839 resultados para Research on problem solving


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The long term goal of the work described is to contribute to the emerging literature of prevention science in general, and to school-based psychoeducational interventions in particular. The psychoeducational intervention reported in this study used a main effects prevention intervention model. The current study focused on promoting optimal cognitive and affective functioning. The goal of this intervention was to increase potential protective factors such as critical cognitive and communicative competencies (e.g., critical problem solving and decision making) and affective competencies (e.g., personal control and responsibility) in middle adolescents who have been identified by the school system as being at-risk for problem behaviors. The current psychoeducational intervention draws on an ongoing program of theory and research (Berman, Berman, Cass Lorente, Ferrer Wreder, Arrufat, & Kurtines 1996; Ferrer Wreder, 1996; Kurtines, Berman, Ittel, & Williamson, 1995) and extends it to include Freire's (1970) concept of transformative pedagogy in developing school-based psychoeducational programs that target troubled adolescents. The results of the quantitative and qualitative analyses indicated trends that were generally encouraging with respect to the effects of the intervention on increasing critical cognitive and affective competencies. ^

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The dissertation reports on two studies. The purpose of Study I was to develop and evaluate a measure of cognitive competence (the Critical Problem Solving Skills Scale – Qualitative Extension) using Relational Data Analysis (RDA) with a multi-ethnic, adolescent sample. My study builds on previous work that has been conducted to provide evidence for the reliability and validity of the RDA framework in evaluating youth development programs (Kurtines et al., 2008). Inter-coder percent agreement among the TOC and TCC coders for each of the category levels was moderate to high, with a range of .76 to .94. The Fleiss' kappa across all category levels was from substantial agreement to almost perfect agreement, with a range of .72 to .91. The correlation between the TOC and the TCC demonstrated medium to high correlation, with a range of r(40)=.68, p<.001 to r(40)=.79, p<.001. Study II reports an investigation of a positive youth development program using an Outcome Mediation Cascade (OMC) evaluation model, an integrated model for evaluating the empirical intersection between intervention and developmental processes. The Changing Lives Program (CLP) is a community supported positive youth development intervention implemented in a practice setting as a selective/indicated program for multi-ethnic, multi-problem at risk youth in urban alternative high schools in the Miami Dade County Public Schools (M-DCPS). The 259 participants for this study were drawn from the CLP's archival data file. The study used a structural equation modeling approach to construct and evaluate the hypothesized model. Findings indicated that the hypothesized model fit the data (χ2 (7) = 5.651, p = .83; RMSEA = .00; CFI = 1.00; WRMR = .319). My study built on previous research using the OMC evaluation model (Eichas, 2010), and the findings are consistent with the hypothesis that in addition to having effects on targeted positive outcomes, PYD interventions are likely to have progressive cascading effects on untargeted problem outcomes that operate through effects on positive outcomes.

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Expertise in physics has been traditionally studied in cognitive science, where physics expertise is understood through the difference between novice and expert problem solving skills. The cognitive perspective of physics experts only create a partial model of physics expertise and does not take into account the development of physics experts in the natural context of research. This dissertation takes a social and cultural perspective of learning through apprenticeship to model the development of physics expertise of physics graduate students in a research group. I use a qualitative methodological approach of an ethnographic case study to observe and video record the common practices of graduate students in their biophysics weekly research group meetings. I recorded notes on observations and conduct interviews with all participants of the biophysics research group for a period of eight months. I apply the theoretical framework of Communities of Practice to distinguish the cultural norms of the group that cultivate physics expert practices. Results indicate that physics expertise is specific to a topic or subfield and it is established through effectively publishing research in the larger biophysics research community. The participant biophysics research group follows a learning trajectory for its students to contribute to research and learn to communicate their research in the larger biophysics community. In this learning trajectory students develop expert member competencies to learn to communicate their research and to learn the standards and trends of research in the larger research community. Findings from this dissertation expand the model of physics expertise beyond the cognitive realm and add the social and cultural nature of physics expertise development. This research also addresses ways to increase physics graduate student success towards their PhD. and decrease the 48% attrition rate of physics graduate students. Cultivating effective research experiences that give graduate students agency and autonomy beyond their research groups gives students the motivation to finish graduate school and establish their physics expertise.^

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This study examined the effectiveness of intelligent tutoring system instruction, grounded in John Anderson's ACT theory of cognition, on the achievement and attitude of developmental mathematics students in the community college setting. The quasi-experimental research used a pretest-posttest control group design. The dependent variables were problem solving achievement, overall achievement, and attitude towards mathematics. The independent variable was instructional method. Four intact classes and two instructors participated in the study for one semester. Two classes (n = 35) served as experimental groups; they received six lessons with real-world problems using intelligent tutoring system instruction. The other two classes (n = 24) served as control groups; they received six lessons with real-world problems using traditional instruction including graphing calculator support. It was hypothesized that students taught problem solving using the intelligent tutoring system would achieve more on the dependent variables than students taught without the intelligent tutoring system. Posttest mean scores for one teacher produced a significant difference in overall achievement for the experimental group. The same teacher had higher means, not significantly, for the experimental group in problem solving achievement. The study did not indicate a significant difference in attitude mean scores. It was concluded that using an intelligent tutoring system in problem solving instruction may impact student's overall mathematics achievement and problem solving achievement. Other factors must be considered, such as the teacher's classroom experience, the teacher's experience with the intelligent tutoring system, trained technical support, and trained student support; as well as student learning styles, motivation, and overall mathematics ability.

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Empirical studies of education programs and systems, by nature, rely upon use of student outcomes that are measurable. Often, these come in the form of test scores. However, in light of growing evidence about the long-run importance of other student skills and behaviors, the time has come for a broader approach to evaluating education. This dissertation undertakes experimental, quasi-experimental, and descriptive analyses to examine social, behavioral, and health-related mechanisms of the educational process. My overarching research question is simply, which inside- and outside-the-classroom features of schools and educational interventions are most beneficial to students in the long term? Furthermore, how can we apply this evidence toward informing policy that could effectively reduce stark social, educational, and economic inequalities?

The first study of three assesses mechanisms by which the Fast Track project, a randomized intervention in the early 1990s for high-risk children in four communities (Durham, NC; Nashville, TN; rural PA; and Seattle, WA), reduced delinquency, arrests, and health and mental health service utilization in adolescence through young adulthood (ages 12-20). A decomposition of treatment effects indicates that about a third of Fast Track’s impact on later crime outcomes can be accounted for by improvements in social and self-regulation skills during childhood (ages 6-11), such as prosocial behavior, emotion regulation and problem solving. These skills proved less valuable for the prevention of mental and physical health problems.

The second study contributes new evidence on how non-instructional investments – such as increased spending on school social workers, guidance counselors, and health services – affect multiple aspects of student performance and well-being. Merging several administrative data sources spanning the 1996-2013 school years in North Carolina, I use an instrumental variables approach to estimate the extent to which local expenditure shifts affect students’ academic and behavioral outcomes. My findings indicate that exogenous increases in spending on non-instructional services not only reduce student absenteeism and disciplinary problems (important predictors of long-term outcomes) but also significantly raise student achievement, in similar magnitude to corresponding increases in instructional spending. Furthermore, subgroup analyses suggest that investments in student support personnel such as social workers, health services, and guidance counselors, in schools with concentrated low-income student populations could go a long way toward closing socioeconomic achievement gaps.

The third study examines individual pathways that lead to high school graduation or dropout. It employs a variety of machine learning techniques, including decision trees, random forests with bagging and boosting, and support vector machines, to predict student dropout using longitudinal administrative data from North Carolina. I consider a large set of predictor measures from grades three through eight including academic achievement, behavioral indicators, and background characteristics. My findings indicate that the most important predictors include eighth grade absences, math scores, and age-for-grade as well as early reading scores. Support vector classification (with a high cost parameter and low gamma parameter) predicts high school dropout with the highest overall validity in the testing dataset at 90.1 percent followed by decision trees with boosting and interaction terms at 89.5 percent.

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The dissertation reports on two studies. The purpose of Study I was to develop and evaluate a measure of cognitive competence (the Critical Problem Solving Skills Scale – Qualitative Extension) using Relational Data Analysis (RDA) with a multi-ethnic, adolescent sample. My study builds on previous work that has been conducted to provide evidence for the reliability and validity of the RDA framework in evaluating youth development programs (Kurtines et al., 2008). Inter-coder percent agreement among the TOC and TCC coders for each of the category levels was moderate to high, with a range of .76 to .94. The Fleiss’ kappa across all category levels was from substantial agreement to almost perfect agreement, with a range of .72 to .91. The correlation between the TOC and the TCC demonstrated medium to high correlation, with a range of r(40)=.68, p Study II reports an investigation of a positive youth development program using an Outcome Mediation Cascade (OMC) evaluation model, an integrated model for evaluating the empirical intersection between intervention and developmental processes. The Changing Lives Program (CLP) is a community supported positive youth development intervention implemented in a practice setting as a selective/indicated program for multi-ethnic, multi-problem at risk youth in urban alternative high schools in the Miami Dade County Public Schools (M-DCPS). The 259 participants for this study were drawn from the CLP’s archival data file. The study used a structural equation modeling approach to construct and evaluate the hypothesized model. Findings indicated that the hypothesized model fit the data (χ2 (7) = 5.651, p = .83; RMSEA = .00; CFI = 1.00; WRMR = .319). My study built on previous research using the OMC evaluation model (Eichas, 2010), and the findings are consistent with the hypothesis that in addition to having effects on targeted positive outcomes, PYD interventions are likely to have progressive cascading effects on untargeted problem outcomes that operate through effects on positive outcomes.

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Expertise in physics has been traditionally studied in cognitive science, where physics expertise is understood through the difference between novice and expert problem solving skills. The cognitive perspective of physics experts only create a partial model of physics expertise and does not take into account the development of physics experts in the natural context of research. This dissertation takes a social and cultural perspective of learning through apprenticeship to model the development of physics expertise of physics graduate students in a research group. I use a qualitative methodological approach of an ethnographic case study to observe and video record the common practices of graduate students in their biophysics weekly research group meetings. I recorded notes on observations and conduct interviews with all participants of the biophysics research group for a period of eight months. I apply the theoretical framework of Communities of Practice to distinguish the cultural norms of the group that cultivate physics expert practices. Results indicate that physics expertise is specific to a topic or subfield and it is established through effectively publishing research in the larger biophysics research community. The participant biophysics research group follows a learning trajectory for its students to contribute to research and learn to communicate their research in the larger biophysics community. In this learning trajectory students develop expert member competencies to learn to communicate their research and to learn the standards and trends of research in the larger research community. Findings from this dissertation expand the model of physics expertise beyond the cognitive realm and add the social and cultural nature of physics expertise development. This research also addresses ways to increase physics graduate student success towards their PhD. and decrease the 48% attrition rate of physics graduate students. Cultivating effective research experiences that give graduate students agency and autonomy beyond their research groups gives students the motivation to finish graduate school and establish their physics expertise.

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The purpose of this paper is to raise a debate on the urgent need for teachers to generate innovative situations in the teaching-learning process, in the field of Mathematics, as a way for students to develop logical reasoning and research skills applicable to everyday situations. It includes some statistical data and possible reasons for the poor performance and dissatisfaction of students towards Mathematics. Since teachers are called to offer meaningful and functional learning experiences to students, in order to promote the pleasure of learning, teacher training should include experiences that can be put into practice by teachers in the education centers. This paper includes a work proposal for Mathematics Teaching to generate discussion, curiosity and logical reasoning in students, together with the Mathematical problem solving study.

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Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

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This study, using a Delphi approach, sought the opinion of a self-selected panel of 320 district nurses regarding research priorities for district nursing in Australia. Over three rounds of questionnaires, the 419 research clinical problem areas requiring research as suggested by the panel were each rated in importance by the panel and then ranked through analysis from high to low average rating scores, thereby, whittling down the list to the top 15% (68) research questions and to a final list of the top 10 research priorities overall. Research questions focusing on discharge planning are dominant in these top 10 priorities, with documentation issues the second most common focus. Other foci in the top 10 priorities are staffing, aged care, palliative care, and assessment. The organization-specific top 10 research priorities focus on wound care, funding, education, and communication issues. Additionally, the top 68 priorities, which are either finitely practice-based or contextual-issues research questions, were categorized into 20 themes. The results will hopefully lead to scarce human and financial resources being directed to practice-relevant research programs that will facilitate improved health for district nursing (primarily home-nursing) clients in Australia and elsewhere. (c) 2005 Elsevier Inc. All rights reserved.

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Purpose of review To identify and discuss recent research studies that propose innovative psychosocial interventions in old age psychiatry. Recent findings Studies have shown that cognitive training research for healthy elderly has advanced in several ways, particularly in the refinement of study design and methodology. Studies have included larger samples and longer training protocols. Interestingly, new research has shown changes in biological markers associated with learning and memory after cognitive training. Among mild cognitive impairment patients, results have demonstrated that they benefit from interventions displaying cognitive plasticity. Rehabilitation studies involving dementia patients have suggested the efficacy of combined treatment approaches, and light and music therapies have shown promising effects. For psychiatric disorders, innovations have included improvements in well known techniques such as cognitive behavior therapy, studies in subpopulations with comorbidities, as well as the use of new computer-aided resources. Summary Research evidence on innovative interventions in old age psychiatry suggests that this exciting field is moving forward by means of methodological refinements and testing of creative new ideas.

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This chapter explores the impact of innovation technologies such as simulation, modelling, and rapid prototyping on engineering practice. Innovation technologies help redefine the role of engineers in the innovation process, creating a new division of innovative labour both with and across organizations. This chapter also explores the boundaries of experimentation and inertia within particular domains of problem-solving to create new opportunities and value.

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This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.