Social Bots and Fake News as (not) seen from the Viewpoint of Digital Education Frameworks

In den letzten Jahren haben internationale Organisationen wie die EU und die UNESCO eine Reihe von Vorschlägen und Strategiepapieren zur Bildung und Ausbildung im Zusammenhang mit digitalen Medien entwickelt. Mit den dabei entstandenen Rahmenkonzepten der EU (Digital Competence, DigComp) sowie der UNESCO (Media and Information Literacy, MIL) werden im Kern zwei zusammenhängende Ziele verfolgt: (i) digitale Bildung bzw. digitale Kompetenzen, Fähigkeiten und zugehörige Einstellungen umfassend zu kartographieren sowie (ii) über die dabei konzipierten edukativ-politischen Rahmenkonzepte Projektförderungen, Bildungs- bzw. Ausbildungsinitiativen sowie Gesetzesvorlagen anzustossen. Tatsächlich sind DigComp und MIL bereits dabei, auf internationaler Ebene einen prägenden Einfluss zu nahezu allen Fragen der Bildung und Ausbildung im Bereich digitaler Medien auszuüben. Beide Initiativen haben innerhalb der genannten Organisationen Leuchtturmcharakter, werden bislang aber von der allgemeinen Öffentlichkeit und der medienpädagogischen Fachöffentlichkeit kaum wahrgenommen. Dessen ungeachtet verbindet sich mit DigComp und MIL jeweils ein impliziter Anspruch auf einen – im Bedarfsfall zu aktualisierenden – Gesamtentwurf zur Analyse und Gestaltung medienpädagogischer Bildung und Ausbildung. Dies gilt für Gesetzesvorlagen, Regulierungen, Forschungsaktivitäten. Sind diese Rahmenkonzepte anschlussfähig an medienpädagogische Debatten über disruptive Versuche, in via soziale Medien geführte öffentliche Debatten einzugreifen, die sich über social bots, fake news oder andere Formen der Einflussnahme manifestieren? Erschliessen sie dazu Reflexionsräume und Handlungsoptionen? Geleitet von diesen Fragen betrachtet der vorliegende Aufsatz, die Rahmenkonzepte der EU und UNESCO, DigComp and MIL. Dabei zeigt sich, dass beide Rahmenkonzepte von Schieflagen gekennzeichnet sind. DigComp und MIL überbetonen die instrumentelle, auf Verwertung am Arbeitsmarkt bezogene Sicht auf digitale Medien - allerdings ist diese Gewichtung bei DigComp stärker ausgeprägt als bei MIL. Obgleich emphatische Appelle zu einem kritischen und reflektierten Umgang mit digitalen Medien weder bei DigComp noch MIL fehlen, bleibt die Ausgestaltung in dieser Hinsicht blass und hat bislang kaum konkretisierende Folgeaktivitäten nach sich gezogen. Bei allen Gesamtentwurfsansprüchen verkennen sowohl MIL und noch stärker DigComp die Rolle sozialer Medien bei der Ermöglichung eines öffentlichen Diskurses sowie ihres Zusammenhanges mit medienpädagogischen Fragen.Over recent years, international organisations like the EU and UNESCO have set up a number of proposals, models and frameworks that seek (i) to map and to conceptualize digital literacy and related concepts, e. g. information, digital or media literacy, digital competence, digital skills and (ii) to formulate policies and recommendations based on the conceptualizations developed. The resulting frameworks, such as Digital Competence (DigComp) developed by the EU, or Media and Information Literacy (MIL) developed by UNESCO, have a strong formative power on a global scale. Affected are policies, laws, regulations, research activities, and academic disciplines like media pedagogy and mindsets. Do these frameworks consider the effects of disruptive attempts by digital media to intervene in public debates e. g. social bots, fake news and other manifestations of biased or false information online? Do they offer avenues for reflection and action to address them? Guided by these questions, this paper studies the flagship frameworks on digital education of the EU and UNESCO, DigComp and MIL. It finds biases in both frameworks. To different degrees, both tend to overemphasize the practical and instrumental use of digital literacy

Dynamic Visual Abstraction of Soccer Movement

Trajectory-based visualization of coordinated movement data within a bounded area, such as player and ball movement within a soccer pitch, can easily result in visual crossings, overplotting, and clutter. Trajectory abstraction can help to cope with these issues, but it is a challenging problem to select the right level of abstraction (LoA) for a given data set and analysis task. We present a novel dynamic approach that combines trajectory simplification and clustering techniques with the goal to support interpretation and understanding of movement patterns. Our technique provides smooth transitions between different abstraction types that can be computed dynamically and on-the-fly. This enables the analyst to effectively navigate and explore the space of possible abstractions in large trajectory data sets. Additionally, we provide a proof of concept for supporting the analyst in determining the LoA semi-automatically with a recommender system. Our approach is illustrated and evaluated by case studies, quantitative measures, and expert feedback. We further demonstrate that it allows analysts to solve a variety of analysis tasks in the domain of soccer

Bring it to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis

Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach

A framework to analyze argumentative knowledge construction in computer-supported collaborative learning

Computer-supported collaborative learning (CSCL) is often based on written argumentative discourse of learners, who discuss their perspectives on a problem with the goal to acquire knowledge. Lately, CSCL research focuses on the facilitation of specific processes of argumentative knowledge construction, e.g., with computer-supported collaboration scripts. In order to refine process-oriented instructional support, such as scripts, we need to measure the influence of scripts on specific processes of argumentative knowledge construction. In this article, we propose a multi-dimensional approach to analyze argumentative knowledge construction in CSCL from sampling and segmentation of the discourse corpora to the analysis of four process dimensions (participation, epistemic, argumentative, social mode)

SimpliFly: A Methodology for Simplification and Thematic Enhancement of Trajectories.

Movement data sets collected using today's advanced tracking devices consist of complex trajectories in terms of length, shape, and number of recorded positions. Multiple additional attributes characterizing the movement and its environment are often also included making the level of complexity even higher. Simplification of trajectories can improve the visibility of relevant information by reducing less relevant details while maintaining important movement patterns. We propose a systematic stepwise methodology for simplifying and thematically enhancing trajectories in order to support their visual analysis. The methodology is applied iteratively and is composed of: (a) a simplification step applied to reduce the morphological complexity of the trajectories, (b) a thematic enhancement step which aims at accentuating patterns of movement, and (c) the representation and interactive exploration of the results in order to make interpretations of the findings and further refinement to the simplification and enhancement process. We illustrate our methodology through an analysis example of two different types of tracks, aircraft and pedestrian movement

Human mesenchymal stromal cells inhibit platelet activation and aggregation involving CD73-converted adenosine

Background: Mesenchymal stromal cells (MSCs) are promising cell therapy candidates. Clinical application is considered safe. However, minor side effects have included thromboembolism and instant blood-mediated inflammatory reactions suggesting an effect of MSC infusion on hemostasis. Previous studies focusing on plasmatic coagulation as a secondary hemostasis step detected both procoagulatory and anticoagulatory activities of MSCs. We now focus on primary hemostasis and analyzed whether MSCs can promote or inhibit platelet activation. Methods: Effects of MSCs and MSC supernatant on platelet activation and function were studied using flow cytometry and further platelet function analyses. MSCs from bone marrow (BM), lipoaspirate (LA) and cord blood (CB) were compared to human umbilical vein endothelial cells or HeLa tumor cells as inhibitory or activating cells, respectively. Results: BM-MSCs and LA-MSCs inhibited activation and aggregation of stimulated platelets independent of the agonist used. This inhibitory effect was confirmed in diagnostic point-of-care platelet function analyses in platelet-rich plasma and whole blood. Using inhibitors of the CD39–CD73–adenosine axis, we showed that adenosine produced by CD73 ectonucleotidase activity was largely responsible for the LA-MSC and BM-MSC platelet inhibitory action. With CB-MSCs, batch-dependent responses were obvious, with some batches exerting inhibition and others lacking this effect. Conclusions: Studies focusing on plasmatic coagulation suggested both procoagulatory and anticoagulatory activities of MSCs. We now show that MSCs can, dependent on their tissue origin, inhibit platelet activation involving adenosine converted from adenosine monophosphate by CD73 ectonucleotidase activity. These data may have strong implications for safety and risk/benefit assessment regarding MSCs from different tissue sources and may help to explain the tissue protective mode of action of MSCs. The adenosinergic pathway emerges as a key mechanism by which MSCs exert hemostatic and immunomodulatory functions

State of the Art of Sports Data Visualization

In this report, we organize and reflect on recent advances and challenges in the field of sports data visualization. The exponentially-growing body of visualization research based on sports data is a prime indication of the importance and timeliness of this report. Sports data visualization research encompasses the breadth of visualization tasks and goals: exploring the design of new visualization techniques; adapting existing visualizations to a novel domain; and conducting design studies and evaluations in close collaboration with experts, including practitioners, enthusiasts, and journalists. Frequently this research has impact beyond sports in both academia and in industry because it is i) grounded in realistic, highly heterogeneous data, ii) applied to real-world problems, and iii) designed in close collaboration with domain experts. In this report, we analyze current research contributions through the lens of three categories of sports data: box score data (data containing statistical summaries of a sport event such as a game), tracking data (data about in-game actions and trajectories), and meta-data (data about the sport and its participants but not necessarily a given game). We conclude this report with a high-level discussion of sports visualization research informed by our analysis—identifying critical research gaps and valuable opportunities for the visualization community. More information is available at the STAR’s website: https://sportsdataviz.github.io/