An Empirical Study Comparing Unobtrusive Physiological Sensors for Stress Detection in Computer Work.

Several unobtrusive sensors have been tested in studies to capture physiological reactions to stress in workplace settings. Lab studies tend to focus on assessing sensors during a specific computer task, while in situ studies tend to offer a generalized view of sensors' efficacy for workplace stress monitoring, without discriminating different tasks. Given the variation in workplace computer activities, this study investigates the efficacy of unobtrusive sensors for stress measurement across a variety of tasks. We present a comparison of five physiological measurements obtained in a lab experiment, where participants completed six different computer tasks, while we measured their stress levels using a chest-band (ECG, respiration), a wristband (PPG and EDA), and an emerging thermal imaging method (perinasal perspiration). We found that thermal imaging can detect increased stress for most participants across all tasks, while wrist and chest sensors were less generalizable across tasks and participants. We summarize the costs and benefits of each sensor stream, and show how some computer use scenarios present usability and reliability challenges for stress monitoring with certain physiological sensors. We provide recommendations for researchers and system builders for measuring stress with physiological sensors during workplace computer use

The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium inaugural meeting report.

The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium is a novel, interdisciplinary initiative comprised of experts across many fields, including genomics, data analysis, engineering, public health, and architecture. The ultimate goal of the MetaSUB Consortium is to improve city utilization and planning through the detection, measurement, and design of metagenomics within urban environments. Although continual measures occur for temperature, air pressure, weather, and human activity, including longitudinal, cross-kingdom ecosystem dynamics can alter and improve the design of cities. The MetaSUB Consortium is aiding these efforts by developing and testing metagenomic methods and standards, including optimized methods for sample collection, DNA/RNA isolation, taxa characterization, and data visualization. The data produced by the consortium can aid city planners, public health officials, and architectural designers. In addition, the study will continue to lead to the discovery of new species, global maps of antimicrobial resistance (AMR) markers, and novel biosynthetic gene clusters (BGCs). Finally, we note that engineered metagenomic ecosystems can help enable more responsive, safer, and quantified cities

Development of an evidence-based medicine mobile application for the use in medical education

BACKGROUND: Evidence-based medicine (EBM) is a methodology that is being incorporated into more medical school curricula. Boston University School of Medicine was one of early adopters of Evidence Based Medicine in the United States. A growing concern in the medical community was that the complexities of applying EBM might be lost when students enter into their clinical rotations, thus there is a need for development of a tool to help reinforce the EBM principles. METHODS: The research team in collaboration with the designers of the Finding Information Framework, a custom-made EBM finding information tool, worked to develop a mobile application to help reinforce the framework for medical students. The app was designed with both Apple and PC operating systems in mind. Key features that were identified from current literature to provide the most user-friendly mobile application. Thus, the research team specifically utilized iOS and Android platforms as both platforms have a centralized app store, possess the highest volume of medical apps available, and are most widely used in the United States by medical students. RESULTS: The Finding Information Framework was a custom-made tool developed to guide new users of EBM, and help them to apply the principles in practice. The mobile application served an added convenience by allowing easy access and fast utilization of the EBM tools. The app was designed on an Android platform first due to its open-source OS and ease in app development to new programmers. Initially, the user-friendly web-based tool, App Inventor (AI), powered by Massachusetts Institute of Technology was evaluated to program the pilot Android app. Using both the AI Component Designer and the Block Editor, several problems were encountered in AI, such as the simplicity of the program and the lack of freedom in design. This moved the project to create the app natively and with a collaborative effort with the BU's Global App Initiative club. Initially, a wireframe was built using Balsamiq. Subsequently, the Android app was built using Android SDK and the iOS app was built in XCode with Objective C; both platforms had design sections prepared in Sketch, Adobe Photoshop and Illustrator. The last and final step was to obtain Boston University branding privileges for the app. CONCLUSION: The research team identified necessary features based on research to build a user-friendly, professional mobile application of an information mastery framework that can be used off-line. The app is called FIF as it is the title of the information mastery tool designed by BUSM EBM-VIG. With a clear mobile interface, it will be beneficial to the learning and training of medical students in EBM

Self-Control in Cyberspace: Applying Dual Systems Theory to a Review of Digital Self-Control Tools

Many people struggle to control their use of digital devices. However, our understanding of the design mechanisms that support user self-control remains limited. In this paper, we make two contributions to HCI research in this space: first, we analyse 367 apps and browser extensions from the Google Play, Chrome Web, and Apple App stores to identify common core design features and intervention strategies afforded by current tools for digital self-control. Second, we adapt and apply an integrative dual systems model of self-regulation as a framework for organising and evaluating the design features found. Our analysis aims to help the design of better tools in two ways: (i) by identifying how, through a well-established model of self-regulation, current tools overlap and differ in how they support self-control; and (ii) by using the model to reveal underexplored cognitive mechanisms that could aid the design of new tools.Comment: 11.5 pages (excl. references), 6 figures, 1 tabl

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research