9 resultados para leave to withdraw admissions

em Digital Commons at Florida International University


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During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

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During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

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Research on the adoption of innovations by individuals has been criticized for focusing on various factors that lead to the adoption or rejection of an innovation while ignoring important aspects of the dynamic process that takes place. Theoretical process-based models hypothesize that individuals go through consecutive stages of information gathering and decision making but do not clearly explain the mechanisms that cause an individual to leave one stage and enter the next one. Research on the dynamics of the adoption process have lacked a structurally formal and quantitative description of the process. ^ This dissertation addresses the adoption process of technological innovations from a Systems Theory perspective and assumes that individuals roam through different, not necessarily consecutive, states, determined by the levels of quantifiable state variables. It is proposed that different levels of these state variables determine the state in which potential adopters are. Various events that alter the levels of these variables can cause individuals to migrate into different states. ^ It was believed that Systems Theory could provide the required infrastructure to model the innovation adoption process, particularly applied to information technologies, in a formal, structured fashion. This dissertation assumed that an individual progressing through an adoption process could be considered a system, where the occurrence of different events affect the system's overall behavior and ultimately the adoption outcome. The research effort aimed at identifying the various states of such system and the significant events that could lead the system from one state to another. By mapping these attributes onto an “innovation adoption state space” the adoption process could be fully modeled and used to assess the status, history, and possible outcomes of a specific adoption process. ^ A group of Executive MBA students were observed as they adopted Internet-based technological innovations. The data collected were used to identify clusters in the values of the state variables and consequently define significant system states. Additionally, events were identified across the student sample that systematically moved the system from one state to another. The compilation of identified states and change-related events enabled the definition of an innovation adoption state-space model. ^

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The subject of this dissertation is the nature of the environmental transformations, both symbolic and physical, that took place in Colombia between 1850 and 1930. This period begins with the attempt by the Colombian elite to leave behind colonial ties, overcome economic disorganization, and link Colombia to the international market. These efforts were part of a general project to “civilize” this tropical country. The period closes with the transition toward an industrialization and urbanization process led by the Colombian state during the 1930s. ^ Frequently, environmental studies as an academic field are dominated by biological concerns. However, most environmental thinking accepts their interdisciplinary nature. Under this framework not only spatial but also symbolic concerns are key elements in understanding environmental transformations. ^ This study finds that despite several attempts to transform the Colombian landscape physically, most of the substantive changes were localized and circumscribed to the Andean region. Other changes were mainly symbolic. This dissertation thus uses the Amazon as one of several regions that did not experience significant changes in the forest canopy. While highlanders originally dreamed of the Amazon as an untapped El Dorado, their failed attempts to exploit the region caused them to imagine it as a nightmarish “green hell”. ^ This dissertation concentrates on three pairs of concepts: tropicality/civilization, landscape/territory, and symbolic/material changes. It presents both a general vision of Colombia and case studies of three regions: Cundinamarca, and Cauca Valley are used to compare with the Amazon region that is developed at length. Whereas mainstream Colombian histories have either fixated on the Andean highlands or, in a relegated second place, on the Caribbean region, this dissertation attempts to significantly contribute to the historiography of Colombia by focusing on the largely neglected Amazonian region. ^ To understand imageries about Colombia's landscape, the dissertation relies on travel writings, chorographic descriptions and maps. It also makes uses legal documents and other published primary sources, including literary pieces and memoirs. ^

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Despite increased Federal, state, and local efforts in the United States to improve outcomes among young adults who emancipate from foster care, low educational achievement and attainment continue to characterize this vulnerable subpopulation. Approximately 50% of foster children do not obtain a high school diploma or a general equivalency diploma (GED). Only about 20% of former foster children enroll in college, compared to 60% of youth not in foster care. The purpose of this study was to explore, describe and explain the perceptions of college students who had lived in foster care regarding the external and internal influences that impacted their academic achievement and attainment. Interviews with a purposefully selected sample of 24 Florida college students were conducted; transcripts were coded and analyzed thematically. Findings included that participants experienced a particular set of external and internal influences at school, in foster care settings, and in the community. External influences include interactions with (a) multiple non-relative guardians and case workers, (b) relatives, especially siblings, (c) mentors, (d) teachers and school administrators, and (e) school counselors. Internal influences include the barriers of anger and bad behavior and a newly identified set of internal characteristics, called success strengths by the researcher, that promote academic achievement and college attainment. Implications are as follows: (a) Future theory on academic achievement concerning foster youth should reflect the importance of the affective aspect of school interactions. (b) Policy should mandate awareness training for educators, social workers, and other adults who work with former foster youth to increase professionals' awareness of the barriers, supports and success strengths that impact the academic lives of children and youth in foster care. (c) Adult educators and human resource development professionals should develop and implement appropriate new education and training materials and interventions. Future research may include a similar interview with former foster youth who graduated from college and with foster youth who leave school before graduating. Finally, a study with a nationally representative sample of college enrolled former foster children should be conducted to determine the relative importance of the barriers, supports and success strengths identified in this study.

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The Inupiaq Tribe resides north of the Arctic Circle in northwestern Alaska. The people are characterized by their continued dependence on harvested fish, game and plants, known as a subsistence lifestyle (Lee 2000:35-45). Many are suggesting that they leave their historical home and move to urban communities, places believed to be more comfortable as they age. Tribal Elders disagree and have stated, "Elders need to be near the river where they were raised" (Branch 2005:1). The research questions focused on differences that location had on four groups of variables: nutrition parameters, community support, physical functioning and health. A total of 101 Inupiaq Elders ≥ 50 years were surveyed: 52 from two rural villages, and 49 in Anchorage. Location did not influence energy intake or intake of protein; levels of nutrition risk and food insecurity; all had similar rates between the two groups. Both rural and urban Elders reported few limitations of ADLs and IADLs. Self-reported general health scores (SF-12.v2 GH) were also similar by location. Differences were found with rural Elders reporting higher physical functioning summary scores (SF-12.v2 PCS), higher mental health scores (SF-12.v2 MH), higher vitality and less pain even though the rural mean ages were five years older than the urban Elders. Traditional food customs appear to support the overall health and well being of the rural Inupiaq Elders as demonstrated by higher intakes of Native foods, stronger food sharing networks and higher family activity scores than did urban Elders. The rural community appeared to foster continued physical activity. It has been said that when Elders are in the rural setting they are near "people they know" and it is a place "where they can get their Native food" (NRC 2005). These factors appear to be important as Inupiaq Elders age, as rural Inupiaq Elders fared as well or better than Inupiaq Elders in terms of diet, mental and physical health.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

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ABSTRACT The purpose of this study is to investigate the extended leave programs offered by lodging companies in the United States and to suggest a model that could be used in the lodging industry. This model mirrors successful sabbatical leave programs offered by leading companies featured in the annual report, 100 Best Companies to Work For (from this point forward, referred to as 100 Best), published on-line by Fortune Magazine, 2013 (CNN, 2013). While extended leave programs are not entirely lacking in the industry, our research discovered that such leave systems are rare. According to the companies investigated that offer a sabbatical leave program, this benefit offers highly sought after time away from work for top performing employees at the management and higher levels. The benefits reported include happier employees who have increased feelings of company loyalty, job satisfaction, and overall better attitudes. The sponsoring companies stated that those who take part in such leave contribute at a higher level upon their return, bringing fresh ideas and a renewed commitment to the company’s success.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.