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- All Subjects: Machine Learning
- Member of: ASU Electronic Theses and Dissertations
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Status: Published
Description
This action research study explored what would happen if a principal network was created to provide time for collaboration about critical case studies of practice. The participants in this study were novice and experienced principals in an elementary school district in Arizona. Based on the underpinnings of the Wallace Foundation principal support programs, the study was designed to combat the limited professional development offerings for in-service principals. Modeling the use of cases from the legal and medical professions, this study utilized case studies as the base for peer collaboration to extend the principals' critical thinking skills of relevance, breadth, and depth.
The study design aligned with adult learning theory and focused on authentic problem solving. Participants read case studies, completed individual case analysis, collaborated, and wrote reflections. The cases were intentionally selected to match current problems of practice for the participants. This mixed methods study followed a sequential analysis process beginning with qualitative analysis using a grounded theory approach and moving to quantitative analysis.
The results of this study indicated that the participants' ability to think critically about the problem (relevance) and its complexity (breadth and depth) increased over time. The data also showed that the principals gained an increased awareness and appreciation for multiple perspectives. Lastly, the participants valued the time to collaborate together, gain insight from one another and reduce feelings of isolation in their role as administrators. Future research should continue to explore the use of critical case studies of practice as a in participatory action research with in-service principals.
The study design aligned with adult learning theory and focused on authentic problem solving. Participants read case studies, completed individual case analysis, collaborated, and wrote reflections. The cases were intentionally selected to match current problems of practice for the participants. This mixed methods study followed a sequential analysis process beginning with qualitative analysis using a grounded theory approach and moving to quantitative analysis.
The results of this study indicated that the participants' ability to think critically about the problem (relevance) and its complexity (breadth and depth) increased over time. The data also showed that the principals gained an increased awareness and appreciation for multiple perspectives. Lastly, the participants valued the time to collaborate together, gain insight from one another and reduce feelings of isolation in their role as administrators. Future research should continue to explore the use of critical case studies of practice as a in participatory action research with in-service principals.
ContributorsKubasko, Wendy Lynn (Author) / Rotheram-Fuller, Erin (Thesis advisor) / Dinn-You Liou, Daniel (Committee member) / Diaz, Rene (Committee member) / Arizona State University (Publisher)
Created2015
Description
With the rise of social media, hundreds of millions of people spend countless hours all over the globe on social media to connect, interact, share, and create user-generated data. This rich environment provides tremendous opportunities for many different players to easily and effectively reach out to people, interact with them, influence them, or get their opinions. There are two pieces of information that attract most attention on social media sites, including user preferences and interactions. Businesses and organizations use this information to better understand and therefore provide customized services to social media users. This data can be used for different purposes such as, targeted advertisement, product recommendation, or even opinion mining. Social media sites use this information to better serve their users.
Despite the importance of personal information, in many cases people do not reveal this information to the public. Predicting the hidden or missing information is a common response to this challenge. In this thesis, we address the problem of predicting user attributes and future or missing links using an egocentric approach. The current research proposes novel concepts and approaches to better understand social media users in twofold including, a) their attributes, preferences, and interests, and b) their future or missing connections and interactions. More specifically, the contributions of this dissertation are (1) proposing a framework to study social media users through their attributes and link information, (2) proposing a scalable algorithm to predict user preferences; and (3) proposing a novel approach to predict attributes and links with limited information. The proposed algorithms use an egocentric approach to improve the state of the art algorithms in two directions. First by improving the prediction accuracy, and second, by increasing the scalability of the algorithms.
Despite the importance of personal information, in many cases people do not reveal this information to the public. Predicting the hidden or missing information is a common response to this challenge. In this thesis, we address the problem of predicting user attributes and future or missing links using an egocentric approach. The current research proposes novel concepts and approaches to better understand social media users in twofold including, a) their attributes, preferences, and interests, and b) their future or missing connections and interactions. More specifically, the contributions of this dissertation are (1) proposing a framework to study social media users through their attributes and link information, (2) proposing a scalable algorithm to predict user preferences; and (3) proposing a novel approach to predict attributes and links with limited information. The proposed algorithms use an egocentric approach to improve the state of the art algorithms in two directions. First by improving the prediction accuracy, and second, by increasing the scalability of the algorithms.
ContributorsAbbasi, Mohammad Ali, 1975- (Author) / Liu, Huan (Thesis advisor) / Davulcu, Hasan (Committee member) / Ye, Jieping (Committee member) / Agarwal, Nitin (Committee member) / Arizona State University (Publisher)
Created2014
Description
ABSTRACT
The purpose of this descriptive study was to gain an understanding of the confidence level held by third, fourth, and fifth grade teachers as to their preparedness for teaching the cognitive demands of the Common Core State Standards (Arizona's College and Career Ready Standards) to all students, in particular Hispanic students living in poverty, who occupy close to a third of all classroom seats in Arizona. The achievement gap between Hispanic students living in poverty and non-Hispanic students of non-poverty status is one of the largest achievement gaps in Arizona, which has existed with minimal change for more than 12 years. By gaining an understanding of the teachers' confidence in teaching critical thinking skills, further support and professional development is suggested to link a teacher's knowledge to instructional practice that in turn increases the academic achievement of Arizona's poor Hispanic students.
The process of gaining this understanding was by using a multi-dimensional survey with 500 third through fifth grade teachers in two uniquely different, but representative, Arizona school districts. Approximately one-third of those teachers responded to the multi-dimensional survey about teaching the critical thinking (CT) skills of Arizona's College and Career Ready Standards for English Language Arts. The survey asked teachers to rate their levels of preparedness for teaching CT to several types of students, to choose a CT definition, describe the relationship of CT and reading, explain how they teach CT to students who are reading below grade level, express the support they need to teach CT to those students, and rate the effectiveness of several CT classroom vignettes for different types of students. Although the questions involved several types of students, the primary focus was on exploring the teachers' position with teaching CT to Low SES Hispanic students.
A disconnect was revealed between the teachers' perception that they had the ability and knowledge necessary to teach critical thinking skills and their ability to identify ineffective critical thinking instructional practices. This disconnect may be interfering with the link between the professional development teachers are currently receiving to implement Common Core State Standards and teachers actively engaging in learning what is needed to effectively teach critical thinking skills to their students.
The purpose of this descriptive study was to gain an understanding of the confidence level held by third, fourth, and fifth grade teachers as to their preparedness for teaching the cognitive demands of the Common Core State Standards (Arizona's College and Career Ready Standards) to all students, in particular Hispanic students living in poverty, who occupy close to a third of all classroom seats in Arizona. The achievement gap between Hispanic students living in poverty and non-Hispanic students of non-poverty status is one of the largest achievement gaps in Arizona, which has existed with minimal change for more than 12 years. By gaining an understanding of the teachers' confidence in teaching critical thinking skills, further support and professional development is suggested to link a teacher's knowledge to instructional practice that in turn increases the academic achievement of Arizona's poor Hispanic students.
The process of gaining this understanding was by using a multi-dimensional survey with 500 third through fifth grade teachers in two uniquely different, but representative, Arizona school districts. Approximately one-third of those teachers responded to the multi-dimensional survey about teaching the critical thinking (CT) skills of Arizona's College and Career Ready Standards for English Language Arts. The survey asked teachers to rate their levels of preparedness for teaching CT to several types of students, to choose a CT definition, describe the relationship of CT and reading, explain how they teach CT to students who are reading below grade level, express the support they need to teach CT to those students, and rate the effectiveness of several CT classroom vignettes for different types of students. Although the questions involved several types of students, the primary focus was on exploring the teachers' position with teaching CT to Low SES Hispanic students.
A disconnect was revealed between the teachers' perception that they had the ability and knowledge necessary to teach critical thinking skills and their ability to identify ineffective critical thinking instructional practices. This disconnect may be interfering with the link between the professional development teachers are currently receiving to implement Common Core State Standards and teachers actively engaging in learning what is needed to effectively teach critical thinking skills to their students.
ContributorsFast, Deborah (Author) / Fischman, Gustavo E (Thesis advisor) / Harris, Connie (Committee member) / Bader, Beth (Committee member) / Arizona State University (Publisher)
Created2014
Description
Users often join an online social networking (OSN) site, like Facebook, to remain social, by either staying connected with friends or expanding social networks. On an OSN site, users generally share variety of personal information which is often expected to be visible to their friends, but sometimes vulnerable to unwarranted access from others. The recent study suggests that many personal attributes, including religious and political affiliations, sexual orientation, relationship status, age, and gender, are predictable using users' personal data from an OSN site. The majority of users want to remain socially active, and protect their personal data at the same time. This tension leads to a user's vulnerability, allowing privacy attacks which can cause physical and emotional distress to a user, sometimes with dire consequences. For example, stalkers can make use of personal information available on an OSN site to their personal gain. This dissertation aims to systematically study a user vulnerability against such privacy attacks.
A user vulnerability can be managed in three steps: (1) identifying, (2) measuring and (3) reducing a user vulnerability. Researchers have long been identifying vulnerabilities arising from user's personal data, including user names, demographic attributes, lists of friends, wall posts and associated interactions, multimedia data such as photos, audios and videos, and tagging of friends. Hence, this research first proposes a way to measure and reduce a user vulnerability to protect such personal data. This dissertation also proposes an algorithm to minimize a user's vulnerability while maximizing their social utility values.
To address these vulnerability concerns, social networking sites like Facebook usually let their users to adjust their profile settings so as to make some of their data invisible. However, users sometimes interact with others using unprotected posts (e.g., posts from a ``Facebook page\footnote{The term ''Facebook page`` refers to the page which are commonly dedicated for businesses, brands and organizations to share their stories and connect with people.}''). Such interactions help users to become more social and are publicly accessible to everyone. Thus, visibilities of these interactions are beyond the control of their profile settings. I explore such unprotected interactions so that users' are well aware of these new vulnerabilities and adopt measures to mitigate them further. In particular, {\em are users' personal attributes predictable using only the unprotected interactions}? To answer this question, I address a novel problem of predictability of users' personal attributes with unprotected interactions. The extreme sparsity patterns in users' unprotected interactions pose a serious challenge. Therefore, I approach to mitigating the data sparsity challenge by designing a novel attribute prediction framework using only the unprotected interactions. Experimental results on Facebook dataset demonstrates that the proposed framework can predict users' personal attributes.
A user vulnerability can be managed in three steps: (1) identifying, (2) measuring and (3) reducing a user vulnerability. Researchers have long been identifying vulnerabilities arising from user's personal data, including user names, demographic attributes, lists of friends, wall posts and associated interactions, multimedia data such as photos, audios and videos, and tagging of friends. Hence, this research first proposes a way to measure and reduce a user vulnerability to protect such personal data. This dissertation also proposes an algorithm to minimize a user's vulnerability while maximizing their social utility values.
To address these vulnerability concerns, social networking sites like Facebook usually let their users to adjust their profile settings so as to make some of their data invisible. However, users sometimes interact with others using unprotected posts (e.g., posts from a ``Facebook page\footnote{The term ''Facebook page`` refers to the page which are commonly dedicated for businesses, brands and organizations to share their stories and connect with people.}''). Such interactions help users to become more social and are publicly accessible to everyone. Thus, visibilities of these interactions are beyond the control of their profile settings. I explore such unprotected interactions so that users' are well aware of these new vulnerabilities and adopt measures to mitigate them further. In particular, {\em are users' personal attributes predictable using only the unprotected interactions}? To answer this question, I address a novel problem of predictability of users' personal attributes with unprotected interactions. The extreme sparsity patterns in users' unprotected interactions pose a serious challenge. Therefore, I approach to mitigating the data sparsity challenge by designing a novel attribute prediction framework using only the unprotected interactions. Experimental results on Facebook dataset demonstrates that the proposed framework can predict users' personal attributes.
ContributorsGundecha, Pritam S (Author) / Liu, Huan (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Ye, Jieping (Committee member) / Barbier, Geoffrey (Committee member) / Arizona State University (Publisher)
Created2015
Description
This mixed methods participatory action research study explored how an instructional coach influenced a state mandated curriculum adoption at a Title 1 urban middle school. The purpose of this study was to identify ways in which an instructional coach supported a veteran staff during the adoption of new curriculum standards. The instructional coach/action researcher employed a three pronged coaching approach that incorporated individual and team coaching sessions and increased networking to encourage and support the development of social capital. This study was informed using Vygotsky's Social Learning Theory, Wenger's Communities of Practice, Coleman's Social Capital Theory, and Hall and Horde's Concerns-Based Adoption Model. The study is heavily weighted in favor of qualitative data which includes participant reflections, coach individual session and team session reflections, field-notes, team meeting videos, and exit interviews. Several themes emerged supporting the use of a differentiated coaching approach, the promotion of social capital, and the identification of initiative overload as a barrier to curriculum adoption. The quantitative data analysis, pre and post study Stages of Concern Questionnaires, produced evidence that participants experienced minor shifts in their concerns relating to the adoption of Common Core State Standards. Results were used to inform coaching decisions based on individual participant needs as well as to augment the qualitative findings. Ideas for further research are discussed.
ContributorsSchwarting, Joann (Author) / Wetzel, Keith (Thesis advisor) / Ewbank, Ann (Thesis advisor) / Johnson, Lynda (Committee member) / Arizona State University (Publisher)
Created2014
Description
Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms.
ContributorsSun, Liang (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Liu, Huan (Committee member) / Mittelmann, Hans D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation reports on an action research study that sought to discover how a new WiFi, tablet computing device, the Apple iPad, affected, enhanced, and impacted student engagement in an English Honors course at Scottsdale Community College. The researcher was also the instructor in the two semester, first-year, college composition sequence (English 101/102) in which all 18 students were provided the new Apple iPad tablet computing device. The researcher described how students adapted the Apple iPads to their academic lives, assessed iPad compatibility with current instructional technology systems, and interviewed participating students to document their beliefs about whether iPad activities enhanced the course. At the conclusion of the college composition sequence, 13 students agreed to participate in focus groups to describe how they made use of the iPad and to report on how the iPad influenced their engagement. Among other findings, students reported that there were compatibility problems with current SCC instructional technology systems, that the iPad increased their efficiency in completing informal educational tasks, but that the iPad was not useful for doing word processing and research. Recommendations for future use of the iPad in this course include reducing the number of iPads accessing the WiFi network at the same time, piloting the use of iPad word processing applications, researching more "mobile-friendly" web sites and documents, and developing innovative assignments that take advantage of iPad capabilities.
ContributorsTualla, Larry Tech (Author) / Clark, Christopher M. (Thesis advisor) / De Los Santos Jr., Alfredo G (Thesis advisor) / Young, Lisa C. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this study was to examine compulsory schooling in the United States and its potential to provide an inconsistent avenue to employment for students from neighborhoods of differing socioeconomic status. Specifically, this study asked why do students from privileged neighborhoods typically end up in positions of ownership and management while those from impoverished urban or rural neighborhoods end up in working-class positions or involved in cycles of incarceration and poverty? This research involved the use of qualitative methods, including participant observation and interview, as well as photography, to take a look at a reputable private day school in the southwest. Data was collected over the span of eight weeks and was then analyzed and compared with preexisting data on the schooling experience of students from impoverished urban and rural neighborhoods, particularly data focused on juvenile detention centers. Results showed that compulsory schooling differs in ways that contribute to the preexisting hierarchical class structure. The research suggests that schooling can be detrimental to the future quality of life for students in impoverished neighborhoods, which questions a compulsory school system that exists within the current hierarchical class system.
ContributorsTheodoropoulos, Eftyhia (Author) / Margolis, Eric (Thesis advisor) / Nakagawa, Kathryn (Committee member) / Appleton, Nicholas (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT Teachers working in isolation to overcome instructional challenges are left to their own devices, but teachers working together can benefit from others' perspectives. Teacher collaboration can increase communication and open doors to increased collective knowledge and rapport. Collaborative knowledge sharing and decision-making that focus on student achievement can go far in improving instructional learning. This action research focused on increasing collaboration among members of a middle school team of teachers. Involving teachers in a collaboration development processes was intended to improve productive interactions and contribute to instructional learning as a professional learning team. Study participants were involved in an eight week professional development initiative that involved techniques to promote collaboration along with instructional learning tools to promote professional learning in regard to guiding students to high levels of cognition. A mixed methods set of data was generated including a research journal, artifacts, surveys, meeting transcriptions, and interviews. Findings concluded that focusing on collaboration contributed to positive changes in the middle school team's interactions. Setting and revisiting norms of collaboration were crucial steps in this focus, leading to increased buy-in and active participation during team meetings. Focusing on relevance contributed to multiple aspects of the team's instructional learning. Participants valued their collaborative efforts especially when they found direct links between their professional learning and their individual classroom situations. Focusing on an action plan also contributed to participants' instructional learning. Setting manageable short terms goals gave the team direction and fostered accountability. Finally, working as a professional learning team contributed to the team's instructional learning. Taking the time to meet frequently allowed teachers to share classroom experiences, assist one another, and develop professionally.
ContributorsRiskus, A. Michael (Albert Michael) (Author) / Moore, David (Thesis advisor) / Cheatham, Gregory (Committee member) / Westhoff, Maggie (Committee member) / Arizona State University (Publisher)
Created2011
Description
This research is a reversal of the traditional concept of the student-teaching research experiment. Instead of studying the clear and stated goal of an apprenticeship, that of a pupil learning from the tutelage of a master, the focus here is on what a mentor-teacher learns from a student-teacher. During the act of teaching a novice, what can a mentor-teacher learn about her own practice, while demonstrating it to a pre-service teacher? Using the conceptual framework of the National Board for Professional Teaching Standards' Architecture of Accomplished Teaching, and using it within a framework centered around cognitive coaching and reciprocal mentoring, this action research study implemented an intervention that called for series of five cognitive coaching cycles between a mentor- and student-teacher designed to foster dialogue and reflection between them. The ultimate aim of this case study was to help determine what a mentor-teacher learned about her own practice as a result of mentoring a student-teacher. Qualitative data were collected over sixteen weeks in a charter high school. Five findings were identified created after the data were analyzed using a grounded theory approach, and four conclusions were drawn about the intervention's role in the mentor-teacher's reciprocal learning.
ContributorsMcCloy, Daniel (Author) / Beardsley, Audrey (Thesis advisor) / Serafini, Frank (Committee member) / Roen, Duane (Committee member) / Arizona State University (Publisher)
Created2011