This dissertation investigates public-public program collaboration (PPPC) between Head Start and the Virginia Preschool Initiative and asks why and how, and to what extent PPPC occurs between these preschool programs. To frame an understanding of PPPC, the dissertation assays collaborative process dimensions, collaborative management techniques, and degrees of collaborative activity. In-depth interviews with Head Start and VPI administrators result in the analysis of 16 Head Start-VPI dyadic relationships and places the focus of this research on the micro-level actions of the program administrators. Each Head Start-VPI dyad is assigned a degree of collaborative activity along a continuum ranging from no relationship (one dyad), cooperation (four dyads), coordination (six dyads), or collaboration (five dyads), and is assessed in terms of the presence or absence of the collaborative process dimensions of governance, administration, organizational autonomy, norms of trust, and mutuality. Qualitative comparative analysis (QCA) is used to identify the underlying process dimensions that comprise collaboration at the varying degrees of collaborative activity. Collaborating dyads generally are found to exhibit all of the process dimensions, where the no relationship and cooperating dyads exhibit relatively few of the process dimensions. Coordinating dyads typically have strong structural dimensions but weak mutuality, or strong social capital dimensions, but weak administration. The dissertation shows how public administrators engage the collaborative management techniques of activating, framing, mobilizing, and synthesizing, and finds variation in management techniques across types of collaborative activities. It also argues for activation activity to include "history of collaboration" stories and identifies six framing types that intersect at being collaborative or non-collaborative in focus and mature or immature. The dissertation concludes with recommendations for current preschool administrators and future scholarship. / Ph. D.

Collaborative learning skills are one of the essential learning outcomes for a college education in 21st century. College students are expected to possess the ability to collaborate with others in order to succeed in their career after graduating from college. However, the effects of collegiate experiences on collaborative learning for different gender and academic areas are almost unexplored. In addition, researchers highlight the need for more research on interaction effects to explore whether different types of students respond differently to various collegiate experiences. The researcher examined the relationship of student-student interactions and student-faculty interactions with graduating seniors' perceived collaborative learning skills. Furthermore, the researcher explored whether this relationship was moderated by students' gender, academic area, and retrospective perception of their collaborative learning skills. Social-cognitive learning theory and Astin's involvement theory were used as conceptual frameworks to guide this study. Astin's input-environment-output college impact model served as a theoretical guide. Using an institutional cross-sectional data set, multiple regression analysis was utilized to examine these relationships. According to the results, the relationship between student-student interactions and graduating seniors' perceived collaborative learning skills was positive after controlling for the other independent variables in the study. Further results revealed that the relationship of student-student interactions and student-faculty interactions with the outcome variable was moderated by students' gender, academic area, and retrospective perception of their collaborative learning skill. The relationship between student-faculty interactions and the outcome variable was significantly weaker for male students, whereas the relationship between student-student interactions and the outcome variable was weaker for female student. The relationship between student-faculty interactions and the outcome variable was weaker for students in hard pure academic areas when compared to students in soft applied academic areas, while the opposite was observed for the relationship between student-student interactions and the outcome variable. The findings of the present study can be used to shape students' interactions with faculty and their peers with the awareness that these impact different types of students in different ways. / Ph. D.

The ability to find the location of a mobile user has become of utmost importance. The demands of first responders necessitates the ability to accurately identify the location of an individual who is calling for help. Their response times are directly influenced by the ability to locate the caller. Thus, applications such as Enhanced 911 and other location-based services warrant the ability to quickly and accurately calculate location. The FCC has also put in place a timeline for indoor location accuracy requirements that must be met by the mobile communications service providers. In order to meet these requirements, there are many means of performing indoor geolocation that require research; in this thesis two specific methods of identifying the location of a user will be investigated. In the first part, the indoor localization of a target, whose exact location is unknown, in a LTE network is studied. In this problem the time difference of arrival of the LTE uplink signals sent from the target to an observer are used as the means to estimate the target position. The two-dimensional location of a user is then estimated through the use of a nonlinear least-squares algorithm. To improve this approach, a cooperative localization technique in uplink LTE is proposed in which the User Equipment (UE) communicates with base stations as well as other handsets. Through simulated results it is shown that utilizing collaboration can improve location estimation and outperform non-collaborative localization. In the second part, the indoor localization of a target, focusing on its third dimension or elevation, is studied through the use of barometric pressure sensors in mobile handsets. Finding the third dimension of location, or the correct height above the ground level which equates to the floor in a building that a UE is on, cannot be performed with two-dimensional measurement models. For this problem, the pressure sensors are used to accurately find an immediate pressure measurement and allow for the altitude of a handset to be calculated. This altitude can be translated into an estimation for a specific floor of a building given the use of a ground floor pressure reference. Through simulation results it is then shown that the accuracy of third dimension or indoor-floor localization can be improved with the use of collaborative pressure sensors of other mobile handsets. / Master of Science

Yes / Alzheimer’s disease irrevocably challenges a person’s capacity to communicate with others. Earlier research on these challenges focused on the language disorders associated with the condition and situated language deficit solely in the limitations of a person’s cognitive and semantic impairments. This research falls short of gaining insight into the actual interactional experiences of a person with Alzheimer’s and their family. Drawing on a UK data set of 70 telephone calls recorded over a two-and-a-half year period (2006–2008) between one elderly woman affected by Alzheimer’s disease, and her daughter and son-in-law, this paper explores the role which communication (and its degeneration) plays in family relationships. Investigating these interactions, using a conversation analytic approach, reveals that there are clearly communicative difficulties, but closer inspection suggests that they arise due to the contingencies that are generated by the other’s contributions in the interaction. That being so, this paper marks a departure from the traditional focus on language level analysis and the assumption that deficits are intrinsic to the individual with Alzheimer’s, and instead focuses on the collaborative communicative challenges that arise in the interaction itself and which have a profound impact on people’s lives and relationships.

Recommender systems have become paramount to customize information access and reduce information overload. They serve multiple uses, ranging from suggesting products and artifacts (to consumers), to bringing people together by the connections induced by (similar) reactions to products and services. This thesis presents a graph-theoretic model that casts recommendation as a process of 'jumping connections' in a graph. In addition to emphasizing the social network aspect, this viewpoint provides a novel evaluation criterion for recommender systems. Algorithms for recommender systems are distinguished not in terms of predicted ratings of services/artifacts, but in terms of the combinations of people and artifacts that they bring together. We present an algorithmic framework drawn from random graph theory and outline an analysis for one particular form of jump called a 'hammock.' Experimental results on two datasets collected over the Internet demonstrate the validity of this approach. / Master of Science

This thesis explores stakeholder engagement in complex networked governance and adaptive management structures. It analyzes the adaptive capacity, multi-level learning, and stakeholder engagement and inclusion processes organizations engaged in transboundary environmental planning employ for effective governance. Over the last few decades, networked governance and adaptive management have become increasingly popular within natural resource management, while public demand for and expectations of stakeholder engagement within government funded programs has grown. There is a need to better understand networked governance arrangements' structures and strategies for local stakeholder engagement, and how these structures and strategies support inclusive determination and implementation of regional planning and funding priorities. Research for this project involved a qualitative study of local stakeholder engagement within the Chesapeake Bay Program using document analysis and semi-structured interviews of Bay Program staff, advisory committee members, and partners. This paper finds that inclusive stakeholder engagement, practiced in both episodic and institutionalized forms, is critical to the social learning and change required for successful natural resource management within regional partnerships. Networked governance arrangements can strategically employ engagement practices that create spaces for network and social learning and increase diversity through inclusion. Informal subnetworks play a key role in developing new engagement strategies (e.g., trusted sources) and preparing organizations for change (e.g., alternative decision-making methods). This research makes the following recommendations for stakeholder engagement: prioritize DEIJ in engagement design; identify engagement goals, values, and roles; strengthen networks to support diversity in participation and inclusion; create mechanisms to operationalize engagement learning; and regularly evaluate engagement practices. / Master of Urban and Regional Planning / This thesis explores stakeholder engagement in complex networked governance and adaptive management structures. It analyzes the adaptive capacity, multi-level learning, and stakeholder engagement and inclusion processes organizations engaged in transboundary environmental planning employ for effective governance. Over the last few decades, networked governance and adaptive management have become increasingly popular within natural resource management, while public demand for and expectations of stakeholder engagement within government funded programs has grown. There is a need to better understand networked governance arrangements' structures and strategies for local stakeholder engagement, and how these structures and strategies support inclusive determination and implementation of regional planning and funding priorities. Research for this project involved a qualitative study of local stakeholder engagement within the Chesapeake Bay Program using document analysis and semi-structured interviews of Bay Program staff, advisory committee members, and partners. This paper finds that inclusive stakeholder engagement, practiced in both episodic and institutionalized forms, is critical to the social learning and change required for successful natural resource management within regional partnerships. Networked governance arrangements can strategically employ engagement practices that create spaces for network and social learning and increase diversity through inclusion. Informal subnetworks play a key role in developing new engagement strategies (e.g., trusted sources) and preparing organizations for change (e.g., alternative decision-making methods). This research makes the following recommendations for stakeholder engagement: prioritize DEIJ in engagement design; identify engagement goals, values, and roles; strengthen networks to support diversity in participation and inclusion; create mechanisms to operationalize engagement learning; and regularly evaluate engagement practices.

Conference paper assignment---the task of assigning paper submissions to reviewers---is a key step in the management and smooth functioning of conferences. We study this problem as an application of recommender systems research. Besides the traditional goal of predicting `who likes what?', a conference management system must take into account reviewer capacity constraints, adequate numbers of reviews for papers, expertise modeling, conflicts of interest, and an overall distribution of assignments that balances reviewer preferences with conference objectives. Issues of modeling preferences and tastes in reviewing have traditionally been studied separately from the optimization of assignments. In this thesis, we present an integrated study of both aspects. First, due to the sparsity of data (relative to other recommender systems applications), we integrate multiple sources of information to learn reviewer/paper preference models, using methods commonly associated with merging content-based and collaborative filtering in the study of large recommender systems. Second, our models are evaluated not just in terms of prediction accuracy, but also in terms of end-assignment quality, and considering multiple evaluation criteria. Using a linear programming-based assignment optimization formulation, we show how our approach better explores the space of potential assignments to maximize the overall affinities of papers assigned to reviewers. Finally, we demonstrate encouraging results on real reviewer preference data gathered during the IEEE ICDM 2007 conference, a premier international data mining conference. Our research demonstrates that there are significant advantages to applying recommender system concepts to the conference paper assignment problem. / Master of Science

Technical interviews have become a popular method for recruiters in the tech industry to assess job candidates' proficiency in both soft skills and technical skills as programmers. However, these interviews can be stressful and frustrating for interviewees. One significant cause of the negative experience of technical interviews was the lack of feedback, making it difficult for job seekers to improve their performance progressively by participating in technical interviews. Although there are open platforms like Leetcode that allow job seekers to practice their technical proficiency, resources for conducting mock interviews to practice soft skills like communication are limited and costly to interviewees. To address this, we investigated how professional interviewers provide feedback if they were conducting a mock interview and the difficulties they face when interviewing job seekers by running mock interviews between software engineers and job seekers. With the insights from the formative studies, we developed a new system for technical interviews aiming to help interviewers conduct technical interviews with less cognitive load and provide context-rich feedback. An evaluation study on the usability of using our system to conduct technical interviews further revealed the unresolved cognitive loads of interviewers, underscoring the requirements for further improvement to facilitate easier interview processes and enable peer-to-peer interview practices. / Master of Science / Technical interview is a common method used by tech companies to evaluate job candidates. During these interviews, candidates are asked to solve algorithm problems and explain their thought processes while coding. Running these interviews, recruiters can assess the job candidate's ability to write codes and solve problems in a limited time. At the same time, the requirements for interviewees to talk aloud help interviewers evaluate their communication and collaboration skills. Although technical interviews enable employers to assess job applicants from multiple perspectives, they also introduce interviewees to stress and anxiety. Among the many complaints about technical interviews, one significant difficulty of the interview process is the lack of feedback from interviewers. As a result, it is difficult for interviewees to improve progressively by participating in technical interviews repeatedly. Although there are platforms for interviewees to practice code writing, resources like mock interviews with actual interviewers for job seekers to practice communication skills are costly and rare. Our study investigated how professional programmers run mock technical interviews and provide feedback when required. The mock interview observations helped us understand the standard procedure and common practices of how practitioners run these interviews. At the same time, we concluded the potential cause of cognitive loads and difficulties for interviewers to run such interviews. To answer the difficulties of conducting technical interviews, we developed a new system that enabled interviewers to conduct technical interviews with less cognitive load and provide enriched feedback. After rerunning mock interviews with our system, we noted that while some features in our system helped make the interview process easier, additional cognitive loads are unresolved. Looking into these difficulties, we suggested several directions for future studies to improve our design to enable an easier interview process for interviewers and support interview rehearsals between job seekers.

Yes / (1) Present deprescribing experiences of patients living with frailty, their informal carers and healthcare professionals; (2) interpret whether their experiences are reflective of person-centred/collaborative care; (3) complement our findings with existing evidence to present a model for person-centred deprescribing for patients living with frailty, based on a previous collaborative care model. Qualitative design in English primary care (general practice). Semi-structured interviews were undertaken immediately post-deprescribing and 5/6 weeks later with nine patients aged 65+ living with frailty and three informal carers of patients living with frailty. Fourteen primary care professionals with experience in deprescribing were also interviewed. In total, 38 interviews were conducted. A two-staged approach to data analysis was undertaken. Three themes were developed: attitudes, beliefs and understanding of medicines management and responsibility; attributes of a collaborative, person-centred deprescribing consultation; organisational factors to support person-centred deprescribing. Based on these findings and complementary to existing evidence, we offer a model for person-centred deprescribing for patients living with frailty. Previous models of deprescribing for patients living with frailty while, of value, do not consider the contextual factors that govern the implementation and success of models in practice. In this paper, we propose a novel person-centred model for deprescribing for people living with frailty, based on our own empirical findings, and the wider evidence base. / This research was funded by the National Institute for Health and Care Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR Yorkshire and Humber PSTRC).

This paper addresses the crucial need for comprehensive guidance in repertoire selection and technical development for pre-collegiate collaborative pianists. By compiling an annotated repertoire list, this research aims to assist teachers and pianists in navigating the developmental stages of collaborative piano work. The guide focuses on establishing foundational skills and techniques necessary for effective collaboration with various instruments, emphasizing the pianist's role as a musical partner. Drawing from the University Interscholastic League (UIL) list, the repertoire choices span a range of musical styles and periods, ensuring a balanced progression of difficulty. The paper talks about essential collaborative piano techniques, including hand and wrist position, physical coordination, listening, voicing, balance, pedaling, and breathing, providing a comprehensive overview to aid in successful ensemble performances. Each piece in the repertoire list is accompanied by detailed performance notes, addressing both pianistic and ensemble considerations. Additionally, the difficulty levels of the compositions are assessed with reference to established pedagogical literature. By offering a structured approach to repertoire selection and technical development, this annotated guide serves as a valuable resource for pre-collegiate collaborative pianists and their instructors, facilitating their growth and proficiency in collaborative music-making.