The purpose of this study was to explore the relationship between divergent thinking and Schmidt's schema theory of motor learning in a population of first year University physical education students. / Problem solving teaching methodology was used as the intervention program in this study and the main sources of data were the Torrance Tests of Creative Thinking and tests of Schmidt's schema theory designed by the researcher. Descriptive data were used to explain the intervention program. / A mixed model analysis of variance was used to compare the pre-test and post-test performance on Torrance Tests of Creative Thinking (TTCT), and the Pearson product-moment correlation technique was used to compare the results of the TTCT post-test and the Schmidt test. / Results showed minimal differences attributable to the intervention and no relationships between the two tests. Analysis of the descriptive data suggests several limitations to the intervention program and some suggestions for further research are offered.

This study examined Filipino mothers' problem solving on issues related to child feeding, using a dyadic, peer-help approach. The participants were mothers of children under 6 years of age from the town of Camaligan, in the southern Philippines, where malnutrition among children is prevalent. Two studies were conducted: one using a controlled experimental session and the second using a multi-session nutrition education format. In the first study, mothers were paired with a mutual or unilateral friend to discuss a feeding problem to which they initially gave similar solutions and one to which they gave different solutions. Their post-discussion solutions were better in quality and number than the pre-discussion solutions; also mothers paired with a mutual friend gave more and better finaL solutions to the initially-agreed problem than other mothers. Mothers' final solutions were more likely to come from their own than their partner's discussed solutions, suggesting that the partner's role was to facilitate the mother's own problem-solving process. In the second study, mothers paired with a mutual or unilateral friend were compared with an unpaired control group, after pacing themselves through four problem-based nutrition education sessions. For all three groups, mothers' nutrition knowledge and target child's weight-for-age and height-for-age improved from before to after the sessions. In conclusion, mothers show improvements in the number and quality of solutions they generate and the nutrition knowledge they acquire as a result of a problem-solving approach to nutrition education.

No description available.

This dissertation reports the results of a three-phase study on the learning of algebra. The first phase involved interviews with ten seventh graders (12 and 13 years of age) to uncover some of their pre-algebraic notions on equations and equation solving. Six of these novice subjects were kept on for the second phase: a two-month teaching experiment on equation solving which emphasized the symmetric procedure of performing the same operation on both sides. The pretest and two posttest interviews of the second phase included both equation-solving and equivalent-equations tasks. The third phase involved interviews with nine more-experienced algebra students from grades eight to eleven, to investigate their equation-solving procedures, errors, and methods of determining the equivalence of equation-pairs. Their approaches were compared with those of the novices on the same tasks. / The study uncovered two distinct paths followed in the learning of equation solving: one by those already predisposed toward inversing; the other by those with a predisposition toward using surface operations. The latter group was more receptive to the procedure taught during the teaching experiment. A relationship was found to exist between subjects' view of the literal term in equations and their preferred equation-solving method. Novices with an inversing preference applied learned principles to equivalence tasks, but not to equation solving. More-expert subjects relied on inversing for both. / Theoretical implications of these findings concern: the processes used in the early stages of learning a new domain, the modeling of the procedures used to determine equivalence, the relationship between errors and structural knowledge, and the representation of word problems by equations. Finally, the characterization of an arithmetic approach and an algebraic approach to the learning of equation solving is used to suggest a basis for a theory of algebra learning.

This study examined diagnostic problem solving and post-problem reflection in medical students, residents, and experts. Participants worked on three internal medicine cases from the computer-based learning environment, BioWorld. The analyses focused on general performance measures, problem solving operators and knowledge states, and post-problem reflection activities. Verbal protocol data was collected and examined using a coding scheme developed and implemented with the N-Vivo software. Students and residents differed in overall diagnostic accuracy, and significant differences were found in solution time and the number of utterances made for cases of varying difficulty. Differences in the use of operators and knowledge states are highlighted, although the groups were quite similar on many measures. The experts spent considerably more time working on case history information, consistently engaged in planning, and always generated the correct diagnosis (among others) in response to case history information. During post-problem reflection students used more case history data than residents. Expert models highlight the experts' problem solving cycle that consisted of reviewing data, identifying hypotheses, and planning. Post-questionnaire results indicate that participants found the cases to be interesting, useful for learning, but not especially difficult. Finally, several implications are drawn for the future development of BioWorld for medical training.

No description available.

No description available.

This study explores and describes the processes of formative evaluation as carried out by content experts and instructional designers. It assumes that formative evaluation is an ill-defined, complex, problem solving task. Six experts (three Content Experts and three Instructional Designers), participated in this descriptive study. Subjects reviewed and revised a unit from a draft version of a self-instructional module on microbiology, while thinking aloud. Two coding schemes were developed and applied to the think-aloud protocols. Overall inter-coder reliability exceeded 89%. Qualitative data were used to describe the processes of formative evaluation, convergence patterns, and the degree of specificity of comments across subjects. Results suggest that there were between group differences in task representation, in the employed strategies, and in features of the text which were commented upon more frequently. Within group similarities in the outcome of formative evaluation were salient on a superficial level. Within group differences were more apparent when comments were compared qualitatively.

Organizational culture can be defined as a set of values and behavior that contribute to the unique social and psychological environment of an organization. It is the major contributing factor in determining the progress of an organization towards the desired objectives. The importance of organizational culture for successful Lean transformation has been emphasized prior research. Lean implementation is based on continuous improvement, the achievement of which is based on problem solving practices. For sustained continuous improvement, problem solving must be done in a repeatable and disciplined way. However, not many organizations follow a structured approach towards problem solving. Some preliminary research indicates that organizational culture appears to be an important factor that influences the nature of problem solving practices used in an organization. This research, therefore, is focused towards establishing whether a relationship exists between these two aspects, namely, organizational culture and problem solving practices in relation to an organization’s success with Lean transformation. A comprehensive survey was developed to evaluate these two aspects. The survey was then administered to employees at different organizations, designations, various sectors and geographical regions. The survey results were analyzed to evaluate if an organization’s culture influences the problem solving practices used.

Cuando hablamos de optimización en el ámbito de las ciencias de la computación hacemos referencia al mismo concepto coloquial asociado a esa palabra, la concreción de un objetivo utilizando la menor cantidad de recursos disponibles, o en una visión similar, la obtención del mejor objetivo posible utilizando todos los recursos con lo que se cuenta. Los métodos para encontrar la mejor solución (óptima) varían de acuerdo a la complejidad del problema enfrentado. Para problemas triviales, el cerebro humano posee la capacidad de resolverlos (encontrar la mejor solución) directamente, pero a medida que aumenta la complejidad del problema, se hace necesario contar con herramientas adicionales. En esta dirección, existe una amplia variedad de técnicas para resolver problemas complejos. Dentro de estas técnicas, podemos mencionar las técnicas exactas. Este tipo de algoritmos son capaces de encontrar las soluciones óptimas a un problema dado en una cantidad finita de tiempo. Como contrapartida, requiere que el problema a resolver cumpla con condiciones bastante restrictivas. Existen además un conjunto muy amplio de técnica aproximadas, conocidas como metaheurísticas. Estas técnicas se caracterizan por integrar de diversas maneras procedimientos de mejora local y estrategias de alto nivel para crear un proceso capaz de escapar de óptimos locales y realizar una búsqueda robusta en el espacio de búsqueda del problema. En su evolución, estos métodos han incorporado diferentes estrategias para evitar la convergencia a óptimos locales, especialmente en espacios de búsqueda complejos. Este tipo de procedimientos tienen como principal característica que son aplicables a cualquier tipo de problemas, sin requerir ninguna condición particular a cumplir por los mismos. Estas técnicas no garantizan en ningún caso la obtención de los valores óptimos de los problemas en cuestión, pero se ha demostrado que son capaces de alcanzar muy buenos valores de soluciones en períodos de tiempo cortos. Además, es posible aplicarlas a problemas de diferentes tipos sin mayores modificaciones, mostrando su robustez y su amplio espectro de uso. La mayoría de estas técnicas están inspiradas en procesos biológicos y/o físicos, y tratan de simular el comportamiento propio de estos procesos que favorecen la búsqueda y detección de soluciones mejores en forma iterativa. La más difundida de estas técnicas son los algoritmos genéticos, basados en el mecanismo de evolución natural de las especies. Existen diferentes tipos de problemas, y multitud de taxonomías para clasificar los mismos. En el alcance de este trabajo nos interesa diferenciar los problemas en cuanto a la cantidad de objetivos a optimizar. Con esta consideración en mente, surge una primera clasificación evidente, los problemas mono-objetivo, donde existe solo una función objetivo a optimizar, y los problemas multi-objetivo donde existe más de una función objetivo. En el presente trabajo se estudia la utilización de metaheurísticas evolutivas para la resolución de problemas complejos, con uno y con más de un objetivo. Se efectúa un análisis del estado de situación en la materia, y se proponen nuevas variantes de algoritmos existentes, validando que las mismas mejoran resultados reportados en la literatura. En una primera instancia, se propone una mejora a la versión canónica y mono-objetivo del algoritmo PSO, luego de un estudio detallado del patrón de movimientos de las partículas en el espacio de soluciones. Estas mejoras se proponen en las versiones de PSO para espacios continuos y para espacios binarios. Asimismo, se analiza la implementación de una versión paralela de esta técnica evolutiva. Como segunda contribución, se plantea una nueva versión de un algoritmo PSO multiobjetivo (MOPSO Multi Objective Particle Swarm Optimization) incorporando la posibilidad de variar dinámicamente el tamaño de la población, lo que constituye una contribución innovadora en problemas con mas de una función objetivo. Por último, se utilizan las técnicas representativas del estado del arte en optimización multi-objetivo aplicando estos métodos a la problemática de una empresa de emergencias médicas y atención de consultas domiciliarias. Se logró poner en marcha un proceso de asignación de móviles a prestaciones médicas basado en metaheurísticas, logrando optimizar el proceso de asignación de móviles médicos a prestaciones médicas en la principal compañía de esta industria a nivel nacional. / Tesis doctoral de la Facultad de Informática (UNLP). Grado alcanzado: Doctor en Ciencias Informáticas. Director de tesis: Laura Lanzarini. Co-director de tesis: Guillermo Leguizamón. La tesis, presentada en el año 2013, obtuvo el Premio "Dr. Raúl Gallard" en el 2014.