Our goal for the present research was to improve upon the subgoal learning framework and further enhance problem solving performance for novice programmers learning to use a block-based programming language. In particular, we are expanding upon recent work done by Margulieux and Morrison that prompts learners to self-explain the subgoals, or functional pieces, of a problem solving process to create their own instructional explanations of the process. We added to this work by exploring whether learners' self-explained instructions could be used to effectively scaffold initial problem solving attempts (i.e., practice problems) to further improve performance. In this experiment, learners self-explained subgoals using the most successful conditions from Margulieux and Catrambone's [1] prior work and then were given practice problems that were either unscaffolded (control condition), scaffolded with their own subgoal explanations, or scaffolded with explanations constructed by an instructional designer and computer scientist. Learners who were scaffolded with their own explanations performed better on later problem solving (i.e., an assessment test) than those scaffolded with the experts' explanations or those with no scaffolding. The results show that scaffolding initial problem solving with learners' explanations of the problem solving process can lead to better problem solving performance than scaffolding from experts if the learners construct explanations with adequate support.

Computer-based learning environments can provide valuable resources for learning at scale, but students in these environments might learn without an instructor. Subgoal labels have been used in worked examples in STEM domains to help a learner understand the purpose of a set of steps, and this feature has increased problem solving performance [1]. Subgoal labels, however, have not been tested in instructional text. The present study explored this intervention. The results of the present study show that learners who received subgoal labels in both the text and example outperformed those in other conditions. When subgoal labeled text is paired with an unlabeled example, however, performance does not improve. These findings indicate that subgoal labeled instructional text when paired with subgoal labeled examples can improve performance in a computer-based learning environment.

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.

Technology-based interventions for promoting health behavior-change frequently leverage multiplayer game mechanics such as group-based competitions. However, health interventions successful for groups writ large may not always translate to successful behavior change at the individual level. In this paper, we explore the tension between group and individual success, based on an empirical study on a long-term real-world deployment of a pervasive health game for youth. We report five distinctive player types along the dimensions of motivation, behavior, and influence on others. Based on the findings, we provide design suggestions to help game designers integrate group-based mechanisms that maximize intervention effectiveness.

Technology-based health behavior change interventions involving passive on-body sensing and feedback interfaces show promise for increasing participation in physical activity. However, the majority of prior studies are small-scale interventions that heavily rely on research teams for programmatic support. In larger-scale deployments, participants may have to take over setup and maintenance tasks. In this paper, we examine the "hidden work" involved with the large-scale deployment of a behavior change application in American schools. We offer insight into the coordination required to maintain such deployments, and identify unique challenges that arise when schoolchildren are the target of a behavior change intervention. Our findings highlight the behind-the-scenes coordination and management work required of adult facilitators in order to support pervasive health interventions for children in school environments. We offer advice to researchers and project managers attempting integration of technology-based health behavior change applications for children.

Active video games (AVG) have become widespread as more physical interfaces are introduced in video games. Lab based studies have indicated that AVGs can increase the amount and intensity of physical activity compared to non-active games and TV, however, the long-term effectiveness of AVGs has yet been established. In fact, most of the existing studies show a reduction of interest and participation over time. This paper presents our findings from a long-term, multi-site deployment of a pervasive health game, the American Horsepower Challenge (AHPC). Similar to previous studies, our findings also show reduced effectiveness of the game, but on a much larger scale. Moreover, we analyze reasons for this and report what kind of game related online and offline activities happened during the deployment. We argue that a shift of evaluation metrics and design goals is required to make real-world sustainable behavior changes. Based on empirical data, we propose three goals for AVGs---sustainability, adaptability and sociability. Behavior-changing games can learn how to achieve these goals from existing game genres, such as alternate reality games, location-based games, family games, and multiplayer online games etc.

Mental models are mental representations of how an action changes a problem state. Creating a mental model early in the learning process is a strong predictor of success in computer science classes. One major problem in computer science education, however, is that novices have difficulty creating mental models perhaps because of the cognitive overload caused by traditional teaching methods. The present study employed subgoal-labeled instructional materials to promote the creation of mental models when teaching novices to program in Android App Inventor. Utilizing this and other well-established educational tools, such as scaffolding, to reduce cognitive load in computer science education improved the performance of participants on novel tasks when learning to develop mobile applications.

With rising concerns about obesity and sedentary lifestyles in youth, there has been an increasing interest in understanding how pervasive and ubiquitous computing technologies can catalyze positive health behaviors in children and teens. School-based interventions seem like a natural choice, and ubiquitous computing technologies hold much promise for these interventions. Yet the literature contains little guidance for how to approach school-based ubicomp deployments. Grounded in our analysis of a large-scale US school-based intervention for promoting youth physical activity, we present an approach to the design and evaluation of school-based ubicomp that treats the school as a social institution. We show how the school regulates students' daily lives, drawing from work in the sociology of schools to create a framing for planning, executing and analyzing school-based ubicomp deployments. These insights will assist other researchers and designers engaging in deployments of ubiquitous computing systems in settings with established institutional structures.

This paper discusses an experiment carried out in an AR test bed called “the pit”. Inspired by the well-known VR acrophobia study of Meehan et al. [18], the experimental goals were to explore whether VR presence instruments were useful in AR (and to modify them where appropriate), to compare additional measures to these well-researched techniques, and to determine if findings from VR evaluations can be transferred to AR. An experimental protocol appropriate for AR was developed. The initial experimental findings concern varying immersion factors (frame rate) and their effect on feelings of presence, user performance and behavior. Unlike the VR study, which found differing frame rates to affect presence measures, there were few differences in the five frame rate modes in our study as measured by the qualitative and quantitative instruments, which included physiological responses, a custom presence questionnaire, task performance, and user behavior. The AR presence questionnaire indicated users experienced a high feeling of presence in all frame rate modes. Behavior, performance, and interview results indicated the participants felt anxiety in the pit environment. However, the physiological data did not reflect this anxiety due to factors of user experience and experiment design. Efforts to develop a useful AR test bed and to identify results from a large data set has produced a body of knowledge related to AR evaluation that can inform others seeking to create AR experiments.

We performed an empirical study exploring people's interactions with an embodied conversational agent (ECA) while performing two tasks. Conditions varied with respect to 1) whether participants were allowed to choose an agent and its characteristics and 2) the putative quality or appropriateness of the agent for the tasks. For both tasks, selection combined with the illusion of further customization significantly improved participants' overall subjective impressions of the ECAs while putative quality had little or no effect. Additionally, performance data revealed that the ECA's motivation and persuasion effects were significantly enhanced when participants chose agents to use. We found that user expectations about and perceptions of the interaction between themselves and an ECA depended very much on the individual's preconceived notions and preferences of various ECA characteristics and might deviate greatly from the models that ECA designers intend to portray.

It is speculated that the processing of different types of information (e.g., quantitative, ordinal, or nominal data) will be affected by what type of visual display is used to present that information (e.g.. line graphs, shapes with varying levels of gray saturation, or shapes of different colors). People are expected to be able to more efficiently and accurately process and answer questions about the visual displays if the type of display (i.e., the representing dimension) provides neither too much nor too little information and matches the type of information (i.e., the represented dimension) being processed. In the present study we found that in general task performance was best when the represented and representing dimensions match. An exception to this is discussed.

This article addresses how to present movement information to learners as part of a larger project on developing a nonconventional computational system that teaches ballet. The requirements of such a system are first described, and then discoveries regarding the first requirement, presenting movement to a user, are discussed. Background research regarding how people learn movement, hypotheses concerning presenting movement with computer animation versus videotape, and an experiment testing those hypotheses are presented. The experiment required individuals to perform movements after viewing them in one of the formats. Each participant viewed a movement sequence multiple times and then was evaluated on his or her performance of that movement by two expert judges. Animations resulted in higher performance ratings for individuals with some previous dance experience. Format did not affect performance for other learners. This result implies that domain knowledge interacts with presentation format in learning ballet. These results will influence the design and implementation of a computer-based dance tutor under development, and they point to several interesting research directions, including exploring the effects of multimodal sensory presentations and prior knowledge in learning movement.

A good deal of research in cognitive psychology has demonstrated that, although learners can solve problems that are just like the ones they have been trained on, they often have great difficulty solving new types of problems. People also have difficulty trying to understand instructions or training materials that try to teach a procedure at a level that is general enough to apply to many different kinds of cases. These two findings lead to a quandary for people designing instructions for procedural tasks such as operating computer software: Instructions should be written with a good deal of specificity so that new users can understand and use them right away, but at the same time the user will have great difficulty generalizing what they have learned to novel cases. Experiment 1 seems to echo this quandary. Computer novices, in this study, were able to follow specific instructions for using a word processor more easily than general instructions. However, they had great difficulty generalizing the specific instructions to novel tasks. Experiment 2 demonstrates that when specific instructions are rewritten to help users form a more general procedure, novices can easily do new tasks and still maintain their initial quality of performance. A production rule formalism is used to represent the knowledge users obtain from instructions and to explore the conditions under which these productions can be generalized. Experiment 2 suggests that this knowledge can be used to improve the generalizability of instructions.

A Training Wheels interface creates a reduced functionality system intended to prevent new users from suffering the consequences of certain types of common errors when they exercise system functions and procedures. This has been shown to be an effective training system design for learning basic text editing functions [4]. We extend this result by examining the extent to which training wheels learners can transfer their skills to interaction with the full-function system. The experiment reported here indicates that training wheels subjects were better able to perform advanced full-system editing functions than subjects who were trained on the full system itself.