Perceptions of beginning teachers in Florida regarding their preparation as it relates to the Florida Essential Generic Competencies

The purpose of the study is to investigate how beginning teachers in the state of Florida perceive their preparation to demonstrate the 27 Florida Essential Generic Competencies.^ The basic research question of this study was: How do beginning teachers perceive their level of preparation regarding their implementation of the Florida Essential Generic Competencies? This study identified and categorized the perceived degree of preparation for each of the competencies. Also, elementary, middle, and high school beginning teachers were compared to find significant differences and similarities in their perception of their preparation. A comparison was also done for graduates from in-state versus out-of-state and private versus public institutions.^ A survey developed in collaboration with the Department of Education, Florida State University, members of the Professional Orientation Program (POP) Coordinators, and the Project Director of Program Review in the College of Education at the University of South Florida, was sent to 5,076 beginning teachers. A total of 1,995 returned the survey in February of 1993. The Multivariate Analysis of Variance (MANOVA) procedure was used (Alpha =.05). Statistical analysis of the data involved a comparison of the different groups of beginning teachers by school level and kind of graduating institutions. The dependent variables analyzed were the responses to all items representing the generic competencies.^ The study identified and categorized the degree of preparation for each competency. The competencies receiving the lowest ratings for degree of preparation were: integrate computers in instruction; manage situations involving child abuse and/or neglect; severe emotional stress; alcohol and drug abuse.^ The Wilkes lambda and the Hotellings multivariate tests of significance were used to examine the differences among the groups. The competency items were further analyzed by a univariate F test. Results indicated that: (1) significant differences were found in nine competency items in which elementary teachers felt better prepared than middle and high school beginning teachers, (2) graduates from a Florida teacher education program felt they were better prepared in demonstrating the competencies than those from out-of-state schools, and (3) no significant difference was found in the perceptions of those who graduated from public versus private institutions.^ Based on the findings of this study, the following recommendations are made: (1) Florida's institutions responsible for teacher preparation programs need to focus on those competencies receiving the lowest ratings, (2) Districts should provide an orientation program for out-of-state beginning teachers, and (3) The survey instrument should be used annually to evaluate teacher education programs. ^

Characteristics of effective clinical and theory instructors as perceived by LPN to RN versus generic students in an associate degree nursing program

The purpose of this study was to compare the characteristics of effective clinical and theory instructors as perceived by LPN/RN versus generic students in an associate degree nursing program.^ Data were collected from 508 students during the 1996-7 academic year from three NLN accredited associate degree nursing programs. The researcher developed instrument consisted of three parts: (a) Whitehead Characteristics of Effective Clinical Instructor Rating Scale, (b) Whitehead Characteristics of Effective Theory Instructor Rating Scale, and (c) Demographic Data Sheet. The items were listed under five major categories identified in the review of the literature: (a) interpersonal relationships, (b) personality traits, (c) teaching practices, (d) knowledge and experience, and (e) evaluation procedures. The instrument was administered to LPN/RN students in their first semester and to generic students in the third semester of an associate degree nursing program.^ Data was analyzed using a one factor mutivariate analysis of variance (MANOVA). Further t tests were carried out to explore for possible differences between type of student and by group. Crosstabulations of the demographic data were analyzed.^ There were no significant differences found between the LPN/RN versus generic students on their perceptions of either effective theory or effective clinical instructor characteristics. There were significant differences between groups on several of the individual items. There was no significant interaction between group and ethnicity or group and age on the five major categories for either of the two instruments. There was a significant main effect of ethnicity on several of the individual items.^ The differences between the means and standard deviations on both instruments were small, suggesting that all of the characteristics listed for effective theory and clinical instructors were important to both groups of students. Effective teaching behaviors, as indicated on the survey instruments, should be taught to students in graduate teacher education programs. These behaviors should also be discussed by faculty coordinators supervising adjunct faculty. Nursing educators in associate degree nursing programs should understand theories of adult learning and implement instructional strategies to enhance minority student success. ^

Predictors of first semester attrition and their relation to retention of generic associate degree nursing students

In community college nursing programs the high rate of attrition was a major concern to faculty and administrators. Since first semester attrition could lead to permanent loss of students and low retention in nursing programs, it was important to identify at-risk students early and develop proactive approaches to assist them to be successful. The goal of nursing programs was to graduate students who were eligible to take the national council licensing examination (RN). This was especially important during a time of critical shortage in the nursing workforce. ^ This study took place at a large, multi-campus community college, and used Tinto's (1975) Student Integration Model of persistence as the framework. A correlational study was conducted to determine whether the independent variables, past academic achievement, English proficiency, achievement tendency, weekly hours of employment and financial resources, could discriminate between the two grade groups, pass and not pass. Establishing the relationship between the selected variables and successful course completion might be used to reduce attrition and improve retention. Three research instruments were used to collect data. A Demographic Information form developed by the researcher was used to obtain academic data, the research questionnaire Measure of Achieving Tendency measured achievement motivation, and the Test of Adult Basic Education (TABE), Form 8, Level A, Tests 1, 4, and 5 measured the level of English proficiency. The Department of Nursing academic policy, requiring a minimum course grade of “C” or better was used to determine the final course outcome. A stepwise discriminant analysis procedure indicated that college language level and pre-semester grade point average were significant predictors of final course outcome. ^ Based on the findings of the study recommendations focused on assessing students' English proficiency prior to admission into the nursing program, an intensive remediation plan in language comprehension for at-risk students, and the selection of alternate textbooks and readings that more closely matched the English proficiency level of the students. A pilot study should be conducted to investigate the benefit of raising the admission grade point average. ^

Achievement of generic baccalaureate student nurses using computer -assisted instruction simulations during a nursing review course

The use of computer assisted instruction (CAI) simulations as an instructional strategy provides nursing students with a critical thinking approach for evaluating risks and benefits and choosing correct alternatives in "safe" patient care situations. It was hypothesized that using CAI simulations during an upper level nursing review course would have a positive effect on the students' posttest scores. Subjects (n = 36) were senior nursing students enrolled in a nursing review course in an undergraduate baccalaureate program. A limitation of the study was the small sample size. The study employed a modified group experimental design using the t test for independent samples. The group who received the CAI simulations during the physiological system review demonstrated a significant increase (p $<$.01) in the posttest score mean when compared to the lecture-discussion group score mean. There was no significant difference between high and low clinical grade point average (GPA) students in the CAI and lecture-discussion groups and their score means on the posttest. However, score mean differences of the low clinical GPA students showed a greater increase for the CAI group than the lecture-discussion group. There was no significant difference between the groups in their system content subscore means on the exit examination completed three weeks later. It was concluded that CAI simulations are as effective as lecture-discussion in assisting upper level students to process information for clinical decision making. CAI simulations can be considered as an instructional strategy to supplement or replace lecture content during a review course, allowing more efficient use of faculty time. It is recommended that the study be repeated using a larger sample size. Further investigations are recommended in comparing the effectiveness of computer software formats and various instructional strategies for other learning situations and student populations. ^

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.^

Perceptions of beginning teachers in Florida regarding their preparation as it relates to the Florida essential generic competencies

The purpose of the study is to investigate how beginning teachers in the state of Florida perceive their preparation to demonstrate the 27 Florida Essential Generic Competencies. The basic research question of this study was: How do beginning teachers perceive their level of preparation regarding their implementation of the Florida Essential Generic Competencies? This study identified and categorized the perceived degree of preparation for each of the competencies. Also, elementary, middle, and high school beginning teachers were compared to find significant differences and similarities in their perception of their preparation. A comparison was also done for graduates from in-state versus out-of-state and private versus public institutions. A survey developed in collaboration with the Department of Education, Florida State University, members of the Professional Orientation Program (POP) Coordinators, and the Project Director of Program Review in the College of Education at the University of South Florida, was sent to 5,076 beginning teachers. A total of 1,995 returned the survey in February of 1993. The Multivariate Analysis of Variance (MANOVA) procedure was used (Alpha = .05). Statistical analysis of the data involved a comparison of the different groups of beginning teachers by school level and kind of graduating institutions. The dependent variables analyzed were the responses to all items representing the generic competencies. The study identified and categorized the degree of preparation for each competency. The competencies receiving the lowest ratings for degree of preparation were: integrate computers in instruction; manage situations involving child abuse and/or neglect; severe emotional stress; alcohol and drug abuse. The Wilkes lambda and the Hotellings multivariate tests of significance were used to examine the differences among the groups. The competency items were further analyzed by a univariate F test. Results indicated that: (1) significant differences were found in nine competency items in which elementary teachers felt better prepared than middle and high school beginning teachers, (2) graduates from a Florida teacher education program felt they were better prepared in demonstrating the competencies than those from out-of-state schools, and (3) no significant difference was found in the perceptions of those who graduated from public versus private institutions. Based on the findings of this study, the following recommendations are made: (1) Florida's institutions responsible for teacher preparation programs need to focus on those competencies receiving the lowest ratings, (2) Districts should provide an orientation program for out-of-state beginning teachers, and (3) The survey instrument should be used annually to evaluate teacher education programs.

A Generic Model of Execution for Synthesizing Domain-Specific Models

Software engineering researchers are challenged to provide increasingly more pow- erful levels of abstractions to address the rising complexity inherent in software solu- tions. One new development paradigm that places models as abstraction at the fore- front 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 sub- sequently producing a generic model of execution (GMoE) from the remaining appli- cation logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis com- ponent 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.