Assessing the effectiveness of the internationalization process in Higher Education Institutions: A case study of Florida International University

The purpose of this study was to examine a Higher Education Institution’s (HEI) process of internationalization. The theoretical model developed by Van Dijk and Miejer (1997) was used to review Florida International University (FIU)’s policy, support, and implementation dimensions and determine its position on the Internationalization Cube, and assess how FIU’s international activities fit into its different organizational processes. In addition, the study sought to shed light on student and faculty attitudes toward internationalization. Qualitative and quantitative data were collected from examining organizational documents, interviews, descriptive data on FIU’s international activities using the International Dimension Index, and the Student and Faculty Survey on Internationalization. FIU’s international activities results were analyzed in relation to a panel of experts’ item relevancy index. The Likert-type survey scales’ frequencies and percentages were calculated as well as Spearman Rho correlations between the survey’s three scales and demographic and experiences variables. The study found that FIU is located on position six of a possible eight positions on the Van Dijk and Meijer Internationalization Cube with the following characteristics: Priority Policy, One-Sided Support, and Structured Implementation toward internationalization. The analysis of FIU’s results on international activities showed that FIU exhibits all the activities considered to be strong indicators of internationalization but for position seven placement special attention is needed in the areas of foreign language study, international students, study abroad, faculty movement and involvement in international projects. The survey indicated students and faculty rated the Benefits of Internationalization highly but didn’t perceive strong institutional Support for Internationalization. Faculty age and offshore programs participation; student gender, race/ethnicity and class status; and for both, study abroad and knowledge of students travel grant had significant positive correlations with student and faculty attitudes. The study concluded that an association exists between FIU’s position on the Internationalization Cube and its international activities. Recommendations for policy, implementation, and future studies were made. It was concluded that advancing FIU’s position on the Cube will require adjustments in FIU’s policy, support and implementation dimensions. Differences in student and faculty views toward internationalization should be taken into account when planning internationalization efforts.

Evaluating the effects of initial participation in the group therapy process

Although the effectiveness of group therapy has been highlighted, the underlying mechanisms involved in the group process have been under studied. The purpose of this study is twofold. First, the current study utilized an outcome mediation model to examine whether initial level of participation in the intervention (Control/No intervention, non-participatory, participatory) predicted change in Identity Conflict Resolution (IDCR), Personal Expressiveness (PE) and Informational Identity Style (INFO) at posttest, and Internalizing (INT) and Externalizing (EXT) behaviors at post and follow-up assessment. Secondly, the current study examined whether relationships between variables varied as a result of group differences in initial participation. The study utilized an archival sample of 234 high school students, ages 14 to 18, who participated in the Changing Lives Program of the Youth Development Project (YDP) since 2003. Structural equation modeling (SEM) was used to examine differences in direct effects as a result of initial participation on an outcome meditational model. To further analyze this model, SEM was utilized to conduct a multi-group solution to examine whether group differences based on level of initial participation in the variables^

Developing a process to create and validate an instrument assessing student attainment of competencies at an intercultural university in Mexico

This study took place at one of the intercultural universities (IUs) of Mexico that serve primarily indigenous students. The IUs are pioneers in higher education despite their numerous challenges (Bertely, 1998; Dietz, 2008; Pineda & Landorf, 2010; Schmelkes, 2009). To overcome educational inequalities among their students (Ahuja, Berumen, Casillas, Crispín, Delgado et al., 2004; Schmelkes, 2009), the IUs have embraced performance-based assessment (PBA; Casillas & Santini, 2006). PBA allows a shared model of power and control related to learning and evaluation (Anderson, 1998). While conducting a review on PBA strategies of the IUs, the researcher did not find a PBA instrument with valid and reliable estimates. The purpose of this study was to develop a process to create a PBA instrument, an analytic general rubric, with acceptable validity and reliability estimates to assess students' attainment of competencies in one of the IU's majors, Intercultural Development Management. The Human Capabilities Approach (HCA) was the theoretical framework and a sequential mixed method (Creswell, 2003; Teddlie & Tashakkori, 2009) was the research design. IU participants created a rubric during two focus groups, and seven Spanish-speaking professors in Mexico and the US piloted using students' research projects. The evidence that demonstrates the attainment of competencies at the IU is a complex set of actual, potential and/or desired performances or achievements, also conceptualized as "functional capabilities" (FCs; Walker, 2008), that can be used to develop a rubric. Results indicate that the rubric's validity and reliability estimates reached acceptable estimates of 80% agreement, surpassing minimum requirements (Newman, Newman, & Newman, 2011). Implications for practice involve the use of PBA within a formative assessment framework, and dynamic inclusion of constituencies. Recommendations for further research include introducing this study's instrument-development process to other IUs, conducting parallel mixed design studies exploring the intersection between HCA and assessment, and conducting a case study exploring assessment in intercultural settings. Education articulated through the HCA empowers students (Unterhalter & Brighouse, 2007; Walker, 2008). This study aimed to contribute to the quality of student learning assessment at the IUs by providing a participatory process to develop a PBA instrument.

A developmental education program model for high -risk minority baccalaureate nursing students

The purpose of this study was to define and describe a Developmental Education Program Model for high-risk minority baccalaureate nursing students based upon perceived needs determined by nursing students and nursing faculty. The research examined differences between Black and Non-Black nursing students in level of importance of concerns and issues related to academic, financial, psycho-social and personal areas of student life; faculty perceptions of the differences between Black and Non-Black nursing students in the level of importance of concerns and issues related to academic, financial, psycho-social and personal areas of student life; and the difference between Black and Non-Black nursing faculty perceptions of level of importance of issues and concerns of academic, financial, psycho-social, and personal areas for Black nursing students. In this study two data collection methods were used, questionnaire and interview. The questionnaire was completed by all students and faculty. Black baccalaureate nursing students and nursing faculty were interviewed. The most significant differences were seen in the category of Personal Issues. Student identified concerns and issues related to both academic and health problems. Faculty identified the greatest differences in Academic Issues. The framework for the model which evolved out of the data uses needs from: (1) a whole person perspective (outcome oriented needs); (2) a programmatic perspective (input oriented needs); and (3) learning domain perspective (process oriented needs). ^

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

Women-led community development organizations (CDOs) in Miami-Dade County: A model of community development efforts impacting the economic security of women

Recent studies on the economic status of women in Miami-Dade County (MDC) reveal an alarming rate of economic insecurity and significant obstacles for women to achieve economic security. Consistent barriers to women's economic security affect not only the health and wellbeing of women and their families, but also economic prospects for the community. A key study reveals in Miami-Dade County, "Thirty-nine percent of single female-headed families with at least one child are living at or below the federal poverty level" and "over half of working women do not earn adequate income to cover their basic necessities" (Brion 2009, 1). Moreover, conventional measures of poverty do not adequately capture women's struggles to support themselves and their families, nor do they document the numbers of women seeking basic self-sufficiency. Even though there is lack of accurate data on women in the county, which is a critical problem, there is also a dearth of social science research on existing efforts to enhance women's economic security in Miami-Dade County. My research contributes to closing the information gap by examining the characteristics and strategies of women-led community development organizations (CDOs) in MDC, working to address women's economic insecurity. The research is informed by a framework developed by Marilyn Gittell, who pioneered an approach to study women-led CDOs in the United States. On the basis of research in nine U.S. cities, she concluded that women-led groups increased community participation and "by creating community networks and civic action, they represent a model for community development efforts" (Gittell, et al. 2000, 123). My study documents the strategies and networks of women-led CDOs in MDC that prioritize women's economic security. Their strategies are especially important during these times of economic recession and government reductions in funding towards social services. The focus of the research is women-led CDOs that work to improve social services access, economic opportunity, civic participation and capacity, and women's rights. Although many women-led CDOs prioritize building social infrastructures that promote change, inequalities in economic and political status for women without economic security remain a challenge (Young 2004). My research supports previous studies by Gittell, et al., finding that women-led CDOs in Miami-Dade County have key characteristics of a model of community development efforts that use networking and collaboration to strengthen their broad, integrated approach. The resulting community partnerships, coupled with participation by constituents in the development process, build a foundation to influence policy decisions for social change. In addition, my findings show that women-led CDOs in Miami-Dade County have a major focus on alleviating poverty and economic insecurity, particularly that of women. Finally, it was found that a majority of the five organizations network transnationally, using lessons learned to inform their work of expanding the agency of their constituents and placing the economic empowerment of women as central in the process of family and community development.

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Development of test-based wind-driven rain intrusion model for hurricane-induced building interior and contents damage

Major portion of hurricane-induced economic loss originates from damages to building structures. The damages on building structures are typically grouped into three main categories: exterior, interior, and contents damage. Although the latter two types of damages, in most cases, cause more than 50% of the total loss, little has been done to investigate the physical damage process and unveil the interdependence of interior damage parameters. Building interior and contents damages are mainly due to wind-driven rain (WDR) intrusion through building envelope defects, breaches, and other functional openings. The limitation of research works and subsequent knowledge gaps, are in most part due to the complexity of damage phenomena during hurricanes and lack of established measurement methodologies to quantify rainwater intrusion. This dissertation focuses on devising methodologies for large-scale experimental simulation of tropical cyclone WDR and measurements of rainwater intrusion to acquire benchmark test-based data for the development of hurricane-induced building interior and contents damage model. Target WDR parameters derived from tropical cyclone rainfall data were used to simulate the WDR characteristics at the Wall of Wind (WOW) facility. The proposed WDR simulation methodology presents detailed procedures for selection of type and number of nozzles formulated based on tropical cyclone WDR study. The simulated WDR was later used to experimentally investigate the mechanisms of rainwater deposition/intrusion in buildings. Test-based dataset of two rainwater intrusion parameters that quantify the distribution of direct impinging raindrops and surface runoff rainwater over building surface — rain admittance factor (RAF) and surface runoff coefficient (SRC), respectively —were developed using common shapes of low-rise buildings. The dataset was applied to a newly formulated WDR estimation model to predict the volume of rainwater ingress through envelope openings such as wall and roof deck breaches and window sill cracks. The validation of the new model using experimental data indicated reasonable estimation of rainwater ingress through envelope defects and breaches during tropical cyclones. The WDR estimation model and experimental dataset of WDR parameters developed in this dissertation work can be used to enhance the prediction capabilities of existing interior damage models such as the Florida Public Hurricane Loss Model (FPHLM).^

A generic model of execution for synthesizing domain-specific models

Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

UV-induced melanoma mouse model dependent on endothelin 3 over-expression

Melanoma is one of the most aggressive types of cancer. It originates from the transformation of melanocytes present in the epidermal/dermal junction of the human skin. It is commonly accepted that melanomagenesis is influenced by the interaction of environmental factors, genetic factors, as well as tumor-host interactions. DNA photoproducts induced by UV radiation are, in normal cells, repaired by the nucleotide excision repair (NER) pathway. The prominent role of NER in cancer resistance is well exemplified by patients with Xeroderma Pigmentosum (XP). This disease results from mutations in the components of the NER pathway, such as XPA and XPC proteins. In humans, NER pathway disruption leads to the development of skin cancers, including melanoma. Similar to humans afflicted with XP, Xpa and Xpc deficient mice show high sensibility to UV light, leading to skin cancer development, except melanoma. The Endothelin 3 (Edn3) signaling pathway is essential for proliferation, survival and migration of melanocyte precursor cells. Excessive production of Edn3 leads to the accumulation of large numbers of melanocytes in the mouse skin, where they are not normally found. In humans, Edn3 signaling pathway has also been implicated in melanoma progression and its metastatic potential. The goal of this study was the development of the first UV-induced melanoma mouse model dependent on the over-expression of Edn3 in the skin. The UV-induced melanoma mouse model reported here is distinguishable from all previous published models by two features: melanocytes are not transformed a priori and melanomagenesis arises only upon neonatal UV exposure. In this model, melanomagenesis depends on the presence of Edn3 in the skin. Disruption of the NER pathway due to the lack of Xpa or Xpc proteins was not essential for melanomagenesis; however, it enhanced melanoma penetrance and decreased melanoma latency after one single neonatal erythemal UV dose. Exposure to a second dose of UV at six weeks of age did not change time of appearance or penetrance of melanomas in this mouse model. Thus, a combination of neonatal UV exposure with excessive Edn3 in the tumor microenvironment is sufficient for melanomagenesis in mice; furthermore, NER deficiency exacerbates this process.^

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.