Instructional change through collaboration and reflection

The purpose of this study was to investigate the effectiveness of the Facilitator-Collaborative-Reflective Model, a strategic plan for changing teachers' practices and beliefs, on a selected group of middle school teachers. This model of staff development training was based on Corey's (1953) Cooperative-Action-Research Model and Anders and Richardson (1994) Collaborative-Reflective Model. It supports the notion that earning a teachers' commitment to change by focusing on collaboration, reflection and the normative-re-educative process aids in altering teachers' beliefs and practices especially crucial to the change process. The year-long training provided for reflection, inquiry, and learning that was useful to teachers as they pursued their goals with their students. The lead teacher, as a change agent and transformational leader, assisted in this commitment to change by improving the teachers' self-concepts as they slowly changed. The collaborative and receptive environment of the staff development fostered acceptance and stimulation of ideas.^ Given the collaborative nature of the change process, qualitative research methods were used in the investigation. The research process was based on Stufflebeam's Context, Input, Process and Product (CIPP) Evaluation Model (Madaus, Scriven & Stufflebeam, 1983). This allowed for all three factors of the staff development model to be evaluated. The case studies and focus group were effective in discerning any actual change in practices or beliefs.^ The findings of the qualitative evaluation, consisting of a baseline survey, case studies, questionnaire and modified focus group interviews, concluded that all of the teachers were strongly influenced by the intervention model which was the subject of this study. From this evaluation, three distinct indicators were looked at to determine if any change in the teachers' practices and beliefs emerged: (1) change in practice and belief, (2) reflective feedback and (3) collaborative reflection. These indicators were common throughout the teacher responses thus substantiating the infusion of the Facilitator-Collaborative-Reflective Model at the school level for effective staff development. ^

Hospitality Managers as Caretakers and Change Agents: A Reconceptualization of the Position

The unit manager in the hospitality organization is presented as a caretaker and a change agent in the organization, a caretaker in maintaining and nurturing the culture of the organization and a change agent in assisting the employees in the acceptance and demonstration of the desired image of the organization. The author reviews the traditional role of the manager and presents a reconceptualization of the position.

Profile of planning: A study of a three-year project on the implementation of collaborative library media programs

The implementation of collaborative planning and teaching models in ten flexibly scheduled elementary and middle school library media centers was studied to determine which factors facilitated the collaborative planning process and to learn what occurs when library media specialists (LMSs) and classroom teachers (CTs) plan together. In this qualitative study, 61 principals, CTs, and LMSs were interviewed on a range of topics including the principal's role, school climate, the value of team planning, the importance of information literacy instruction, and the ideal learning environment. Other data sources were observations, videotapes of planning sessions, and documents. This three-year school reform effort was funded by the Library Power Project to improve library programs, to encourage collaborative planning, and to increase curricular integration of information literacy skills instruction. ^ The findings included a description of typical planning sessions and the identification of several major factors which impacted the success of collaborative planning: the individuals involved, school climate, time for planning, the organization of the school, the facility and collection, and training. Of these factors, the characteristics and actions of the people involved were most critical to the implementation of the innovation. The LMS was the pivotal player and, in the views of CTs, principals, and LMSs themselves, must be knowledgeable about curriculum, the library collection, and instructional design and delivery; must be open and welcoming to CTs and use good interpersonal skills; and must be committed to information literacy instruction and willing to act as a change agent. The support of the principal was vital; in schools with successful programs, the principal served as an advocate for collaborative planning and information literacy instruction, provided financial support for the library program including clerical staff, and arranged for LMSs and CTs to have time during the school day to plan together. ^ CTs involved in positive planning partnerships with LMSs were flexible, were open to change, used a variety of instructional materials, expected students to be actively involved in their own learning, and were willing to team teach with LMSs. Most CTs planning with LMSs made lesson plans in advance and preferred to plan with others. Also, most CTs in this study planned with grade level or departmental groups, which expedited the delivery of information literacy instruction and the effective use of planning time. ^ Implications of the findings of this research project were discussed for individual schools, for school districts, and for colleges and universities training LMSs, CTs, and administrators. Suggestions for additional research were also included. ^

The winds of change? Exploring political effects of Hurricane Andrew

Before dawn on August 24, 1992, Hurricane Andrew smashed into south Florida, particularly southern Dade County, and soon become the costliest natural disaster in U.S. history. Andrew's impacts quickly overwhelmed local and state emergency response capabilities and eventually required major federal assistance, including regular military units. While the social and economic impacts of Hurricane Andrew are relatively well researched, much less attention has been given to its possible political effects. ^ Focusing on incumbent officeholders at three levels (municipal, state legislative, and statewide) who stood for reelection after Hurricane Andrew, this study seeks to determine whether they experienced any political effects from Andrew. That is, this study explores the possible interaction between the famous “incumbency advantage” and an “extreme event,” in this case a natural disaster. The specific foci were (1) campaigns and campaigning (a research process that included 43 personal interviews), and (2) election results before and after the event. ^ Given well-documented response problems, the working hypothesis was that incumbents experienced largely negative political fallout from the disaster. The null hypothesis was that incumbents saw no net political effects, but the reverse hypothesis was also considered: incumbents benefited politically from the event. ^ In the end, this study found that although the election process was physically disrupted, especially in south Dade County, the disaster largely reinforced the incumbency advantage. More specifically, the aftermath of Hurricane Andrew allowed most incumbent officeholders to (1) enhance constituency service, (2) associate themselves with the flow of external assistance, (3) achieve major personal visibility and media coverage, and yet (4) appear non-political or at least above normal politics. Overall, this combination allowed incumbents to very effectively “campaign without campaigning,” a point borne out by post-Andrew election results. ^

An agent-based model of team coordination and performance

This research is based on the premises that teams can be designed to optimize its performance, and appropriate team coordination is a significant factor to team outcome performance. Contingency theory argues that the effectiveness of a team depends on the right fit of the team design factors to the particular job at hand. Therefore, organizations need computational tools capable of predict the performance of different configurations of teams. This research created an agent-based model of teams called the Team Coordination Model (TCM). The TCM estimates the coordination load and performance of a team, based on its composition, coordination mechanisms, and job’s structural characteristics. The TCM can be used to determine the team’s design characteristics that most likely lead the team to achieve optimal performance. The TCM is implemented as an agent-based discrete-event simulation application built using JAVA and Cybele Pro agent architecture. The model implements the effect of individual team design factors on team processes, but the resulting performance emerges from the behavior of the agents. These team member agents use decision making, and explicit and implicit mechanisms to coordinate the job. The model validation included the comparison of the TCM’s results with statistics from a real team and with the results predicted by the team performance literature. An illustrative 26-1 fractional factorial experimental design demonstrates the application of the simulation model to the design of a team. The results from the ANOVA analysis have been used to recommend the combination of levels of the experimental factors that optimize the completion time for a team that runs sailboats races. This research main contribution to the team modeling literature is a model capable of simulating teams working on complex job environments. The TCM implements a stochastic job structure model capable of capturing some of the complexity not capture by current models. In a stochastic job structure, the tasks required to complete the job change during the team execution of the job. This research proposed three new types of dependencies between tasks required to model a job as a stochastic structure. These dependencies are conditional sequential, single-conditional sequential, and the merge dependencies.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

Managing small-scale commercial fisheries for adaptive capacity: Insights from dynamic social-ecological drivers of change in Monterey Bay

Globally, small-scale fisheries (SSFs) are driven by climate, governance, and market factors of social-ecological change, presenting both challenges and opportunities. The ability of small-scale fishermen and buyers to adapt to changing conditions allows participants to survive economic or environmental disturbances and to benefit from optimal conditions. This study presented here identifies key large-scale factors that drive SSFs in California to shift focus among targets and that dictate long-term trends in landings. We use Elinor Ostrom’s Social-Ecological System (SES) framework to apply an interdisciplinary approach when identifying potential factors and when understanding the complex dynamics of these fisheries. We analyzed the interactions among Monterey Bay SSFs over the past four decades since the passage of the Magnuson Stevens Fisheries Conservation and Management Act of 1976. In this region, the Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), and market squid (Loligo opalescens) fisheries comprise a tightly linked system where shifting focus among fisheries is a key element to adaptive capacity and reduced social and ecological vulnerability. Using a cluster analysis of landings, we identified four modes from 1974 to 2012 that were dominated by squid, sardine, anchovy, or lacked any dominance, enabling us to identify external drivers attributed to a change in fishery dominance during seven distinct transition points. Overall, we show that market and climate factors drive the transitions among dominance modes. Governance phases most dictated long-term trends in landings and are best viewed as a response to changes in perceived biomass and thus a proxy for biomass. Our findings suggest that globally, small-scale fishery managers should consider enabling shifts in effort among fisheries and retaining existing flexibility, as adaptive capacity is a critical determinant for social and ecological resilience.

The Prison System and the Media: How “Orange Is The New Black” Engages with the Prison as a Normalizing Agent

The purpose of this project is to ascertain the ways in which Orange is the New Black uses its platform to either complicate or reify narratives about the prison system, prisoners and their relationship to the state. This research uses the works of Giorgio Agamben, Colin Dayan, Michelle Alexander and Lisa Guenther to situate the ways the state uses the prison and social narratives about the prison to extend its control on certain populations beyond prison walls through police presence, parole, the war on drugs and prison fees. From that basis, this work argues that while Orange does challenge some narratives about race and sexuality, because of its reliance on “bad choices” as a humanizing trope and its reliance on certain racialized stereotypes for entertainment, the show ultimately does more to reify existing narratives that support state interests.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^