Interactive systems are increasingly used in a growing number of domains to encourage users to perform certain actions or take a certain position toward a given subject. This article offers a perspective on interactive persuasive systems that emphasizes theories and concepts that can guide their design and evaluation. The goal is not to champion a theoretical model over others or to compare the effectiveness of different persuasive strategies but rather to depict the current conceptual landscape in this field and highlight emerging concepts and positions that have recently appeared in it. The article includes a discussion of some representative, general, and domain-specific constructs that can be used to evaluate the effectiveness of interactive persuasive systems.

In the face of increased cyber risks, we present our iterative design process and the resulting principles of SpringRain, an information visualization (infoVis) display design concept for large screens in network control rooms (NOCs). It aims to raise team situation awareness by visualizing large-scale multidimensional computer network data sets as a live “rainfall.” We used aesthetic principles and theories of perception to prototype this ambient, yet data-dense, visualization. By applying multiple data dimensions to different properties of a line segment, such as length, motion, and color, the two-dimensional visualization offers analytical affordances (i.e., graphic qualities that make it clear how the display should be “read”) that can be processed pre-attentively (i.e., under 200 ms). This grants that time-sensitive anomalies in the network can be noticed, processed, and addressed in a timely manner. Our design approach was driven by theories rather than existing design works in the hope of encouraging more user-centered theories-driven infoVis designs that are better suited to user needs and requirements. Expert reviewers’ feedback from the VAST 2013 Challenge committee confirmed the novelty of the design and pointed to opportunities for improvements. We discuss three redesign attempts to address some of the identified limitations.

Gaining a better understanding of human–computer interaction in multiple-goal environments, such as driving, is critical as people increasingly use information technology to accomplish multiple tasks simultaneously. Extensive research shows that decision biases can be utilized as effective cues to guide user interaction in single-goal environments. This article is a first step toward understanding the effect of decision biases in multiple-goal environments. This study analyzed data from a field experiment during which a comparison was made between drivers’ decisions on parking lots in a single-goal environment and drivers’ decisions in a multiple-goal environment when being exposed to the default option bias. The article shows that the default option bias is effective in multiple-goal environments. The results have important implications for the design of human–computer interaction in multiple-goal environments.

Advancements in technology have spurred the development of new in-vehicle applications. Drivers are faced with different driving contexts due to an increase in the number of devices that provide a wealth of diverse information. However, such a scenario can cause drivers to become distracted. Therefore, research on how the presentation of visual information can affect drivers’ performance is important. In this study, an analysis of quantifiable measurements that affect drivers’ perception of visual complexity and visual search performance was conducted. A questionnaire was administered to assess subjective perception of visual complexity, and a user experiment using eye tracking was designed to explore participants’ visual search performance. The results of subjective visual complexity perception and visual search performance suggested that some objective measurement variables were significantly related only to perceived visual complexity, whereas others affected both subjective and behavioral measurements. Thus it is possible to predict which quantifiable measurement variables affect subjective perception of visual complexity and which affect visual search performance. Therefore, this study allows understanding and explaining of perception of visual complexity by quantifiable measurements and the different ways by which these measurements affect visual search performance.

This article reviewed both studies on general smart car technologies and human–computer interaction (HCI)/human–vehicle interaction studies that were published in journals and conferences so that the current status of research can be identified and future research directions can be suggested. Furthermore, previous studies on elderly drivers were reviewed, as these drivers could be the most vulnerable social group in terms of new technology acceptance. A total of 257 articles for HCI research and 45 articles for elderly drivers were selected and reviewed from 11,267 collected articles (2010–2014). According to the results, most articles were mainly related to safety and adaptive features (e.g., driver’s state recognition, vehicle surrounding monitoring, driver action-suggestion), and infotainment research in terms of HCI (e.g., information technology devices–vehicle interaction, vehicle–vehicle interaction) was relatively insufficient despite its high research demand. According to the results of the literature review and technological trends analysis based on previous technical road maps, from HCI/human factors engineering (HFE) perspectives, research related to “Assistance systems,” “Physiological & mental state recognition,” “Position sensor technology,” “Behavior recognition,” and “Infotainment” was suggested to HCI/HFE researchers for further research. In particular, HCI/HFE researchers need to focus on research on acceptable levels of automation, observing new driving behaviors, investigation of driver characteristics to develop personalized services, and new technology acceptance to develop and improve smart cars in the future.

The value of thinking aloud in usability tests depends on the content of the users’ verbalizations. We investigated moderated and unmoderated users’ verbalizations during relaxed thinking aloud (i.e., verbalization at Levels 1–3). Verbalizations of user experience were frequent and mostly relevant to the identification of usability issues. Explanations and redesign proposals were also mostly relevant, but infrequent. The relevance of verbalizations of user experience, explanations, and redesign proposals showed the value of relaxed thinking aloud but did not clarify the trade-off between rich verbalizations and test reactivity. Action descriptions and system observations—two verbalization categories consistent with both relaxed and classic thinking aloud—were frequent but mainly of low relevance. Across all verbalizations, the positive or negative verbalizations were more often relevant than those without valence. Finally, moderated and unmoderated users made largely similar verbalizations, the main difference being a higher percentage of high-relevance verbalizations by unmoderated users.

This article describes the psychometric properties of the Emotional Metric Outcomes (EMO) questionnaire and the System Usability Scale (SUS) using data collected as part of a large-sample unmoderated usability study (n = 471). The EMO is a concise multifactor standardized questionnaire that provides an assessment of transaction-driven personal and relationship emotional outcomes, both positive and negative. The SUS is a well-known standardized usability questionnaire designed to assess perceived usability. In previous research, psychometric evaluation using data from a series of online surveys showed that the EMO and its component scales had high reliability and concurrent validity with loyalty and overall experience metrics but did not find the expected four-factor structure. Previous structural analyses of the SUS have had mixed results. Analysis of the EMO data from the usability study revealed the expected four-factor structure. The factor structure of the SUS appeared to be driven by item tone. The estimated reliability of the SUS (.90) was consistent with previous estimates. The EMO and its subscales were also quite reliable, with the estimates of reliability for the various EMO scales ranging from .86 to .96. Regression analysis using SUS, EMO, and Effort as predictors revealed different key drivers for the outcome metrics of Satisfaction and Likelihood-to-Recommend. The key recommendations are to include the EMO as part of the battery of poststudy standardized questionnaires, along with the SUS (or similar questionnaire), but to be cautious in reporting SUS subscales such as Usable and Learnable.

In this article the results of a usability study of CONTACT, an application that supports negotiation strategy training via video modeling for enhancing the conflict resolution of adolescents with autism spectrum disorder (ASD), are presented. This application was modified from the NoProblem! prototype based on feedback from two focus groups of typically developing adolescents and therapists and teachers of adolescents with ASD. It has been designed to address social competencies through video modeling and complies with the principles of constructivist learning theory. Twenty-one adolescents with ASD, 12 to 18 years of age, and 27 age- and gender-matched typically developing adolescents participated in this study. The outcome measure used was the Intrinsic Motivation Inventory. Both adolescents with ASD and typically developing adolescents perceived the application to be interesting and enjoyable; they claimed that it did not generate feelings of pressure or tension and that they had independent choices. The results also showed that adolescents with ASD felt significantly more competent than typically developing adolescents when using this application. The findings of this study emphasize the important role that the usability process has when designing and developing new technologies for educational purposes for adolescents with and without ASD.