Matching Items (51)
Filtering by
- All Subjects: Computer Science
- All Subjects: Educational technology
- All Subjects: instructional design
Description
The video game graphics pipeline has traditionally rendered the scene using a polygonal approach. Advances in modern graphics hardware now allow the rendering of parametric methods. This thesis explores various smooth surface rendering methods that can be integrated into the video game graphics engine. Moving over to parametric or smooth surfaces from the polygonal domain has its share of issues and there is an inherent need to address various rendering bottlenecks that could hamper such a move. The game engine needs to choose an appropriate method based on in-game characteristics of the objects; character and animated objects need more sophisticated methods whereas static objects could use simpler techniques. Scaling the polygon count over various hardware platforms becomes an important factor. Much control is needed over the tessellation levels, either imposed by the hardware limitations or by the application, to be able to adaptively render the mesh without significant loss in performance. This thesis explores several methods that would help game engine developers in making correct design choices by optimally balancing the trade-offs while rendering the scene using smooth surfaces. It proposes a novel technique for adaptive tessellation of triangular meshes that vastly improves speed and tessellation count. It develops an approximate method for rendering Loop subdivision surfaces on tessellation enabled hardware. A taxonomy and evaluation of the methods is provided and a unified rendering system that provides automatic level of detail by switching between the methods is proposed.
ContributorsAmresh, Ashish (Author) / Farin, Gerlad (Thesis advisor) / Razdan, Anshuman (Thesis advisor) / Wonka, Peter (Committee member) / Hansford, Dianne (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this survey study was to collect data from pre-K-12 educators in the U.S. regarding their perceptions of the purpose, conceptions, use, impact, and results of educational research. The survey tool was based on existing questionnaires and case studies in the literature, as well as newly developed items. 3,908 educators in a database developed over 10+ years at the world's largest education company were sent a recruiting email; 400 elementary and secondary teachers in the final sample completed the online survey containing 48 questions over a three-week deployment period in the spring of 2013. Results indicated that overall teachers believe educational research is important, that the most important purpose of research is to increase effectiveness of classroom practice, yet research is not frequently sought out during the course of practice. Teachers perceive results in research journals as the most trustworthy yet also perceive research journals the most difficult to access (relying second-most often for research via in-service trainings). These findings have implications for teachers, administrators, policy-makers, and researchers. Educational researchers should seek to address both the theoretical and the applied aspects of learning. Professional development must make explicit links between research findings and classroom strategies and tactics, and research must be made more readily available to those who are not currently seeking additional credentialing, and therefore do not individually have access to scholarly literature. Further research is needed to expand the survey sample and refine the survey instrument. Similar research with administrators in pre-K-20 settings as well as in-depth interviews would serve to investigate the "why" of many findings.
ContributorsMahoney, Shawn (Author) / Savenye, Wilhelmina (Thesis advisor) / Nelson, Brian (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the unveiling of the National Educational Technology Plan 2010, both preservice and inservice K12 teachers in the United States are expected to create a classroom environment that fosters the creation of digital citizens. However, it is unclear whether or not teacher education programs build this direct instruction, or any other method of introducing students to the National Education Technology Standards (NETS), "a standard of excellence and best practices in learning, teaching and leading with technology in education," into their curriculum (International Society for Technology in Education, 2012). As with most teaching skills, the NETS and standards-based technology integration must be learned through exposure during the teacher preparation curriculum, either through modeling, direct instruction or assignments constructed to encourage standards-based technology integration. This study attempted to determine the extent to which preservice teachers at Arizona State University (ASU) enrolled in the Mary Lou Fulton Teachers College (MLFTC) can recognize the National Education Technology Standards (NETS) published by the International Society for Technology in Education (ISTE) and to what extent preservice teachers are exposed to technology integration in accordance with the NETS-T standards in their preparation curriculum in order to answer the questions of whether or not teacher education curriculum provides students an opportunity to learn and apply the NETS-T and if preservice teachers in core teacher preparation program courses that include objectives that integrate technology are more likely to be able to identify NETS-T standards than those in courses that do not include these elements In order to answer these questions, a mixed-method design study was utilized to gather data from an electronic survey, one-on-one interviews with students, faculty, and administrators, and document analysis of core course objectives and curriculum goals in the teacher certification program at ASU. The data was analyzed in order to determine the relationship between the preservice teachers, the NETS-T standards, and the role technology plays in the curriculum of the teacher preparation program. Results of the analysis indicate that preservice teachers have a minimum NETS-T awareness at the Literacy level, indicating that they can use technology skills when prompted and explore technology independently.
ContributorsLewis, Carrie L (Author) / Nelson, Brian (Thesis advisor) / Archambault, Leanna (Thesis advisor) / Savenye, Wilhelmenia (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2013
Description
Detection of extruded features like rooftops and trees in aerial images automatically is a very active area of research. Elevated features identified from aerial imagery have potential applications in urban planning, identifying cover in military training or flight training. Detection of such features using commonly available geospatial data like orthographic aerial imagery is very challenging because rooftop and tree textures are often camouflaged by similar looking features like roads, ground and grass. So, additonal data such as LIDAR, multispectral imagery and multiple viewpoints are exploited for more accurate detection. However, such data is often not available, or may be improperly registered or inacurate. In this thesis, we discuss a novel framework that only uses orthographic images for detection and modeling of rooftops. A segmentation scheme that initializes by assigning either foreground (rooftop) or background labels to certain pixels in the image based on shadows is proposed. Then it employs grabcut to assign one of those two labels to the rest of the pixels based on initial labeling. Parametric model fitting is performed on the segmented results in order to create a 3D scene and to facilitate roof-shape and height estimation. The framework can also benefit from additional geospatial data such as streetmaps and LIDAR, if available.
ContributorsKhanna, Kunal (Author) / Femiani, John (Thesis advisor) / Wonka, Peter (Thesis advisor) / Razdan, Anshuman (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study explored three methods to measure cognitive load in a learning environment using four logic puzzles that systematically varied in level of intrinsic cognitive load. Participants' perceived intrinsic load was simultaneously measured with a self-report measure--a traditional subjective measure--and two objective, physiological measures based on eye-tracking and EEG technology. In addition to gathering self-report, eye-tracking data, and EEG data, this study also captured data on individual difference variables and puzzle performance. Specifically, this study addressed the following research questions: 1. Are self-report ratings of cognitive load sensitive to tasks that increase in level of intrinsic load? 2. Are physiological measures sensitive to tasks that increase in level of intrinsic load? 3. To what extent do objective physiological measures and individual difference variables predict self-report ratings of intrinsic cognitive load? 4. Do the number of errors and the amount of time spent on each puzzle increase as the puzzle difficulty increases? Participants were 56 undergraduate students. Results from analyses with inferential statistics and data-mining techniques indicated features from the physiological data were sensitive to the puzzle tasks that varied in level of intrinsic load. The self-report measures performed similarly when the difference in intrinsic load of the puzzles was the most varied. Implications for these results and future directions for this line of research are discussed.
ContributorsJoseph, Stacey (Author) / Atkinson, Robert K (Thesis advisor) / Johnson-Glenberg, Mina (Committee member) / Nelson, Brian (Committee member) / Klein, James (Committee member) / Arizona State University (Publisher)
Created2013
Description
The purpose of this study was to investigate the effects of instructor response prompts and rubrics on students' performance in an asynchronous discussion-board assignment, their learning achievement on an objective-type posttest, and their reported satisfaction levels. Researchers who have studied asynchronous computer-mediated student discussion transcripts have found evidence of mostly mid-level critical thinking skills, with fewer examples limited to lower or higher order thinking skill demonstration. Some researchers suggest that instructors may facilitate increased demonstration of higher-order critical thinking skills within asynchronous discussion-board activities. However, there is little empirical evidence available to compare the use of different external supports to facilitate students' critical thinking skills performance and learning achievement in blended learning environments. Results of the present study indicate that response prompts and rubrics can affect students' discussion performance, learning, and satisfaction ratings. The results, however, are complex, perhaps mirroring the complexity of instructor-led online learning environments. Regarding discussion board performance, presenting students with a rubric tended to yield higher scores on most aspects that is, on overall performance, as well as depth and breadth of performance, though these differences were not significant. In contrast, instructor prompts tended to yield lower scores on aspects of discussion board performance. On breadth, in fact, this main effect difference was significant. Interactions also indicated significant differences on several aspects of discussion board performance, in most cases indicating that the combination of rubric and prompt was detrimental to scores. The learning performance on the quiz showed, again, the effectiveness of rubrics, with students who received the rubric earning significantly higher scores, and with no main effects or interactions for instructor prompts. Regarding student satisfaction, again, the picture is complicated. Results indicated that, in some instances, the integration of prompts resulted in lower satisfaction ratings, particularly in the areas of students' perceptions of the amount of work required, learning in the partially online format, and student-to-student interaction. Based on these results, design considerations to support rubric use and explicit feedback in asynchronous discussions to support student learning are proposed.
ContributorsGiacumo, Lisa (Author) / Savenye, Wilhelmina (Thesis advisor) / Nelson, Brian (Committee member) / Legacy, Jane (Committee member) / Bitter, Gary (Committee member) / Arizona State University (Publisher)
Created2012
Description
The gameplay experience can be understood as an interaction between player and game design characteristics. A greater understanding of these characteristics can be gained through empirical means. Subsequently, an enhanced knowledge of these characteristics should enable the creation of games that effectively generate desirable experiences for players. The purpose of this study was to investigate the relationships between gameplay enjoyment and the individual characteristics of gaming goal orientations, game usage, and gender. A total of 301 participants were surveyed and the data were analyzed using Structural Equation Modeling (SEM). This led to an expanded Gameplay Enjoyment Model (GEM) with 41 game features, an overarching Enjoyment factor, and 9 specific components, including Challenge, Companionship, Discovery, Fantasy, Fidelity, Identity, Multiplayer, Recognition, and Strategy. Furthermore, the 3x2 educational goal orientation framework was successfully applied to a gaming context. The resulting 3x2 Gaming Goal Orientations (GGO) model consists of 18 statements that describe players' motivations for gaming, which are distributed across the six dimensions of Task-Approach, Task-Avoidance, Self-Approach, Self-Avoidance, Other-Approach, and Other-Avoidance. Lastly, players' individual characteristics were used to predict gameplay enjoyment, which resulted in the formation of the GEM-Individual Characteristics (GEM-IC) model. In GEM-IC, the six GGO dimensions were the strongest predictors. Meanwhile, game usage variables like multiplayer, genre, and platform preference, were minimal to moderate predictors. Although commonly appearing in games research, gender and game time commitment variables failed to predict enjoyment. The results of this study enable important work to be conducted involving game experiences and player characteristics. After several empirical iterations, GEM is considered suitable to employ as a research and design tool. In addition, GGO should be useful to researchers interested in how player motivations relate to gameplay experiences. Moreover, GEM-IC points to several variables that may prove useful in future research. Accordingly, it is posited that researchers will derive more meaningful insights on games and players by investigating detailed, context-specific characteristics as compared to general, demographic ones. Ultimately, it is believed that GEM, GGO, and GEM-IC will be useful tools for researchers and designers who seek to create effective gameplay experiences that meet the needs of players.
ContributorsQuick, John (Author) / Atkinson, Robert (Thesis advisor) / McNamara, Danielle (Committee member) / Nelson, Brian (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
Description
Night vision goggles (NVGs) are widely used by helicopter pilots for flight missions at night, but the equipment can present visually confusing images especially in urban areas. A simulation tool with realistic nighttime urban images would help pilots practice and train for flight with NVGs. However, there is a lack of tools for visualizing urban areas at night. This is mainly due to difficulties in gathering the light system data, placing the light systems at suitable locations, and rendering millions of lights with complex light intensity distributions (LID). Unlike daytime images, a city can have millions of light sources at night, including street lights, illuminated signs, and light shed from building interiors through windows. In this paper, a Procedural Lighting tool (PL), which predicts the positions and properties of street lights, is presented. The PL tool is used to accomplish three aims: (1) to generate vector data layers for geographic information systems (GIS) with statistically estimated information on lighting designs for streets, as well as the locations, orientations, and models for millions of streetlights; (2) to generate geo-referenced raster data to suitable for use as light maps that cover a large scale urban area so that the effect of millions of street light can be accurately rendered at real time, and (3) to extend existing 3D models by generating detailed light-maps that can be used as UV-mapped textures to render the model. An interactive graphical user interface (GUI) for configuring and previewing lights from a Light System Database (LDB) is also presented. The GUI includes physically accurate information about LID and also the lights' spectral power distributions (SPDs) so that a light-map can be generated for use with any sensor if the sensors luminosity function is known. Finally, for areas where more detail is required, a tool has been developed for editing and visualizing light effects over a 3D building from many light sources including area lights and windows. The above components are integrated in the PL tool to produce a night time urban view for not only a large-scale area but also a detail of a city building.
ContributorsChuang, Chia-Yuan (Author) / Femiani, John (Thesis advisor) / Razdan, Anshuman (Committee member) / Amresh, Ashish (Committee member) / Arizona State University (Publisher)
Created2011
Description
The goal of this research was to understand the different kinds of learning that take place in Mod The Sims (MTS), an online Sims gaming community. The study aimed to explore users' experiences and to understand learning practices that are not commonly observed in formal educational settings. To achieve this goal, the researcher conducted a four-year virtual ethnographic study that followed guidelines set forth in Hine (2000). After Hine, the study focused on understanding the complexity of the relationships between technology and social interactions among people, with a particular emphasis on investigating how participants shaped both the culture and structure of the affinity space. The format for the dissertation consists of an introduction, three core chapters that present different sets of findings, and a concluding chapter. Each of the core chapters, which can stand alone as separate studies, applies different theoretical lenses and analytic methods and uses a separate data set. The data corpus includes hundreds of thread posts, member profiles, online interview data obtained through email and personal messaging (PM), numerous screenshots, field notes, and additional artifacts, such as college coursework shared by a participant. Chapter 2 examines thread posts to understand the social support system in MTS and the language learning practices of one member who was a non-English speaker. Chapter 3 analyzes thread posts from administrative staff and users in MTS to identify patterns of interactions, with the goal of ascertaining how users contribute to the ongoing design and redesign of the site. Chapter 4 investigates user-generated tutorials to understand the nature of these instructional texts and how they are adapted to an online context. The final chapter (Chapter 5) presents conclusions about how the analyses overall represent examples of participatory learning practices that expand our understanding of 21st century learning. Finally, the chapter offers theoretical and practical implications, reflections on lessons learned, and suggestions for future research.
ContributorsLee, Yoonhee Naseef (Author) / Hayes, Elisabeth (Thesis advisor) / Gee, James (Committee member) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2012
Description
Education of any skill based subject, such as mathematics or language, involves a significant amount of repetition and pratice. According to the National Survey of Student Engagements, students spend on average 17 hours per week reviewing and practicing material previously learned in a classroom, with higher performing students showing a tendency to spend more time practicing. As such, learning software has emerged in the past several decades focusing on providing a wide range of examples, practice problems, and situations for users to exercise their skills. Notably, math students have benefited from software that procedurally generates a virtually infinite number of practice problems and their corresponding solutions. This allows for instantaneous feedback and automatic generation of tests and quizzes. Of course, this is only possible because software is capable of generating and verifying a virtually endless supply of sample problems across a wide range of topics within mathematics. While English learning software has progressed in a similar manner, it faces a series of hurdles distinctly different from those of mathematics. In particular, there is a wide range of exception cases present in English grammar. Some words have unique spellings for their plural forms, some words have identical spelling for plural forms, and some words are conjugated differently for only one particular tense or person-of-speech. These issues combined make the problem of generating grammatically correct sentences complicated. To compound to this problem, the grammar rules in English are vast, and often depend on the context in which they are used. Verb-tense agreement (e.g. "I eat" vs "he eats"), and conjugation of irregular verbs (e.g. swim -> swam) are common examples. This thesis presents an algorithm designed to randomly generate a virtually infinite number of practice problems for students of English as a second language. This approach differs from other generation approaches by generating based on a context set by educators, so that problems can be generated in the context of what students are currently learning. The algorithm is validated through a study in which over 35 000 sentences generated by the algorithm are verified by multiple grammar checking algorithms, and a subset of the sentences are validated against 3 education standards by a subject matter expert in the field. The study found that this approach has a significantly reduced grammar error ratio compared to other generation algorithms, and shows potential where context specification is concerned.
ContributorsMoore, Zachary Christian (Author) / Amresh, Ashish (Thesis director) / Nelson, Brian (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05