M.Ed.

Organizations need to develop innovations to meet emerging problems and challenges due to increasing global competition, customer expectations, or market changes. Responding to these challenges requires employees to create solutions within their organizations, such as new products or processes. While some research has found crucial roles of individual faculty in the innovation process, less is known about how individual educators (i.e., university faculty and clinical practitioners) work across knowledge and organizational boundaries.The purpose of this case study on team innovative work behavior (TIWB) in higher education was to learn more about which team learning behaviors (TLBs) and team innovative work behaviors (TIWBs) were exhibited by a university-based cross-boundary work team to understand how these complex organizations can leverage learning toward practice improvement. The purposefully selected sample was composed of an 11 member California-based work team consisting of 5 faculty members from a redesigning public university, 4 senior administrators from partnering public school districts, and 2 faculty members from a partnering mentor program. The primary data collection method was in depth critical incident (CI) interviews. Supportive methods included a pre-interview questionnaire, field observations, document and artifact review, and a group interview. The data were coded and analyzed first by research question, and then findings were organized thematically in alignment with three analytic categories based on the study’s conceptual framework. The research revealed that the team exhibited several TLBs and one TIWB throughout the redesign process. The team’s capacity for learning and innovating was strongly influenced by the organizational conditions that brought the team together as well as the team’s leadership and facilitation. While few of the team members were able to articulate their own learning and practice changes explicitly, they did reflect on their learning in the context of task completion and goal achievement. Recommendations are offered for university and district practitioners, and for further research, including: (1) identifying a team leader with both positional and reputational authority, (2) selecting a team based on existing relationships and shared commitment to change, (3) using evidence to challenge existing assumptions, and (4) aligning activities to organizational and environmental forces.

The research on cooperative learning has been conducted in terms of student achievement but little is known of how training in and use of cooperative learning affects teachers. The central purpose of this study was to examine the association between training in cooperative learning and teacher job satisfaction, with special attention to the subsets of collegiality and efficacy. A second purpose was to examine how levels of job satisfaction, efficacy, and collegiality vary as a function of the following training variables: (a) setting, (b) amount of use, (c) kind of training, (d) preparation for implementation, and (e) opportunity for skill maintenance. The research was conducted via questionnaire with 129 teachers responding, which was a response rate of 71%. The questionnaire gathered data about training variables and included a 30-item Job satisfaction Survey which had subscales: 10 questions on collegiality, 15 on efficacy, and 5 on overall job satisfaction. The validity of the Job satisfaction Survey was established by pilot testing, by expert review of the questions, and by the use of an established survey as a bench mark for comparison. The research analysis involved examination of mean scores on the Job satisfaction Survey and ANOVA technique to examine the significance of variables in training and levels of job satisfaction as well as the subsets of collegiality and efficacy. Although the research did not reveal a significant relationship between training in cooperative learning and teacher job satisfaction, a significant relationship was found between several training variables and levels of satisfaction as well as collegiality and efficacy. The training variables found to be significantly associated with teacher efficacy were these: (a) use of cooperative learning at the level of seven or more times a week, (b) small group sharing and problem solving sessions for participants during training, (c) discussion with colleagues to maintain skills, and (d) the use of principal observation and feedback. The training variables found to be associated with collegiality were as follows: (a) the use of five different opportunities to maintain skills as opposed to three or fewer and (b) the use of peer coaching and feedback. Training variables associated with overall job satisfaction were: (a) small group sharing and problem solving sessions during training, (b) the use of five skill maintenance opportunities as opposed to three or fewer, and ((c) the use of peer coaching and feedback. Given the results of this study, staff development specialists should structure training to include these significant variables as sources of collegiality and efficacy as well as overall job satisfaction of teachers.

Thesis (M.Ed.)--University of Hong Kong, 1983. / Includes bibliographical references (leaf 51-53). Also available in print.

This dissertation explores the experiences of nineteen individuals assigned to six collaborative Massive Open Online Course (MOOC) development teams across four university sites. Based on an analysis of these semi-structured interviews and process artifacts, findings reveal that collaborative MOOC development teams are composed of members with cross-campus affiliations who possess distinct knowledge, skills, and attitudes that—when combined with specific resources—facilitate the interdependence needed to effectively collaborate on MOOC curriculum. This research suggests that process behaviors that cultivate empathy and expedite trust among members positively mediate states that emerge from the diversity of power and affiliations commonly found on MOOC teams. Further, these process behaviors and emergent states are found to have an impact beyond the MOOC itself, on faculty behaviors in the classroom, staff behaviors with regards to future curriculum collaborations, and institutional acceptance and promotion of cross-campus collaborations with regards to online learning and collaborative curriculum development. While existing MOOC research has focused on the historical, pedagogical, and technical aspects of MOOC curriculum development, this dissertation contributes to a better understanding of how MOOC teams effectively collaborate to develop curriculum that leverages existing scholarship. This research therefore has implications for advancing scholarship on effective teams, collaborative curriculum design, online learning, and MOOCs, as well as informing practical recommendations for stakeholders engaged in strategically composing and working within collaborative curriculum development teams.

Fast pace of change in the business of technology is the reality of many organizations today. The software development industry is one example where this nature is prominent. Companies need to adapt in ways that eases the persistence against change from external forces. Companies need to turn into Learning Organizations as these help people and organizations embrace change. Two key components of the Learning Organization are the teams, as they are considered to be the fundamental units of organizations, and managers, as they have the biggest impact on facilitating learning in the organization. Therefore, this study has investigated how managers could act to create conditions for encouraging team learning of a software development company to become a Learning Organization.   This has been done by conducting a case study at the company Ericsson in Kista, Sweden, who is market leaders within the software development industry. The case design consisted of a two phase method that included both a quantitative and qualitative data collection method.   The results indicate that Ericsson could be classified as a Learning Organization and in addition display promising characteristics when it comes to having team learning capabilities. Furthermore, the findings suggest that in order for managers to encourage team learning they should take on a coaching and supporting role to understand the need of the teams; challenge the status quo; empower teams through giving them mandate; allocate time for learning as an integral part of the daily work; and reward learning in teams.   The findings of this study have implications both in a theoretical aspect and a sustainability aspect. From the theoretical aspect, the findings provide with further empirical data in a field that is currently dominated by theoretical literature. Furthermore, the findings display a practical example of how managers of a market leading company with promising characteristics of team learning capabilities have acted to create such conditions. From a sustainability aspect, the results of this study give firms a sustainable competitive advantage through increased business performance, healthy labor conditions that are a result of healthy team dynamics and possible encouragement to future attention towards emphasis on environmental aspects.

Thesis (Ph. D.)--University of Tennessee, Knoxville, 2007. / Title from title page screen (viewed on Sept. 19, 2008). Thesis advisor: Schuyler Huck. Vita. Includes bibliographical references.

published_or_final_version / Education / Master / Master of Science in Information Technology in Education

Widespread unexplained variations in clinical practices and patient outcomes, together with rapidly growing availability of data, suggest major opportunities for improving the quality of medical care. One way that healthcare practitioners try to do that is by participating in organized healthcare quality improvement collaboratives (QICs). In QICs, teams of practitioners from different hospitals exchange information on clinical practices, with the aim of improving health outcomes at their own institutions. However, what works in one hospital may not work in others with different local contexts, due to non-linear interactions among various demographics, treatments, and practices. I.e., the clinical landscape is a complex socio-technical system that is difficult to search. In this dissertation we develop methods for analysis and modeling of complex systems, and apply them to the problem of healthcare improvement. Searching clinical landscapes is a multi-objective dynamic problem, as hospitals simultaneously optimize for multiple patient outcomes. We first discuss a general method we developed for finding which changes in features may be associated with various changes in outcomes at different points in time with different delays in affect. This method correctly inferred interactions on synthetic data, however the complexity and incompleteness of the real hospital dataset available to us limited the usefulness of this approach. We then discuss an agent-based model (ABM) of QICs to show that teams comprising individuals from similar institutions outperform those from more diverse institutions, under nearly all conditions, and that this advantage increases with the complexity of the landscape and the level of noise in assessing performance. We present data from a network of real hospitals that provides encouraging evidence of a high degree of similarity in clinical practices among hospitals working together in QIC teams. Based on model outcomes, we propose a secure virtual collaboration system that would allow hospitals to efficiently identify potentially better practices in use at other institutions similar to theirs, without any institutions having to sacrifice the privacy of their own data. To model the search for quality improvement in clinical fitness landscapes, we need benchmark landscapes with tunable feature interactions. NK landscapes have been the classic benchmarks for modeling landscapes with epistatic interactions, but the ruggedness is only tunable in discrete jumps. Walsh polynomials are more finely tunable than NK landscapes, but are only defined on binary alphabets and, in general, have unknown global maximum and minimum. We define a different subset of interaction models that we dub as NM landscapes. NM landscapes are shown to have smoothly tunable ruggedness and difficulty and known location and value of global maxima. With additional constraints, we can also determine the location and value of the global minima. The proposed NM landscapes can be used with alphabets of any arity, from binary to real-valued, without changing the complexity of the landscape. NM landscapes are thus useful models for simulating clinical landscapes with binary or real decision variables and varying number of interactions. NM landscapes permit proper normalization of fitnesses so that search results can be fairly averaged over different random landscapes with the same parameters, and fairly compared between landscapes with different parameters. In future work we plan to use NM landscapes as benchmarks for testing various algorithms that can discover epistatic interactions in real world datasets.

Thesis (D. Ed.)--University of Oregon, 2001. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 211-216). Also available for download via the World Wide Web; free to University of Oregon users.