CohExplore : Visually Supporting Students in Exploring Text Cohesion

A cohesive text allows readers to follow the described ideas and events. Exploring cohesion in text might aid students enhancing their academic writing. We introduce CohExplore, which promotes exploring and reflecting on cohesion of a given text by visualizing computed cohesion-related metrics on an overview and detailed level. Detected topics are color-coded, semantic similarity is shown via lines, while connectives and co-references in a paragraph are encoded using text decoration. Demonstrating the system, we share insights about a student-authored text

VisCoMET: Visually Analyzing Team Collaboration in Medical Emergency Trainings

Handling emergencies requires efficient and effective collaboration of medical professionals. To analyze their performance, in an application study, we have developed VisCoMET, a visual analytics approach displaying interactions of healthcare personnel in a triage training of a mass casualty incident. The application scenario stems from social interaction research, where the collaboration of teams is studied from different perspectives. We integrate recorded annotations from multiple sources, such as recorded videos of the sessions, transcribed communication, and eye-tracking information. For each session, an information-rich timeline visualizes events across these different channels, specifically highlighting interactions between the team members. We provide algorithmic support to identify frequent event patterns and to search for user-defined event sequences. Comparing different teams, an overview visualization aggregates each training session in a visual glyph as a node, connected to similar sessions through edges. An application example shows the usage of the approach in the comparative analysis of triage training sessions, where multiple teams encountered the same scene, and highlights discovered insights. The approach was evaluated through feedback from visualization and social interaction experts. The results show that the approach supports reflecting on teams' performance by exploratory analysis of collaboration behavior while particularly enabling the comparison of triage training sessions

Understanding Shoulder Surfer Behavior and Attack Patterns Using Virtual Reality

In this work, we explore attacker behavior during shoulder surfing. As such behavior is often opportunistic and difficult to observe in real world settings, we leverage the capabilities of virtual reality (VR). We recruited 24 participants and observed their behavior in two virtual waiting scenarios: at a bus stop and in an open office space. In both scenarios, participants shoulder surfed private screens displaying different types of content. From the results we derive an understanding of factors influencing shoulder surfing behavior, reveal common attack patterns, and sketch a behavioral shoulder surfing model. Our work suggests directions for future research on shoulder surfing and can serve as a basis for creating novel approaches to mitigate shoulder surfing

CohExplore : Visually Supporting Students in Exploring Text Cohesion

A cohesive text allows readers to follow the described ideas and events. Exploring cohesion in text might aid students enhancing their academic writing. We introduce CohExplore, which promotes exploring and reflecting on cohesion of a given text by visualizing computed cohesion-related metrics on an overview and detailed level. Detected topics are color-coded, semantic similarity is shown via lines, while connectives and co-references in a paragraph are encoded using text decoration. Demonstrating the system, we share insights about a student-authored text

VisCoMET: Visually Analyzing Team Collaboration in Medical Emergency Trainings

Handling emergencies requires efficient and effective collaboration of medical professionals. To analyze their performance, in an application study, we have developed VisCoMET, a visual analytics approach displaying interactions of healthcare personnel in a triage training of a mass casualty incident. The application scenario stems from social interaction research, where the collaboration of teams is studied from different perspectives. We integrate recorded annotations from multiple sources, such as recorded videos of the sessions, transcribed communication, and eye-tracking information. For each session, an information-rich timeline visualizes events across these different channels, specifically highlighting interactions between the team members. We provide algorithmic support to identify frequent event patterns and to search for user-defined event sequences. Comparing different teams, an overview visualization aggregates each training session in a visual glyph as a node, connected to similar sessions through edges. An application example shows the usage of the approach in the comparative analysis of triage training sessions, where multiple teams encountered the same scene, and highlights discovered insights. The approach was evaluated through feedback from visualization and social interaction experts. The results show that the approach supports reflecting on teams' performance by exploratory analysis of collaboration behavior while particularly enabling the comparison of triage training sessions

Understanding Shoulder Surfer Behavior Using Virtual Reality

We explore how attackers behave during shoulder surfing. Unfortunately, such behavior is challenging to study as it is often opportunistic and can occur wherever potential attackers can observe other people's private screens. Therefore, we investigate shoulder surfing using virtual reality (VR). We recruited 24 participants and observed their behavior in two virtual waiting scenarios: at a bus stop and in an open office space. In both scenarios, avatars interacted with private screens displaying different content, thus providing opportunities for shoulder surfing. From the results, we derive an understanding of factors influencing shoulder surfing behavior