Human-machine teaming aims to meld human cognitive strengths and the unique capabilities of smart machines to create intelligent teams adaptive to rapidly changing circumstances. One major contributor to the problem of human-machine teaming is a lack of communication skills on the part of the machine. The primary objective of this research is focused on a machine’s interruption timings or when a machine should share and communicate information with human teammates within human-machine teaming interactions. Previous work addresses interruption timings from the perspective of single human, multitasking and multiple human, single task interactions. The primary aim of this dissertation is to augment this area by approaching the same problem from the perspective of a multiple human, multitasking interaction. The proposed machine is the Collaborative Communication Interruption Management System (C-CIMS) which is tasked with leveraging speech information from a human-human task and making inferences on when to interrupt with information related to an orthogonal human-machine task. This study and previous literature both suggest monitoring task boundaries and engagement as candidate moments of interruptibility within multiple human, multitasking interactions. The goal then becomes designing an intermediate step between human teammate communication and points of interruptibility within these interactions. The proposed intermediate step is the mapping of low-level speech information such as prosodic and lexical information onto higher constructs indicative of interruptibility. C-CIMS is composed of a Task Boundary Prosody Model, a Task Boundary Topic Model, and finally a Task Engagement Topic Model. Each of these components are evaluated separately in terms of how they perform within two different simulated human-machine teaming scenarios and the speed vs. accuracy tradeoffs as well as other limitations of each module. Overall the Task Boundary Prosody Model is tractable within a real-time system because of the low-latency in processing prosodic information, but is less accurate at predicting task boundaries even within human-machine interactions with simple dialogue. Conversely, the Task Boundary and Task Engagement Topic Models do well inferring task boundaries and engagement respectively, but are intractable in a real-time system because of the bottleneck in producing automatic speech recognition transcriptions to make interruption decisions. The overall contribution of this work is a novel approach to predicting interruptibility within human-machine teams by modeling higher constructs indicative of interruptibility using low-level speech information.

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With increased globalization, Internet connectivity, and competitive economic conditions, global organizations are increasingly recognizing the importance of effective global collaborations. Hence, there is a need to extend the use of psychological teaming strategies for domestic team-formations to also accommodate teams that are globally distributed. Previous research efforts have investigated psychological factors for design creativity and effective global collaboration; however, few have addressed these factors concurrently. The focus of this dissertation is therefore on the formation of creative design teams in a globally distributed and culturally diverse environment. This dissertation provides a theoretical foundation for teaming methodologies for globally distributed and culturally diverse teams. It also presents a new global collaborative and creative design team formation method: the Global Design Team Formation (GDTF) method. This is a novel computational method that uses potential team members' psychological and cultural traits, in an attempt to form effective teams that are psychologically and culturally cohesive. The method is based upon and merges Jung's theory with the theoretical frameworks of (a) Teamology and (b) Global Leadership and Organizational Behavior Effectiveness (GLOBE), and it provides a quantitative representation scheme combining scores from the Meyers-Briggs Test Indicator (MBTI) and the Kogut and Singh index (KS index) using the GLOBE dataset. The GDTF method has been applied to three populations. The control group consisted of 42 three-person teams in a sophomore-level mechanical engineering design course at a US university, to validate the Teamology framework, which is based on Jung's and Belbin's theories. The GDTF method was then applied to two international teaming situations: a globally team-taught course on engineering design at the senior and graduate levels with 8 globally distributed teams across the US, Germany, Mexico, and China; and 23 dyadic teams of US undergraduate students performing automotive research with German graduate students in Germany. Results of this research shows that psychologically balanced and cohesive teams provide improved design creativity, and that this performance difference can be predicted using the team members' psychological traits. Statistical analysis indicates that creativity in engineering design depends on the presence of Te, Fe, Fi, and Si psychological traits, in decreasing order of importance, within the teams. The importance of these traits remains dominant in global teams, though global diversity negatively impacts team cohesiveness and hence their effectiveness, though not their creativity. / Ph. D.

The successful delivery of large complex infrastructure projects continues to challenge the civil engineering profession, with a predominance of projects delivered late and over budget. Many researchers have investigated methods and means of improving the less-than-satisfactory record of the execution of these projects. One recent research direction suggests that improvements in project delivery may not be realized until the project setting is understood from the as-lived perspective of the participants. Following this direction, the research described in this dissertation explores the personal and interpersonal dynamics operating within projects, treating them as complex social processes. The social dimensions explored in this study involve team leaders and staff engineers in a matriced organization handling a large urban design-build infrastructure project. The interactions among the participants within and across units and levels had both positive and negative impacts. The data for this exploratory case study comes from semi-structured interviews and online surveys collected at three points over eleven months when the project was in the design phase. Interviews were conducted with a limited number of individuals; the survey was collected from the larger engineering organization. From the interview data, issues which impacted project delivery were identified as the relationship with supervision, the availability of information, an understanding of the larger project context, and the response to project constraints. The survey data was used primarily to understand the social dimensions affecting two engineering disciplines, one that performed well and one that performed poorly. Issues that aligned with the performance differences included frequency of contact with supervision, the ability to make decisions, and effective use of time available to complete design tasks. Data from the two modes of investigation demonstrated strong triangulation. Recommendations for both academia and industry are provided. / Ph. D.

This qualitative study addressed an intersection in which the application of the medical model to educational disabilities and its implications for educational labeling of students interacted with the professional enculturation of clinical social workers. Employed as clinicians in programs administered in a large south eastern school district in the United States, five social workers served elementary students labeled Emotionally/Behaviorally Disabled (EBD) through federally authorized provisions for special education related services. This study used grounded theory methods to discover and analyze the social workers' underlying assumptions, values, and patterns of practice with regard to ethical and guild issues, roles and responsibilities, and bases of knowledge. The study found that participants interpreted and applied a knowledge base grounded in the normative aspects of social work. Their preparation made it possible to compete for licensure (LCSW) and assume roles as professional helpers but did not provide all the tools they needed to carry out their work as clinicians with students in EBD programs. Secondly, it found that ambiguities regarding ethics, guild issues, and roles emerged with regard to acting as helping professionals in an integrated professional setting. Each practitioner exercised certain latitude to respond as needed to challenges which varied from site to site. Finally, the findings reflected how the clinicians have situated themselves in the face of the demands of documentation procedures and of participation in meetings endemic to special education.

Schools in Queensland, Australia, are undergoing inclusive education reform, following the report of the Ministerial Taskforce on Inclusive Education (Students with Disabilities) in 2004. The State government’s responses to the taskforce report emphasise a commitment to social justice and equity so that all students can be included in ways that enable them to achieve their potential. Teacher aides are employed in schools as ancillary staff to support students with disabilities and learning difficulties. Their support roles in schools are emerging within an educational context in which assumptions about disability, difference and inclusion of students with disabilities and learning difficulties are changing. It is important to acknowledge teacher aides as support practitioners, and to understand their roles in relation to the inclusion of students with disabilities and learning difficulties as inclusive education reform continues. This study used a phenomenological approach to explore the lived experiences of teacher aides as they supported students with disabilities and learning difficulties in primary schools. Four key insights into the support roles of teacher aides in primary schools in Brisbane, Queensland emerged from the study: 1) teacher aides develop empathetic relationships with students that contribute significantly to the students’ sense of belonging within school communities; 2) lack of clear definition of roles and responsibilities for teacher aides has detrimental effects on inclusion of students; 3) collaborative planning and implementation of classroom learning and socialisation programs enhances inclusion; and 4) teacher aides learn about supporting students while on-the-job, and in consultation and collaboration with other members of the students’ support networks.

abstract: Humans and robots need to work together as a team to accomplish certain shared goals due to the limitations of current robot capabilities. Human assistance is required to accomplish the tasks as human capabilities are often better suited for certain tasks and they complement robot capabilities in many situations. Given the necessity of human-robot teams, it has been long assumed that for the robotic agent to be an effective team member, it must be equipped with automated planning technologies that helps in achieving the goals that have been delegated to it by their human teammates as well as in deducing its own goal to proactively support its human counterpart by inferring their goals. However there has not been any systematic evaluation on the accuracy of this claim. In my thesis, I perform human factors analysis on effectiveness of such automated planning technologies for remote human-robot teaming. In the first part of my study, I perform an investigation on effectiveness of automated planning in remote human-robot teaming scenarios. In the second part of my study, I perform an investigation on effectiveness of a proactive robot assistant in remote human-robot teaming scenarios. Both investigations are conducted in a simulated urban search and rescue (USAR) scenario where the human-robot teams are deployed during early phases of an emergency response to explore all areas of the disaster scene. I evaluate through both the studies, how effective is automated planning technology in helping the human-robot teams move closer to human-human teams. I utilize both objective measures (like accuracy and time spent on primary and secondary tasks, Robot Attention Demand, etc.) and a set of subjective Likert-scale questions (on situation awareness, immediacy etc.) to investigate the trade-offs between different types of remote human-robot teams. The results from both the studies seem to suggest that intelligent robots with automated planning capability and proactive support ability is welcomed in general. / Dissertation/Thesis / Masters Thesis Computer Science 2015

PurposeThe purpose with thisstudyis to find out how preschool teachers describe their individual and collaborative work in relation to handling and preventing the children’s conflicts. Further the objective is to discover therole of the individual pedagogue, and the teacher team have in conflict situations. To discover the relevance of the teacher teamin the children’s conflicts,the studywill also evaluate how the collaborative work within the teamcan be made possible. Research methodThe data has been collected by interviews to research how the preschool teachers describe the individual, and collaborative work with conflicts, and how they perceive the work with conflicts.ResultsThe study shows that the preschool teachers find thatit’s important to handlethe conflicts that emerge among the children. Although the collaborative work within the teacher teams varied, the teachers still found it of importance of handlingthe conflicts within the group. According to the preschool teachers, the reason that the collaborative work is crucial is because a lack of organization between the pedagogues, results in inconsistent methods for handling the children’s conflicts. An organized teacher team is also important because the collaboration allow the children to develop and learn from their conflicts.

abstract: Despite the prevalence of teams in complex sociotechnical systems, current approaches to understanding workload tend to focus on the individual operator. However, research suggests that team workload has emergent properties and is not necessarily equivalent to the aggregate of individual workload. Assessment of communications provides a means of examining aspects of team workload in highly interdependent teams. This thesis set out to explore how communications are associated with team workload and performance under high task demand in all-human and human–autonomy teams in a command and control task. A social network analysis approach was used to analyze the communications of 30 different teams, each with three members operating in a command and control task environment of over a series of five missions. Teams were assigned to conditions differentiated by their composition with either a naïve participant, a trained confederate, or a synthetic agent in the pilot role. Social network analysis measures of centralization and intensity were used to assess differences in communications between team types and under different levels of demand, and relationships between communication measures, performance, and workload distributions were also examined. Results indicated that indegree centralization was greater in the all-human control teams than in the other team types, but degree centrality standard deviation and intensity were greatest in teams with a highly trained experimenter pilot. In all three team types, the intensity of communications and degree centrality standard deviation appeared to decrease during the high demand mission, but indegree and outdegree centralization did not. Higher communication intensity was associated with more efficient target processing and more successful target photos per mission, but a clear relationship between measures of performance and decentralization of communications was not found. / Dissertation/Thesis / Masters Thesis Human Systems Engineering 2020

This thesis work examines how people accomplish annotation tasks (i.e., labelling data based on content) while working with an artificial intelligence (AI) system. When people and AI systems work together to accomplish a task, this is referred to as human-AI teaming. This study reports on the results of an interview and observation study of 15 volunteers from the Washington DC area as the volunteers annotated Twitter messages (tweets) about the COVID-19 pandemic. During the interviews, researchers observed the volunteers as they annotated tweets, noting any needs, frustrations, or confusion that the volunteers expressed about the task itself or when working with the AI. This research provides the following contributions: 1) an examination of annotation work in a human-AI teaming context; 2) the HATA (human-AI teaming annotation) framework with five key factors that affect the way people annotate while working with AI systems--background, task interpretation, training, fatigue, and the annotation system; 3) a set of questions that will help guide users of the HATA framework as they create or assess their own human-AI annotation teams; 4) design recommendations that will give future researchers, designers, and developers guidance for how to create a better environment for annotators to work with AI; and 5) HATA framework implications when it is put into practice.