The role of non-formal education in increasing female participation in Computer Science (CS) is a hot topic. Short-term interventions, including programming skill outreach activities, have been reported to increase self-efficacy and willingness to pursue computing careers in young women. We explored the impact of a programming outreach activity on three types of measures for 30 female pupils: computing self-efficacy, social participation, and understanding of basic computing concepts. Preliminary results revealed a significant increase in participants' self-efficacy and sense of belonging in computing after the informal learning activity. Students were more focused on tasks when engaging socially with their peers and teachers. A decrease in misconception was observed in uni-structural knowledge but no significant difference was found in multi-structural computing knowledge acquisition. These data provide a baseline for study of the long term impact of outreach activities.

Adapting dashboard design to different contexts of use is an open question in visualisation research. Dashboard designers often seek to strike a balance between dashboard adaptability and ease-of-use, and in hospitals challenges arise from the vast diversity of key metrics, data models and users involved at different organizational levels. In this design study, we present QualDash, a dashboard generation engine that allows for the dynamic configuration and deployment of visualisation dashboards for healthcare quality improvement (QI). We present a rigorous task analysis based on interviews with healthcare professionals, a co-design workshop and a series of one-on-one meetings with front line analysts. From these activities we define a metric card metaphor as a unit of visual analysis in healthcare QI, using this concept as a building block for generating highly adaptable dashboards, and leading to the design of a Metric Specification Structure (MSS). Each MSS is a JSON structure which enables dashboard authors to concisely configure unit-specific variants of a metric card, while offloading common patterns that are shared across cards to be preset by the engine. We reflect on deploying and iterating the design of OualDash in cardiology wards and pediatric intensive care units of five NHS hospitals. Finally, we report evaluation results that demonstrate the adaptability, ease-of-use and usefulness of QualDash in a real-world scenario.

Public transportation movement data provide a wealth of information and insights into many aspects of urban life and human behavior. However, huge amounts of raw data, coupled with incomplete or inconsistent records, may turn into an obstacle for the effective use of the available information. The need for effective movement data analysis has resulted in a large number of visual analytics tools and specialized views. There are still many challenges in public transportation and other kinds of cyclic movement data analysis. In this paper we address some of those challenges by presenting an improvement of the standard map view. This improved view is specifically designed to simplify and make the visual analysis of complex movement data easier to perform, especially when integrated in a coordinated multiple views tool and articulated together with other techniques. We illustrate the effectiveness of the view on public transportation data from Bahía Blanca, Argentina.

Abstract Scientific data acquired through sensors which monitor natural phenomena, as well as simulation data that imitate time‐identified events, have fueled the need for interactive techniques to successfully analyze and understand trends and patterns across space and time. We present a novel interactive visualization technique that fuses ground truth measurements with simulation results in real‐time to support the continuous tracking and analysis of spatiotemporal patterns. We start by constructing a reference model which densely represents the expected temporal behavior, and then use GPU parallelism to advect measurements on the model and track their location at any given point in time. Our results show that users can interactively fill the spatio‐temporal gaps in real world observations, and generate animations that accurately describe physical phenomena.

We present a study to evaluate OpenDSA, an open source, online system combining textbook-quality content with algorithm visualizations and interactive exercises for data structures and algorithms courses. We hypothesize that answering many questions and exercises with immediate feedback allows students to know whether they are on track with their learning. In a quasi-experimental study, a control group received lecture and textbook for three weeks. The treatment section spent class time working through equivalent content and exercises in OpenDSA. A post-test compared the two. An opinion survey examined students' perception and opinions about the experience. Detailed interaction logs were used to analyze student use of the tutorials and exercises to understand how they used the system.