larger number of unique usability problems. Furthermore, the more interactive version of the AR application was perceived by evaluators as the harder version to inspect, regardless of the set of heuristics utilized. Neuroticism and agreeableness traits were found with a significant impact on subjective usability ratings.

The implementation of haptic interfaces in vehicles has important safety and flexibility implications for lessening visual and auditory overload during driving. The present study aims to design and evaluate haptic interfaces with vehicle seats. Three experiments were conducted by testing a haptic seat in a simulator with a total of 20 participants. The first experiment measured reaction time, subjective satisfaction, and subject workloads of the haptic, visual, and auditory displays for the four signals primarily used by vehicle navigation systems. The second experiment measured reaction time, subjective satisfaction, and subjective workloads of the haptic, auditory, and multimodal (haptic + auditory) displays for the ringing signal used by in-vehicle Bluetooth hands-free systems. The third experiment measured drivers' subjective awareness, urgency, usefulness, and disturbance levels at various vibration intensities and positions for a haptic warning signal used by a driver drowsiness warning system. The results indicated that haptic seat interfaces performed better than visual and auditory interfaces, but the unfamiliarity of the haptic interface caused a lower subjective satisfaction for some criteria. Generally, participants showed high subjective satisfaction levels and low subjective workloads toward haptic seat interfaces. This study provided guidance for implementing haptic seat interfaces and identified the possible benefits of their use. It is expected that haptic seats implemented in vehicles will improve safety and the interaction between driver and vehicle.

The overall discovery rates, which are the ratios of sum of unique usability problems detected by all experiment participants against the number of usability problems existed in the evaluated systems, were investigated to find significant factors of usability evaluation through a meta-analytic approach with the n-corrected effect sizes newly defined in this study. Since many studies of usability evaluation have been conducted under specific contexts showing some mixed findings, usability practitioners need holistic and more generalized conclusions. Due to the limited applicability of the traditional meta-analysis to usability evaluation studies, a new meta-analytic approach was established and applied to 38 experiments that reported overall discovery rates of usability problems as a criterion measure. Through the meta-analytic approach with the n-corrected effect sizes, we successfully combined 38 experiments and found evaluator's expertise, report type, and interaction between usability evaluation method and time constraint as significant factors. We suggest that in order to increase overall discovery rates of usability problems, (a) free-style written reports are better than structured written reports; (b) when heuristic evaluation or cognitive walkthrough is used, the usability evaluation experiments should be conducted without time constraint, but when think-aloud is used, time constraint is not an important experimental condition; (c) usability practitioners do not need to be concerned about unit of evaluation, fidelity of evaluated systems, and task type; and (d) HCI experts are better than novice users or evaluators. Our conclusions can guide usability practitioners when determining evaluation contexts, and the meta-analytic approach of this study provides an alternative way to combine the empirical results of usability evaluation besides the traditional meta-analysis.

An ontology-based multi-layered robot knowledge framework (OMRKF) is proposed to implement robot intelligence to be useful in a robot environment. OMRKF consists of four classes of knowledge (KClass), axioms and two types of rules. Four KClasses including perception, model, activity and context class are organized in a hierarchy of three knowledge levels (KLevel) and three ontology layers (OLayer). The axioms specify the semantics of concepts and relational constraints between ontological elements in each OLayer. One type of rule is designed for relationships between concepts in the same KClasses but in different KLevels. These rules will be used in a way of unidirectional reasoning. And, the other types of rules are also designed for association between concepts in different KLevels and different KClasses to be used in a way of bi-directional reasoning. These features will let OMRKF enable a robot to integrate robot knowledge from levels of sensor data and primitive behaviors to levels of symbolic data and contextual information regardless of class of knowledge. To show the validities of our proposed OMRKF, several experimental results will be illustrated, where some queries can be possibly answered by using uni-directional rules as well as bi-directional rules even with partial and uncertain information.

The cell phone is an information appliance that has been widely used. It provides instant access to information and makes people more ‘connected’. The objective of our study is to investigate the relationship among the design features of the cell phone and identify the most important design features and design factors. In our survey study, we asked 1,006 college students using a 7-point Likert scale structured questionnaire to evaluate their preference of the design features and overall satisfaction of their current cell phone. Nine design factors were derived. Ten cell phone design features and five design factors that significantly impact a user's satisfaction were identified. The most important design features are: the physical appearance, size and menu organisation, which together account for 42% of the total variance of a user's overall satisfaction.

International e-commerce has been developed as an efficient means of global transaction, and it may be further improved, especially in B2C, if adapted to the conditions of local markets, such as economy, infrastructure and culture. To obtain the insight in the internationalisation of e-commerce, we investigated online shopping preferences in three nations – the US (well developed in e-commerce), Korea (fast growing with good infrastructure) and Turkey (developing with good potentials). A survey of 205 Korean university students was conducted, and its results were compared with the results of Turkish and US surveys in Lightner et al. (). We found significant cross-national differences in online shopping preferences, especially in information accuracy, security and product-price comparison, and discussed those differences in terms of economic, infrastructural and cultural factors. Several practical guidelines were provided for website design in the Korean online market.