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Educational Data Virtual Lab (EDVL) is an open-source platform for data exploration and analysis that combines the power of a coding environment, the convenience of an interactive visualization engine, and the infrastructure needed to handle the complete data lifecycle. Based on the building blocks of the FIWARE European platform and Apache Zeppelin, this tool allows domain experts to become acquainted with data science methods using the data available within their own organization, ensuring that the skills they acquire are relevant to their field and driven by their own professional goals. We used EDVL in a pilot study in which we carried out a focus group within a multinational company to gain insight into potential users' perceptions of EDVL, both from the educational and operational points of view. The results of our evaluation suggest that EDVL holds a great potential to train the workforce in data science skills and to enable collaboration among professionals with different levels of expertise.
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Visualização de Dados , Escolaridade , Projetos PilotoRESUMO
This article describes the motivation, design, and evaluation of the VisVisual toolkit to engage students in learning essential visualization concepts, algorithms, and techniques. The toolkit includes four independent components: 1) VolumeVisual, 2) FlowVisual, 3) GraphVisual, and 4) TreeVisual, covering scalar and vector data visualization in scientific visualization and graph and tree layouts in information visualization. Complementary to the toolkit design is resource development, aiming to help instructors integrate VisVisual into their curriculum.
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Visualização de Dados , Aprendizagem , Currículo , Humanos , Motivação , EstudantesRESUMO
With the widespread advent of visualization techniques to convey complex data, visualization literacy (VL) is growing in importance. Two noteworthy facets of literacy are user understanding and the discovery of visual patterns with the help of graphical representations. The research literature on VL provides useful guidance and opportunities for further studies in this field. This introduction summarizes and presents research on VL that examines how well users understand basic and advanced data representations. To the best of our knowledge, this is the first tutorial article on interactive VL. We describe evaluation categories of existing relevant research into unique subject groups that facilitate and inform comparisons of literacy literature and provide a starting point for interested readers. In addition, the introduction also provides an overview of the various evaluation techniques used in this field of research and their challenging nature. Our introduction provides researchers with unexplored directions that may lead to future work. This starting point serves as a valuable resource for beginners interested in the topic of VL.
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Visualização de Dados , Compreensão , Humanos , Reconhecimento Visual de ModelosRESUMO
The ability to recognize misleading data visualizations is a key aspect of visualization literacy. In this article, we argue that learning to successfully identify a deceptive graphic requires strategies that deliberately force learners to take an active role in the visualization process. We describe a series of experiments where three groups of learners were shown various deceptive graphics and asked to answer a series of questions. Three different interventions were analyzed to compare the educational effectiveness of the strategies used to engage learners into the process of identifying deceptive visualizations. Our results suggest that the ability to identify deceptive visualizations must be explicitly taught as a core element of visualization literacy. Although both traditional and self-learning approaches are beneficial, the more active the intervention, the higher its educational effectiveness.
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Aprendizagem , Alfabetização , Visualização de Dados , EnganaçãoRESUMO
We share our experiences of teaching virtual reality with Ubiq, an open-source system for building social virtual reality (VR). VR as a subject touches on many areas, including perception, human-computer interaction, and psychology. In our VE module, we consider all aspects of VR. In recent years, networked VR, and in particular social VR, has become increasingly relevant, at the same time as demand for online and hybrid teaching has increased. Commercial social virtual reality systems have proliferated, but for a number of reasons, this has not resulted in systems any more suitable for research and teaching. As a result we created Ubiq, a system for building social VR applications designed first for research and teaching. In this article, we describe how Ubiq came to be, and our experiences of using it in our virtual environments module over the last two years.
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Rayground is a novel online framework for fast prototyping and interactive demonstration of ray tracing algorithms. It aims to set the ground for the online development of ray-traced visualization algorithms in an accessible manner for everyone, stripping off the mechanics that get in the way of creativity and the understanding of the core concepts. Due to the COVID-19 pandemic, remote teaching and online coursework have taken center stage. In this work, we demonstrate how Rayground can incorporate advanced instructive rendering media during online lectures as well as offer attractive student assignments in an engaging, hands-on manner. We cover things to consider when building or porting methods to this new development platform, best practices in remote teaching and learning activities, and time-tested assessment and grading strategies suitable for fully online university courses.
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This article details a system titled "Camera as Mediator" that was built to aid undergraduate Film Studies students study camera placement and shot composition techniques. Learning how camera placement impacts a film is a common educational outcome in undergraduate Film Studies classes. However, building a controlled set with proper lighting, actors, and props is a cost- and time-prohibitive task in a typical introductory course. A virtual system can give students more hands-on experience and leave ample time to focus on core learning outcomes. To this end, we constructed a photorealistic virtual environment to replicate a scene from the Charlie Chaplin film "The Gold Rush" using computer-generated models and three-dimensional scans of actors dressed as the characters from the movie. An interface was designed to allow students to navigate around the scene with a virtual camera and capture shots from perspectives not visible in the original movie. By saving and comparing these different shots, students are easily able to explore how the mood and feel of a story changes with the camera's perspective. Doing this virtually enables undergraduate students in large classes and/or online classes and with potentially limited time and equipment to study film making techniques in greater depth than they would otherwise.
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Modern computer graphics courses require students to complete assignments involving computer programming. The evaluation of student programs, either by the student (self-assessment) or by the instructors (grading) can take a considerable amount of time and does not scale well with large groups. Interactive judges giving a pass/fail verdict do constitute a scalable solution, but they only provide feedback on output correctness. In this article, we present a tool to provide extensive feedback on student submissions. The feedback is based both on checking the output against test sets, as well as on syntactic and semantic analysis of the code. These analyses are performed through a set of code features and instructor-defined rubrics. The tool is built with Python and supports shader programs written in GLSL. Our experiments demonstrate that the tool provides extensive feedback that can be useful to support self-assessment, facilitate grading, and identify frequent programming mistakes.
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We share our experiences teaching university students about clustering algorithms using EduClust, an online visualization we developed. EduClust supports professors in preparing teaching material and students in visually and interactively exploring cluster steps and the effects of changing clustering parameters. We used EduClust for two years in our computer science lectures on clustering algorithms and share our experience integrating the online application in a data science curriculum. We also point to opportunities for future development.