Richard Catrambone

An evaluation of space-filling information visualizations for depicting hierarchical structures

A variety of information visualization tools have been developed recently, but relatively little effort has been made to evaluate the effectiveness and utility of the tools. This article describes results from two empirical studies of two visualization tools for depicting hierarchies, in particular, computer file and directory structures. The two tools examined implement space-filling methodologies, one rectangular, the Treemap method, and one circular, the Sunburst method. Participants performed typical file/directory search and analysis tasks using the two tools. In general, performance trends favored the Sunburst tool with respect to correct task performance, particularly on initial use. Performance with Treemap tended to improve over time and use, suggesting a greater learning cost that was partially recouped over time. Each tool afforded somewhat different search strategies, which also appeared to influence performance. Finally, participants strongly preferred the Sunburst tool, citing better ability to convey structure and hierarchy.

Health Mashups: Presenting Statistical Patterns between Wellbeing Data and Context in Natural Language to Promote Behavior Change

People now have access to many sources of data about their health and wellbeing. Yet, most people cannot wade through all of this data to answer basic questions about their long-term wellbeing: Do I gain weight when I have busy days? Do I walk more when I work in the city? Do I sleep better on nights after I work out? We built the Health Mashups system to identify connections that are significant over time between weight, sleep, step count, calendar data, location, weather, pain, food intake, and mood. These significant observations are displayed in a mobile application using natural language, for example, “You are happier on days when you sleep more.” We performed a pilot study, made improvements to the system, and then conducted a 90-day trial with 60 diverse participants, learning that interactions between wellbeing and context are highly individual and that our system supported an increased self-understanding that lead to focused behavior changes.

Evaluating animations as student aids in learning computer algorithms

Abstract We conducted two experiments designed to examine whether animations of algorithms would help students learn the algorithms more effectively. Across the two studies we used two different algorithms — depth-first search and binomial heaps — and used two different subject populations — students with little or no computer science background and students who were computer science majors — and examined whether animations helped students acquire procedural and conceptual knowledge about the algorithms. The results suggest that one way animations may aid learning of procedural knowledge is by encouraging learners to predict the algorithms behavior. However, such a learning improvement was also found when learners made predictions of an algorithms behavior from static diagrams. This suggests that prediction, rather than animation per se, may have been the key factor in aiding learning in the present studies. These initial experiments served to highlight a number of methodological issues that need to be systematically addressed in future experiments in order to fully test the relationship between animation and prediction as well as to examine other possible benefits of animations on learning.

Establishing tradeoffs that leverage attention for utility: empirically evaluating information display in notification systems

Designing and evaluating notification systems represents an emerging challenge in the study of human-computer interaction. Users rely on notification systems to present potentially interruptive information in an efficient and effective manner to enable appropriate reaction and comprehension. Little is known about the effects of these systems on ongoing computer tasks. As the research community strives to understand information design suitable for opposing usage goals, few existing efforts lend themselves to extensibility.However, three often conflicting design objectives are interruption to primary tasks, reaction to specific notifications, and comprehension of information over time. Based on these competing parameters, we propose a unifying research theme for the field that defines success in notification systems design as achieving the desirable balance between attention and utility. This paradigm distinguishes notification systems research from traditional HCI by centering on the limitations of the human attention system.In a series of experiments that demonstrate this research approach and investigate use of animated text in secondary displays, we describe two empirical investigations focused on the three critical parameters during a browsing task. The first experiment compares tickering, blasting, and fading text, finding that tickering text is best for supporting deeper comprehension, fading best facilitates reaction, and, compared to the control condition, none of the animated displays are interruptive to the browsing task. The second experiment investigates fading and tickering animation in greater detail with similar tasks--at two different speeds and sizes. Here, we found smaller displays allowed better reaction but were more interruptive, while slower displays provides increased comprehension. Overall, the slow fade appears to be the best secondary display animation type tested. Focusing research and user studies within this field on critical parameters such as interruption, reaction, and comprehension will increase cohesion among design and evaluation efforts for notification systems.

A psychological perspective on augmented reality in the mathematics classroom

Physical objects and virtual information are used as teaching aids in classrooms everywhere, and until recently, merging these two worlds has been difficult at best. Augmented reality offers the combination of physical and virtual, drawing on the strengths of each. We consider this technology in the realm of the mathematics classroom, and offer theoretical underpinnings for understanding the benefits and limitations of AR learning experiences. The paper presents a framework for understanding AR learning from three perspectives: physical, cognitive, and contextual. On the physical dimension, we argue that physical manipulation affords natural interactions, thus encouraging the creation of embodied representations for educational concepts. On the cognitive dimension, we discuss how spatiotemporal alignment of information through AR experiences can aid students symbolic understanding by scaffolding the progression of learning, resulting in improved understanding of abstract concepts. Finally, on the contextual dimension, we argue that AR creates possibilities for collaborative learning around virtual content and in non-traditional environments, ultimately facilitating personally meaningful experiences. In the process of discussing these dimensions, we discuss examples from existing AR applications and provide guidelines for future AR learning experiences, while considering the pragmatic and technological concerns facing the widespread implementation of augmented reality inside and outside the classroom.

Improving examples to improve transfer to novel problems

People often memorize a set of steps for solving problems when they study worked-out examples in domains such as math and physics without learning what domain-relevant subgoals or subtasks these steps achieve. As a result, they have trouble solving novel problems that contain the same structural elements but require different, lower-level steps. In three experiments, subjects who studied example solutions that emphasized a needed subgoal were more likely to solve novel problems that required a new approach for achieving this subgoal than were subjects who did not learn this subgoal. This result suggests that research aimed at determining the factors that influence subgoal learning may be valuable in improving transfer from examples to novel problems.

Learning subgoals and methods for solving probability problems

We hypothesize that typical example problems used in quantitative domains such as algebra and probability can be represented in terms of subgoals and methods that these problems teach learners. The “quality” of these subgoals and methods can vary, depending on the features of the examples. In addition, the likelihood of these subgoals’ being recognized in novel problems and the likelihood of learners’ being able to modify an old method for a new problem may be functions of the training examples learners study. In Experiment 1, subjects who studied examples predicted to teach certain subgoals were often able to recognize those subgoals in nonisomorphic transfer problems. Subjects who studied examples demonstrating two methods rather than one exhibited no advantages in transfer. Experiment 2 demonstrated that if the conditions for applying a method are highlighted in examples, learners are more likely to appropriately adapt that method in a novel problem, perhaps because they recognize that the conditions do not fully match those required for any of the old methods. Overall, the results indicate that the subgoal/method representational scheme may be useful in predicting transfer performance.

Procedural instructions, principles, and examples: how to structure instructions for procedural tasks to enhance performance, learning, and transfer.

Objective: The goal of this article is to investigate how instructions can be constructed to enhance performance and learning of procedural tasks. Background: Important determinants of the effectiveness of instructions are type of instructions (procedural information, principles, and examples) and pedagogical goal (initial performance, learning, and transfer). Method: Procedural instructions describe how to complete tasks in a stepwise manner, principles describe rules governing the tasks, and examples demonstrate how instances of the task are carried out. The authors review the research literature associated with each type of instruction to identify factors determining effectiveness for different pedagogical goals. Results: The results suggest a trade-off between usability and learnability. Specific instructions help initial performance, whereas more general instructions, requiring problem solving, help learning and transfer. Learning from instructions takes cognitive effort, and research suggests that learners typically opt for low effort. However, it is possible to meet both goals of good initial performance and learning with methods such as fading and by combining different types of instructions. Conclusion: How instructions are constructed influences their effectiveness for the goals of good initial performance, learning, and transfer, and it is therefore important for researchers and practitioners alike to define the pedagogical goal of instructions. Application: If the goal is good initial performance, then instructions should highly resemble the task at hand (e.g., in the form of detailed procedural instructions and examples), but if the goal is good learning and transfer, then instructions should be more abstract, inducing learners to expend the necessary cognitive effort for learning.

Social facilitation effects of virtual humans.

Objective: To investigate whether virtual humans produce social facilitation effects. Background: When people do an easy task and another person is nearby, they tend to do that task better than when they are alone. Conversely, when people do a hard task and another person is nearby, they tend to do that task less well than when they are alone. This phenomenon is referred to in the social psychology literature as social facilitation. The present study investigated whether virtual humans can evoke a social facilitation response. Method: Participants were given different tasks to do that varied in difficulty. The tasks involved anagrams, mazes, and modular arithmetic. They did the tasks alone, in the company of another person, or in the company of a virtual human on a computer screen. Results: For easy tasks, performance in the virtual human condition was better than in the alone condition, and for difficult tasks, performance in the virtual human condition was worse than in the alone condition. Conclusion: As with a human, virtual humans can produce social facilitation. Application: The results suggest that designers of virtual humans should be mindful about the social nature of virtual humans; a design decision as to when and how to present a virtual human should be a deliberate and informed decision. An ever-present virtual human might make learning and performance difficult for challenging tasks.

Is the Self-Concept a Habitual Referent in Judgments of Similarity?

People typically provide higher similarity ratings in response to the question “How similar is the typical preppie to you?” than to the question “How similar are you to the typical preppie?” Observed asymmetries in comparisons of the self and person prototypes have been offered as evidence that the self-concept acts as a habitual reference point in social judgment However, such a task does not test the habitual placement of a concept in the referent position of a comparison In this study, participants judged the similarity between the self and person prototypes in response to linguistic (forced directional) queries or to spatial (nonforced) queries in which the self was positioned above or below the person concept Participants also rated pairs of familiar and unfamiliar countries in a similar manner, to replicate and extend the work of Tversky (1977) Expected asymmetries were observed in forced comparisons The self and the familiar country were seen as more similar to other people and less familiar countries, respectively, when the former concepts served as the referent of a comparison than when they served as the subject Asymmetries were not observed in the nonforced conditions, and mean similarity in these conditions was of the same magnitude as in the forced condition in which the more familiar stimulus was the referent of the comparison This result provides the first direct evidence that the self serves as a habitual referent in similarity judgments