Context-Aware Mobile Augmented Reality Visualization in Construction Engineering Education

Recent studies suggest that the number of students pursuing science, technology, engineering, and mathematics (STEM) degrees has been generally decreasing. An extensive body of research cites the lack of motivation and engagement in the learning process as a major underlying reason of this decline. It has been discussed that if properly implemented, instructional technology can enhance student engagement and the quality of learning. Therefore, the main goal of this research is to implement and assess effectiveness of augmented reality (AR)-based pedagogical tools on student learning. For this purpose, two sets of experiments were designed and implemented in two different construction and civil engineering undergraduate level courses at the University of Central Florida (UCF). The first experiment was designed to systematically assess the effectiveness of a context-aware mobile AR tool (CAM-ART) in real classroom-scale environment. This tool was used to enhance traditional lecture-based instruction and information delivery by augmenting the contents of an ordinary textbook using computer-generated three-dimensional (3D) objects and other virtual multimedia (e.g. sound, video, graphs). The experiment conducted on two separate control and test groups and pre- and post- performance data as well as student perception of using CAM-ART was collected through several feedback questionnaires. In the second experiment, a building design and assembly task competition was designed and conducted using a mobile AR platform. The pedagogical value of mobile AR-based instruction and information delivery to student learning in a large-scale classroom setting was also assessed and investigated. Similar to the first experiment, students in this experiment were divided into two control and test groups. Students\u27 performance data as well as their feedback, suggestions, and workload were systematically collected and analyzed. Data analysis showed that the mobile AR framework had a measurable and positive impact on students\u27 learning. In particular, it was found that students in the test group (who used the AR tool) performed slightly better with respect to certain measures and spent more time on collaboration, communication, and exchanging ideas in both experiments. Overall, students ranked the effectiveness of the AR tool very high and stated that it has a good potential to reform traditional teaching methods

Implementing non-photorealistic rendreing enhancements with real-time performance

We describe quality and performance enhancements, which work in real-time, to all well-known Non-photorealistic (NPR) rendering styles for use in an interactive context. These include Comic rendering, Sketch rendering, Hatching and Painterly rendering, but we also attempt and justify a widening of the established definition of what is considered NPR. In the individual Chapters, we identify typical stylistic elements of the different NPR styles. We list problems that need to be solved in order to implement the various renderers. Standard solutions available in the literature are introduced and in all cases extended and optimised. In particular, we extend the lighting model of the comic renderer to include a specular component and introduce multiple inter-related but independent geometric approximations which greatly improve rendering performance. We implement two completely different solutions to random perturbation sketching, solve temporal coherence issues for coal sketching and find an unexpected use for 3D textures to implement hatch-shading. Textured brushes of painterly rendering are extended by properties such as stroke-direction and texture, motion, paint capacity, opacity and emission, making them more flexible and versatile. Brushes are also provided with a minimal amount of intelligence, so that they can help in maximising screen coverage of brushes. We furthermore devise a completely new NPR style, which we call super-realistic and show how sample images can be tweened in real-time to produce an image-based six degree-of-freedom renderer performing at roughly 450 frames per second. Performance values for our other renderers all lie between 10 and over 400 frames per second on homePC hardware, justifying our real-time claim. A large number of sample screen-shots, illustrations and animations demonstrate the visual fidelity of our rendered images. In essence, we successfully achieve our attempted goals of increasing the creative, expressive and communicative potential of individual NPR styles, increasing performance of most of them, adding original and interesting visual qualities, and exploring new techniques or existing ones in novel ways.KMBT_363Adobe Acrobat 9.54 Paper Capture Plug-i