This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

Displaying 1 - 10 of 405
Filtering by

Clear all filters

151688-Thumbnail Image.png
Description
This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version

This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version was a business-as-usual traditional classroom teaching mathematics with direct instruction. The 2rd version of the course provided students with self-paced, individualized Algebra instruction with a web-based, intelligent tutor. The 3rd version of the course coupled self-paced, individualized instruction on the web-based, intelligent Algebra tutor coupled with a series of e-learning modules on self-regulated learning knowledge and skills that were distributed throughout the semester. A quasi-experimental, mixed methods evaluation design was used by assigning pre-registered, high-school remedial Algebra I class periods made up of an approximately equal number of students to one of the three study conditions or course versions: (a) the control course design, (b) web-based, intelligent tutor only course design, and (c) web-based, intelligent tutor + SRL e-learning modules course design. While no statistically significant differences on SRL skills, math achievement or motivation were found between the three conditions, effect-size estimates provide suggestive evidence that using the SRL e-learning modules based on ARCS motivation model (Keller, 2010) and Let Me Learn learning pattern instruction (Dawkins, Kottkamp, & Johnston, 2010) may help students regulate their learning and improve their study skills while using a web-based, intelligent Algebra tutor as evidenced by positive impacts on math achievement, motivation, and self-regulated learning skills. The study also explored predictive analyses using multiple regression and found that predictive models based on independent variables aligned to student demographics, learning mastery skills, and ARCS motivational factors are helpful in defining how to further refine course design and design learning evaluations that measure achievement, motivation, and self-regulated learning in web-based learning environments, including intelligent tutoring systems.
ContributorsBarrus, Angela (Author) / Atkinson, Robert K (Thesis advisor) / Van de Sande, Carla (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
151716-Thumbnail Image.png
Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a

The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
151718-Thumbnail Image.png
Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a

The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
152228-Thumbnail Image.png
Description
ABSTRACT This study describes student interactions in the academic social network site Edmodo versus student interactions in Facebook. This qualitative case study relies upon four high school juniors enrolled in Advanced Placement Language and Composition who use Edmodo to complete assignments for their English class. Their experiences were gathered in

ABSTRACT This study describes student interactions in the academic social network site Edmodo versus student interactions in Facebook. This qualitative case study relies upon four high school juniors enrolled in Advanced Placement Language and Composition who use Edmodo to complete assignments for their English class. Their experiences were gathered in an attempt to describe specific experiences in a complex system. Students were selected using an Internet Connectedness Index survey. Using a Virtual Community of Practice framework, students were asked about their experiences in Edmodo. This study concludes that Edmodo and Facebook can be compared in three categories: accessibility, functionality, and environment. Unlike Facebook, which students access regularly, students access Edmodo only to fulfill the teacher's participation expectations for the specific grade they wish to receive. Additionally, students appreciated the convenience of using Edmodo to complete assignments. The functionality of Edmodo is quite similar in layout and appearance to Facebook, yet students were unaware of the media sharing capability, wished for private messaging options, and desired the ability to tag peers for direct comment using the @ sign, all options that are available in Facebook. Students felt the environment in Edmodo could best be characterized as intellectual and academic, which some mentioned might best be used with honors or AP students. A surprising benefit of Edmodo is the lack of social cues enable students to feel free of judgment when composing writing. Some felt this allowed students to know their classmates better and share their true personae free from judgment of classmates. As a result of the case studies of four students, this study seeks to illustrate how students interact in Edmodo versus Facebook to provide a robust image of the academic social network site for teachers seeking to implement educational technology in their classes.
ContributorsCurran-Sejkora, Elizabeth (Author) / Blasingame, James (Thesis advisor) / Nilsen, Alleen (Committee member) / Rodrigo, Rochelle (Committee member) / Turchi, Laura (Committee member) / Arizona State University (Publisher)
Created2013
152244-Thumbnail Image.png
Description
Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR)

Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR) delivered via mobile technology that could potentially provide rich, contextualized learning for understanding concepts related to statistics education. This study examined the effects of AR experiences for learning basic statistical concepts. Using a 3 x 2 research design, this study compared learning gains of 252 undergraduate and graduate students from a pre- and posttest given before and after interacting with one of three types of augmented reality experiences, a high AR experience (interacting with three dimensional images coupled with movement through a physical space), a low AR experience (interacting with three dimensional images without movement), or no AR experience (two dimensional images without movement). Two levels of collaboration (pairs and no pairs) were also included. Additionally, student perceptions toward collaboration opportunities and engagement were compared across the six treatment conditions. Other demographic information collected included the students' previous statistics experience, as well as their comfort level in using mobile devices. The moderating variables included prior knowledge (high, average, and low) as measured by the student's pretest score. Taking into account prior knowledge, students with low prior knowledge assigned to either high or low AR experience had statistically significant higher learning gains than those assigned to a no AR experience. On the other hand, the results showed no statistical significance between students assigned to work individually versus in pairs. Students assigned to both high and low AR experience perceived a statistically significant higher level of engagement than their no AR counterparts. Students with low prior knowledge benefited the most from the high AR condition in learning gains. Overall, the AR application did well for providing a hands-on experience working with statistical data. Further research on AR and its relationship to spatial cognition, situated learning, high order skill development, performance support, and other classroom applications for learning is still needed.
ContributorsConley, Quincy (Author) / Atkinson, Robert K (Thesis advisor) / Nguyen, Frank (Committee member) / Nelson, Brian C (Committee member) / Arizona State University (Publisher)
Created2013
151862-Thumbnail Image.png
Description
This dissertation describes the development of a state-of-the-art immersive media environment and its potential to motivate high school youth with autism to vocally express themselves. Due to the limited availability of media environments in public education settings, studies on the use of such systems in special education contexts are rare.

This dissertation describes the development of a state-of-the-art immersive media environment and its potential to motivate high school youth with autism to vocally express themselves. Due to the limited availability of media environments in public education settings, studies on the use of such systems in special education contexts are rare. A study called Sea of Signs utilized the Situated Multimodal Art Learning Lab (SMALLab), to present a custom-designed conversational scenario for pairs of youth with autism. Heuristics for building the scenario were developed following a 4-year design-based research approach that fosters social interaction, communication, and self-expression through embodied design. Sea of Signs implemented these heuristics through an immersive experience, supported by spatial and audio-visual feedback that helped clarify and reinforce students' vocal expressions within a partner-based conversational framework. A multiple-baseline design across participants was used to determine the extent to which individuals exhibited observable change as a result of the activity in SMALLab. Teacher interviews were conducted prior to the experimental phase to identify each student's pattern of social interaction, communication, and problem-solving strategies in the classroom. Ethnographic methods and video coding were used throughout the experimental phase to assess whether there were changes in (a) speech duration per session and per turn, (b) turn-taking patterns, and (c) teacher prompting per session. In addition, teacher interviews were conducted daily after every SMALLab session to further triangulate the nature of behaviors observed in each session. Final teacher interviews were conducted after the experimental phase to collect data on possible transfer of behavioral improvements into students' classroom lives beyond SMALLab. Results from this study suggest that the activity successfully increased independently generated speech in some students, while increasing a focus on seeking out social partners in others. Furthermore, the activity indicated a number of future directions in research on the nature of voice and discourse, rooted in the use of aesthetics and phenomenology, to augment, extend, and encourage developments in directed communication skills for youth with autism.
ContributorsTolentino, Lisa (Author) / Paine, Garth (Thesis advisor) / Kozleski, Elizabeth B. (Thesis advisor) / Kelliher, Aisling (Committee member) / Megowan-Romanowicz, Colleen (Committee member) / Arizona State University (Publisher)
Created2013
152039-Thumbnail Image.png
Description
An integral part of teacher development are teacher observations. Many teachers are observed once or twice a year to evaluate their performance and hold them accountable for meeting standards. Instructional coaches, however, observe and work with teachers to help them reflect on their performance, with the goal of improving their

An integral part of teacher development are teacher observations. Many teachers are observed once or twice a year to evaluate their performance and hold them accountable for meeting standards. Instructional coaches, however, observe and work with teachers to help them reflect on their performance, with the goal of improving their practice. Video-based evidence has long been used in connection with teacher reflection and as the technology necessary to record video has become more readily available, video recordings have found an increasing presence in teacher observations. In addition, more and more schools are turning to mobile technology to help record evidence during teacher observations. Several mobile applications have been developed, which are designed to help instructional coaches, administrators, and teachers make the most of teacher observations. This study looked at the use of the DataCapture mobile application to record video-based evidence in teacher observations as part of an instructional coaching program in a large public school district in the Southwestern United States. Six instructional coaches and two teachers participated in interviews at the end of the study period. Additional data was collected from the DataCapture mobile application and from a survey of instructional coaches conducted by the school district in connection with its Title I programs. Results show that instructional coaches feel that using video-based evidence for teacher reflection is effective in a number of ways. Teachers who have experienced seeing themselves on video also felt that video-based evidence is effective at improving teacher reflection, while teachers who have not yet experienced seeing themselves on video displayed extreme apprehensiveness about being video recorded in the classroom. Instructional coaches felt the DataCapture mobile application was beneficial in teacher evaluation, but there were several issues that impacted the use of the mobile application and video-based evidence, including logistics, time requirements, and administrative support. The discussion focuses on recommendations for successfully using video-based evidence in an instructional coaching context, as well as some suggestions for other researchers attempting to study how video-based evidence impacts teachers' ability to reflect on their own teaching.
ContributorsShewell, Justin Reed (Author) / Bitter, Gary (Thesis advisor) / Dawson, Edwin (Committee member) / Blair, Heidi (Committee member) / Arizona State University (Publisher)
Created2013
151942-Thumbnail Image.png
Description
Researchers have postulated that math academic achievement increases student success in college (Lee, 2012; Silverman & Seidman, 2011; Vigdor, 2013), yet 80% of universities and 98% of community colleges require many of their first-year students to be placed in remedial courses (Bettinger & Long, 2009). Many high school graduates are

Researchers have postulated that math academic achievement increases student success in college (Lee, 2012; Silverman & Seidman, 2011; Vigdor, 2013), yet 80% of universities and 98% of community colleges require many of their first-year students to be placed in remedial courses (Bettinger & Long, 2009). Many high school graduates are entering college ill prepared for the rigors of higher education, lacking understanding of basic and important principles (ACT, 2012). The desire to increase academic achievement is a wide held aspiration in education and the idea of adapting instruction to individuals is one approach to accomplish this goal (Lalley & Gentile, 2009a). Frequently, adaptive learning environments rely on a mastery learning approach, it is thought that when students are afforded the opportunity to master the material, deeper and more meaningful learning is likely to occur. Researchers generally agree that the learning environment, the teaching approach, and the students' attributes are all important to understanding the conditions that promote academic achievement (Bandura, 1977; Bloom, 1968; Guskey, 2010; Cassen, Feinstein & Graham, 2008; Changeiywo, Wambugu & Wachanga, 2011; Lee, 2012; Schunk, 1991; Van Dinther, Dochy & Segers, 2011). The present study investigated the role of college students' affective attributes and skills, such as academic competence and academic resilience, in an adaptive mastery-based learning environment on their academic performance, while enrolled in a remedial mathematics course. The results showed that the combined influence of students' affective attributes and academic resilience had a statistically significant effect on students' academic performance. Further, the mastery-based learning environment also had a significant effect on their academic competence and academic performance.
ContributorsFoshee, Cecile Mary (Author) / Atkinson, Robert K (Thesis advisor) / Elliott, Stephen N. (Committee member) / Horan, John (Committee member) / Arizona State University (Publisher)
Created2013
151780-Thumbnail Image.png
Description
Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this thesis is creation

Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this thesis is creation of a software solution which can be used in the academia and industry for research in cyber physical systems related applications. The major features of the project are: creating a modular system for motion planning, use of Robot Operating System (ROS), use of triangulation for environment decomposition and using stargazer sensor for localization. The project is built on an open source software called ROS which provides an environment where it is very easy to integrate different modules be it software or hardware on a Linux based platform. Use of ROS implies the project or its modules can be adapted quickly for different applications as the need arises. The final software package created and tested takes a data file as its input which contains the LTL specifications, a symbols list used in the LTL and finally the environment polygon data containing real world coordinates for all polygons and also information on neighbors and parents of each polygon. The software package successfully ran the experiment of coverage, reachability with avoidance and sequencing.
ContributorsPandya, Parth (Author) / Fainekos, Georgios (Thesis advisor) / Dasgupta, Partha (Committee member) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2013
151793-Thumbnail Image.png
Description
Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to

Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to create high level motion plans to control robots in the field by converting a visual representation of the motion/task plan into a Linear Temporal Logic (LTL) specification. The visual interface is built on the Android tablet platform and provides functionality to create task plans through a set of well defined gestures and on screen controls. It uses the notion of waypoints to quickly and efficiently describe the motion plan and enables a variety of complex Linear Temporal Logic specifications to be described succinctly and intuitively by the user without the need for the knowledge and understanding of LTL specification. Thus, it opens avenues for its use by personnel in military, warehouse management, and search and rescue missions. This thesis describes the construction of LTL for various scenarios used for robot navigation using the visual interface developed and leverages the use of existing LTL based motion planners to carry out the task plan by a robot.
ContributorsSrinivas, Shashank (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2013