This research investigated how the similarity of the rendering parameters of background and foreground objects affected egocentric depth perception in indoor virtual and augmented environments. We refer to the similarity of the rendering parameters as visual 'congruence'. Study participants manipulated the depth of a sphere to match the depth of a designated target peg. In the first experiment, the sphere and peg were both virtual, while in the second experiment, the sphere is virtual and the peg is real. In both experiments, depth perception accuracy was found to depend on the levels of realism and congruence between the sphere, pegs, and background. In Experiment 1, realistic backgrounds lead to overestimation of depth, but resulted in underestimation when the background was virtual, and when depth cues were applied to the sphere and target peg. In Experiment 2, background and target pegs were real but matched with the virtual sphere; in comparison to Experiment 1, realistically rendered targets prompted an underestimation and more accuracy with the manipulated object. These findings suggest that congruence can affect distance estimation and the underestimation effect in the AR environment resulted from increased graphical fidelity of the foreground target and background.

Computing proficiency is an increasingly vital component of the modern workforce, and computer science programs are faced with the challenges of engaging and retaining students to meet the growing need in that sector. However, administrators and instructors often find themselves either reinventing the wheel or relying too heavily on intuition, despite the availability of national curriculum standards. To address these issues, we present CS Materials, an open-source resource targeted at computing educators for designing and analyzing courses for coverage of recommended guidelines, and alignment between the various components within a course, between sections of the same course, or course sequences within a program. The system works by facilitating mapping educational materials to national curriculum standards. A side effect of the system is that it centralizes the design of the courses and the materials used therein. The curriculum guidelines act as a lingua franca that allows examination of and comparison between materials and courses. More relevant to instructors, the system enables a more precise search for materials that match particular topics and learning outcomes, and dissemination of high quality materials and course designs. This paper discusses the system, and analyzes the costs and benefits of its features and usage. While adding courses and materials requires some overhead, having a centralized repository of courses and materials with a shared structure and vocabulary serves students, instructors, and administrators, by promoting a data-driven approach to rigor and alignment with national standards.

Effective communication using visualization relies in part on the use of viable encoding strategies. For example, a viewer's ability to rapidly and accurately discern between two or more categorical variables in a chart or figure is contingent upon the distinctiveness of the encodings applied to each variable. Research in perception suggests that color is a more salient visual feature when compared to shape and although that finding is supported by visualization studies, characteristics of shape also yield meaningful differences in distinctiveness. We propose that open or closed shapes (that is, whether shapes are composed of line segments that are bounded across a region of space or not) represent a salient characteristic that influences perceptual processing. Three experiments were performed to test the reliability of the open/closed category; the first two from the perspective of attentional allocation, and the third experiment in the context of multi-class scatterplot displays. In the first, a flanker paradigm was used to test whether perceptual load and open/closed feature category would modulate the effect of the flanker on target processing. Results showed an influence of both variables. The second experiment used a Same/Different reaction time task to replicate and extend those findings. Results from both show that responses are faster and more accurate when closed rather than open shapes are processed as targets, and there is more processing interference when two competing shapes come from the same rather than different open or closed feature categories. The third experiment employed three commonly used visual analytic tasks - perception of average value, numerosity, and linear relationships with both single and dual displays of open and closed symbols. Our findings show that for numerosity and trend judgments, in particular, that different symbols from the same open or closed feature category cause more perceptual interference when they are presented together in a plot than symbols from different categories. Moreover, the extent of the interference appears to depend upon whether the participant is focused on processing open or closed symbols.

Although undergraduate enrollment in Computer Science has remained strong and seen substantial increases in the past decade, retention of majors remains a significant concern, particularly for students at the freshman and sophomore level that are tackling foundational courses on algorithms and data structures. In this work, we present BRIDGES, a software infrastructure designed to enable the creation of more engaging assignments in introductory data structures courses by providing students with a simplified API that allows them to populate their own data structure implementations with live, real-world, and interesting data sets, such as those from popular social networks (e.g., Twitter, Facebook). BRIDGES also provides the ability for students to create and explore {\em visualizations} of the execution of the data structures that they construct in their course assignments, which can promote better understanding of the data structure and its underlying algorithms; these visualizations can be easily shared via a weblink with peers, family, and instructional staff. In this paper, we present the BRIDGES system, its design, architecture and its use in our data structures course over two semesters.

Do human-human social interactions carry over to human-virtual human social interactions? How does this affect future interface designers? We replicated classical tests of social influence known as the social facilitation and inhibition effects. Social facilitation/inhibition theory states that when in the presence of others, people perform simple tasks better and complex tasks worse. Participants were randomly assigned to perform both simple and complex tasks alone and in the presence of either a real human, a projected virtual human, or a virtual human in a head-mounted display. Our results showed participants were inhibited by the presence of others, whether real or virtual. That is, participants performed worse on the complex task, both in terms of percent correct and reaction times, when in the presence of others than when alone. Social facilitation did not occur with the real or virtual human. We discuss these results and their implications for future interface designers.

This study examines the roles of gender and visual realism in the persuasiveness of speakers. Participants were presented with a persuasive passage delivered by a male or female person, virtual human, or virtual character. They were then assessed on attitude change and their ratings of the argument, message, and speaker. The results indicated that the virtual speakers were as effective at changing attitudes as real people. Male participants were more persuaded when the speaker was female than when the speaker was male, whereas female participants were more persuaded when the speaker was male than when the speaker was female. Cross gender interactions occurred across all conditions, suggesting that some of the gender stereotypes that occur with people may carry over to interaction with virtual characters. Ratings of the perceptions of the speaker were more favorable for virtual speakers than for human speakers. We discuss the application of these findings in the design of persuasive human computer interfaces.