11 resultados para self adaptive modified teacher learning optimization (SAMTLO) algorithm
em Digital Commons at Florida International University
The development, application, and implications of a strategy for reflective learning from experience
Resumo:
The problem on which this study focused was individuals' reduced capacity to respond to change and to engage in innovative learning when their reflective learning skills are limited. In this study, the preceding problem was addressed by two primary questions: To what degree can mastery of a strategy for reflective learning be facilitated as a part of an academic curriculum for professional practitioners? What impact will mastery of this strategy have on the learning style and adaptive flexibility of adult learners? The focus of the study was a direct application of human resource development technology in the professional preparation of teachers. The background of the problem in light of changing global paradigms and educational action orientations was outlined and a review of the literature was provided. Roots of thought for two key concepts (i.e., learning to learn from experience and meaningful reflection in learning) were traced. Reflective perspectives from the work of eight researchers were compared. A meta-model of learning from experience drawn from the literature served as a conceptual framework for the study. A strategy for reflective learning developed from this meta-model was taught to 109 teachers-in-training at Florida International University in Miami, Florida. Kolb's Adaptive Style Inventory and Learning Style Inventory were administered to the treatment group and to two control groups taught by the same professor. Three research questions and fourteen hypotheses guided data analysis. Qualitative review of 1565 personal documents generated by the treatment group indicated that 77 students demonstrated "double-loop" learning, going beyond previously established limits to perception, understanding, or action. The mean score for depth of reflection indicated "single-loop" learning with "reflection-in-action" present. The change in the mean score for depth of reflection from the beginning to end of the study was statistically significant (p $<$.05). On quantitative measures of adaptive flexibility and learning style, with two exceptions, there were no significant differences noted between treatment and control groups on pre-test to post-test differences and on post-test mean scores adjusted for pre-test responses and demographic variables. Conclusions were drawn regarding treatment, instrumentation, and application of the strategy and the meta-model. Implications of the strategy and the meta-model for research, for education, for human resource development, for professional practice, and for personal growth were suggested. Qualitative training materials and Kolb's instruments were provided in the appendices.
Resumo:
The role of support from teachers on the academic and emotional adjustment of a ethnically and economically diverse sample of adolescents was examined. Analyses were conducted on data from a larger study examining social networks across the transition to junior high school. Participants in the current study included 694 African-American, Hispanic-American and European-American students in grades 6 and 8 from public elementary schools in South Florida. Some of these schools are located in economically distressed areas and some are in middle income areas. Children were interviewed, and information on teacher social support resources, school stressors, risk and academic and emotional adjustment was obtained. Several significant findings emerged from the analyses. First, overall teacher support was a significant predictor of a wide range of academic and emotional adjustment outcomes. Second, teacher support compensated for low peer support on teacher rated behavior problems. Third, teacher support interacted with school stress to predict depressed affect and self esteem. Fourth, teacher support interacted with low ecological risk conditions to predict feelings of loneliness. ^
Resumo:
The purpose of this study was to describe the experiences of five educators participating in a teacher-initiated learning community that valued practical teacher knowledge. Connelly and Clandinin (2000) argued that practical teacher knowledge grew out of experience through interaction in the professional knowledge landscape. Collaboration that promoted teacher learning was the foundation to effective school change (Wood, 1997). This teacher-initiated learning community consisted of members who had equal status and collaborated by participating in discourse on curriculum and instruction. The collegiality of the community fostered teacher professionalism that improved practice and benefited the school. This study focused on the following research questions: (1) What was the experience of these five educators in this learning community? (2) What did these five individuals understand about the nature of practical teacher knowledge? (3) According to the participants, what was the relationship between teacher empowerment and effective school change? ^ The participants were chosen because each voluntarily attended this teacher-initiated learning community. Each participant answered questions regarding the experience during three semi-structured tape-recorded interviews. The interviews were transcribed, and significant statements of meaning were extracted. Using a triangulation of ideas that were common to at least three of the participants ensured the trustworthiness of the analysis. These statements were combined to describe what was experienced and how the participants described their experience. The emerging themes were the characteristics of and the relationships, methods, conditions, and environment for the teachers. The teachers described how a knowledge base of practical teacher knowledge was gained as a spirit of camaraderie developed. The freedom that the teachers experienced to collaborate and learn fostered new classroom practice that affected school change as student interaction and productivity increased. ^ The qualitative analysis of this study provided a description of a learning community that valued practical teacher knowledge and fostered professional development. This description was important to educational stakeholders because it demonstrated how practical teacher knowledge was gained during the teachers' daily work. By sharing every day experiences, the teacher talk generated collaboration and accountability that the participants felt improved practice and fostered a safe, productive learning environment for students. ^
Resumo:
The purpose of this thesis was to identify the optimal design parameters for a jet nozzle which obtains a local maximum shear stress while maximizing the average shear stress on the floor of a fluid filled system. This research examined how geometric parameters of a jet nozzle, such as the nozzle's angle, height, and orifice, influence the shear stress created on the bottom surface of a tank. Simulations were run using a Computational Fluid Dynamics (CFD) software package to determine shear stress values for a parameterized geometric domain including the jet nozzle. A response surface was created based on the shear stress values obtained from 112 simulated designs. A multi-objective optimization software utilized the response surface to generate designs with the best combination of parameters to achieve maximum shear stress and maximum average shear stress. The optimal configuration of parameters achieved larger shear stress values over a commercially available design.
Resumo:
To date, hospitality management educators have struggled to modify generic software or adapt vendor-designed industry systems as a means of bringing hospitality information systems to the classroom. Specially- designed computer-based courseware can enhance learning while extending the boundaries of the traditional hospitality classroom. The author discusses the relevance of this software to the hospitality curriculum.
Resumo:
The current study was designed to explore the salience of parent and peer support in middle childhood and early adolescence across two time periods as indicated by measures of achievement (grade point average (GPA), Stanford Achievement Test (SAT) scores and teacher rated school adaptation) and well-being (loneliness, depression, self-concept and teacher-rated internalizing behaviors). ^ Participants were part of an initial study on social network relations and school adaptation in middle childhood and early adolescence. Participants at Time 1 (in the spring of 1997) included 782 children in grades 4 and 6 of eight lower and middle income public elementary schools. Participants (N = 694) were reinterviewed two years later in the spring of 1999 (Time 2). ^ Multivariate analyses of variance (MANOVA) were used to investigate the change in salience of parent and peer support from Time 1 to Time 2. In addition, Tukey-HSD (Honestly Significant Difference) post hoc tests were used to test the significance of the differences among the means of four support categories: (1) low parent-low friend, (2) low parent-high friend, (3) high parent-low friend, and (4) high parent-high friend. ^ Compensatory effects were observed for loneliness and self-concept at Time 1, as well as for SAT scores, self-concept and overall achievement at Time 2. Results were consistent with existing findings that suggest a competitive model of parent/peer influence on achievement during adolescence. This study affirms the need for a more contextual approach to research examining competing and compensatory effects on adolescent development. ^
Resumo:
Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.
Resumo:
Many classical as well as modern optimization techniques exist. One such modern method belonging to the field of swarm intelligence is termed ant colony optimization. This relatively new concept in optimization involves the use of artificial ants and is based on real ant behavior inspired by the way ants search for food. In this thesis, a novel ant colony optimization technique for continuous domains was developed. The goal was to provide improvements in computing time and robustness when compared to other optimization algorithms. Optimization function spaces can have extreme topologies and are therefore difficult to optimize. The proposed method effectively searched the domain and solved difficult single-objective optimization problems. The developed algorithm was run for numerous classic test cases for both single and multi-objective problems. The results demonstrate that the method is robust, stable, and that the number of objective function evaluations is comparable to other optimization algorithms.
Resumo:
Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^
Resumo:
A fundamental goal of education is to equip students with self-regulatory capabilities that enable them to educate themselves. Self directedness not only contributes to success in formal instruction but also promotes lifelong learning (Bandura, 1997). The area of research on self-regulated learning is well grounded within the framework of psychological literature attributed to motivation, metacognition, strategy use and learning. This study explored past research and established the purpose of teaching students to self-regulate their learning and highlighted the fact that teachers are expected to assume a major role in the learning process. A student reflective writing journal activity was sustained for a period of two semesters in two fourth-grade mathematics classrooms. The reflective writing journal was analyzed in search of identifying strategies reported by students. Research questions were analyzed using descriptive statistics, frequency counts, cross-tabs and chi-square analyses. ^ Results based on student-use of the journals and teacher interviews indicated that the use of a reflective writing journal does promote self-regulated learning strategies to the extent which the student is engaged in the journaling process. Those students identified as highly self-regulated learners on the basis of their strategy use, were shown to consistently claim to learn math “as well or better than planned” on a weekly basis. Furthermore, good self-regulators were able to recognize specific strategies that helped them do well and change their strategies across time based on the planned learning objectives. The perspectives of the participating teachers were examined in order to establish the context in which the students were working. The effect of “planned change” and/or the resistance to change as established in previous research, from the teachers point of view, was also explored. The analysis of the journal data did establish a significant difference between students who utilized homework as a strategy. ^ Based on the journals and interviews, this study finds that the systematic use of metacognitive, motivational and/or learning strategies can have a positive effect on student's responsiveness to their learning environment. Furthermore, it reflects that teaching students “how to learn” can be a vital part of the effectiveness of any curriculum. ^
Resumo:
This thesis describes the development of an adaptive control algorithm for Computerized Numerical Control (CNC) machines implemented in a multi-axis motion control board based on the TMS320C31 DSP chip. The adaptive process involves two stages: Plant Modeling and Inverse Control Application. The first stage builds a non-recursive model of the CNC system (plant) using the Least-Mean-Square (LMS) algorithm. The second stage consists of the definition of a recursive structure (the controller) that implements an inverse model of the plant by using the coefficients of the model in an algorithm called Forward-Time Calculation (FTC). In this way, when the inverse controller is implemented in series with the plant, it will pre-compensate for the modification that the original plant introduces in the input signal. The performance of this solution was verified at three different levels: Software simulation, implementation in a set of isolated motor-encoder pairs and implementation in a real CNC machine. The use of the adaptive inverse controller effectively improved the step response of the system in all three levels. In the simulation, an ideal response was obtained. In the motor-encoder test, the rise time was reduced by as much as 80%, without overshoot, in some cases. Even with the larger mass of the actual CNC machine, decrease of the rise time and elimination of the overshoot were obtained in most cases. These results lead to the conclusion that the adaptive inverse controller is a viable approach to position control in CNC machinery.