801 resultados para Scenario-based problem solving
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The objective of this study is to understand why virtual knowledge workers conduct autonomous tasks and interdependent problem solving tasks on virtual platforms. The study is qualitative case study including three case organizations that tap the knowledge of expert networks, and utilize virtual platforms in the work processes. Research data includes 15 interviews, that is, five experts from each case company. According to the findings there are some specific characteristics in motivation to work on tasks on online platforms. Autonomy, self-improvement, meaningful tasks, knowledge sharing, time management, variety of contacts, and variety of tasks, and projects motivate virtual knowledge workers. Factors that may enhance individuals’ engagement to work on tasks are trust, security of continuous task flow and income, feedback, meaningful tasks and tasks that contribute to self-improvement, flexibility and effectiveness in time management, and virtual tools that support social interaction. The results also indicate that there are some differences in individuals’ motivation based on the tasks’ nature. That is, knowledge sharing and variety of contacts motivated experts who worked on interdependent problem solving tasks. Then again, autonomy and variety of tasks motivated experts who worked on autonomous tasks.
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The quantitative component of this study examined the effect of computerassisted instruction (CAI) on science problem-solving performance, as well as the significance of logical reasoning ability to this relationship. I had the dual role of researcher and teacher, as I conducted the study with 84 grade seven students to whom I simultaneously taught science on a rotary-basis. A two-treatment research design using this sample of convenience allowed for a comparison between the problem-solving performance of a CAI treatment group (n = 46) versus a laboratory-based control group (n = 38). Science problem-solving performance was measured by a pretest and posttest that I developed for this study. The validity of these tests was addressed through critical discussions with faculty members, colleagues, as well as through feedback gained in a pilot study. High reliability was revealed between the pretest and the posttest; in this way, students who tended to score high on the pretest also tended to score high on the posttest. Interrater reliability was found to be high for 30 randomly-selected test responses which were scored independently by two raters (i.e., myself and my faculty advisor). Results indicated that the form of computer-assisted instruction (CAI) used in this study did not significantly improve students' problem-solving performance. Logical reasoning ability was measured by an abbreviated version of the Group Assessment of Lx)gical Thinking (GALT). Logical reasoning ability was found to be correlated to problem-solving performance in that, students with high logical reasoning ability tended to do better on the problem-solving tests and vice versa. However, no significant difference was observed in problem-solving improvement, in the laboratory-based instruction group versus the CAI group, for students varying in level of logical reasoning ability.Insignificant trends were noted in results obtained from students of high logical reasoning ability, but require further study. It was acknowledged that conclusions drawn from the quantitative component of this study were limited, as further modifications of the tests were recommended, as well as the use of a larger sample size. The purpose of the qualitative component of the study was to provide a detailed description ofmy thesis research process as a Brock University Master of Education student. My research journal notes served as the data base for open coding analysis. This analysis revealed six main themes which best described my research experience: research interests, practical considerations, research design, research analysis, development of the problem-solving tests, and scoring scheme development. These important areas ofmy thesis research experience were recounted in the form of a personal narrative. It was noted that the research process was a form of problem solving in itself, as I made use of several problem-solving strategies to achieve desired thesis outcomes.
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Three grade three mathematics textbooks were selected arbitrarily (every other) from a total of six currently used in the schools of Ontario. These textbooks were examined through content analysis in order to determine the extent (i. e., the frequency of occurrence) to which problem solving strategies appear in the problems and exercises of grade three mathematics textbooks, and how well they carry through the Ministry's educational goals set out in The Formative Years. Based on Polya's heuristic model, a checklist was developed by the researcher. The checklist had two main categories, textbook problems and process problems and a finer classification according to the difficulty level of a textbook problem; also six commonly used problem solving strategies for the analysis of a process problem. Topics to be analyzed were selected from the subject guideline The Formative Years, and the same topics were selected from each textbook. Frequencies of analyzed problems and exercises were compiled and tabulated textbook by textbook and topic by topic. In making comparisons, simple frequency count and percentage were used in the absence of any known criteria available for judging highor low frequency. Each textbook was coded by three coders trained to use the checklist. The results of analysis showed that while there were large numbers of exercises in each textbook, not very many were framed as problems according to Polya' s model and that process problems form a small fraction of the number of analyzed problems and exercises. There was no pattern observed as to the systematic placement of problems in the textbooks.
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Forty grade 9 students were selected from a small rural board in southern Ontario. The students were in two classes and were treated as two groups. The treatment group received instruction in the Logical Numerical Problem Solving Strategy every day for 37 minutes over a 6 week period. The control group received instruction in problem solving without this strategy over the same time period. Then the control group received the treat~ent and the treatment group received the instruction without the strategy. Quite a large variance was found in the problem solving ability of students in grade 9. It was also found that the growth of the problem solving ability achievement of students could be measured using growth strands based upon the results of the pilot study. The analysis of the results of the study using t-tests and a MANOVA demonstrated that the teaching of the strategy did not significaritly (at p s 0.05) increase the problem solving achievement of the students. However, there was an encouraging trend seen in the data.
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The magnitude of the cervical cancer problem, coupled with the potential for prevention with recent technological advances, made it imperative to step back and reassess strategic options for dealing with cervical cancer screening in Kenya. The purpose of this qualitative study was: 1) to explore the extent to which the Participatory Action Research (PAR) methodology and the Scenario Based Planning (SBP) method, with the application of analytics, could enable strategic, consequential, informed decision making, and 2) to determine how influential Kenyan decision makers could apply SBP with analytic tools and techniques to make strategic, consequential decisions regarding the implementation of a Cervical Self Sampling Program (CSSP) in both urban and rural settings. The theoretical paradigm for this study was action research; it was experiential, practical, and action oriented, and resulted in co-created knowledge that influenced study participants’ decision making. Action Africa Help International (AAHI) and Brock University collaborated with Local Decision Influencing Participants (LDIP’s) to develop innovative strategies on how to implement the CSSP. SBP tools, along with traditional approaches to data collection and analysis, were applied to collect, visualize and analyze predominately qualitative data. Outputs from the study included: a) a generic implementation scenario for a CSSP (along with scenarios unique to urban and rural settings), and b) 10 strategic directions and 22 supporting implementation strategies that address the variables of: 1) technical viability, 2) political support, 3) affordability, 4) logistical feasibility, 5) social acceptability, and 6) transformation/sustainability. In addition, study participants’ capacity to effectively engage in predictive/prescriptive strategic decision making was strengthened.
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This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.
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This study assessed the effectiveness of an online mathematical problem solving course designed using a social constructivist approach for pre-service teachers. Thirty-seven pre-service teachers at the Batu Lintang Teacher Institute, Sarawak, Malaysia were randomly selected to participate in the study. The participants were required to complete the course online without the typical face-to-face classes and they were also required to solve authentic mathematical problems in small groups of 4-5 participants based on the Polya’s Problem Solving Model via asynchronous online discussions. Quantitative and qualitative methods such as questionnaires and interviews were used to evaluate the effects of the online learning course. Findings showed that a majority of the participants were satisfied with their learning experiences in the course. There were no significant changes in the participants’ attitudes toward mathematics, while the participants’ skills in problem solving for “understand the problem” and “devise a plan” steps based on the Polya’s Model were significantly enhanced, though no improvement was apparent for “carry out the plan” and “review”. The results also showed that there were significant improvements in the participants’ critical thinking skills. Furthermore, participants with higher initial computer skills were also found to show higher performance in mathematical problem solving as compared to those with lower computer skills. However, there were no significant differences in the participants’ achievements in the course based on gender. Generally, the online social constructivist mathematical problem solving course is beneficial to the participants and ought to be given the attention it deserves as an alternative to traditional classes. Nonetheless, careful considerations need to be made in the designing and implementing of online courses to minimize problems that participants might encounter while participating in such courses.
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This article describes a knowledge-based application in the domain of road traffic management that we have developed following a knowledge modeling approach and the notion of problem-solving method. The article presents first a domain-independent model for real-time decision support as a structured collection of problem solving methods. Then, it is described how this general model is used to develop an operational version for the domain of traffic management. For this purpose, a particular knowledge modeling tool, called KSM (Knowledge Structure Manager), was applied. Finally, the article shows an application developed for a traffic network of the city of Madrid and it is compared with a second application developed for a different traffic area of the city of Barcelona.
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This research project focused upon the design strategies adopted by expert and novice designers. It was based upon a desire to compare the design problem solving strategies of novices, in this case key stage three pupils studying technolgy within the United Kingdom National Curriculum, with designers who could be considered to have developed expertise. The findings helped to provide insights into potential teaching strategies to suit novice designers. Verbal protocols were made as samples of expert and novice designers solved a design problem and talked aloud as they worked. The verbalisations were recorded on video tape. The protocols were transcribed and segmented, with each segment being assigned to a predetermined coding system which represented a model of design problem solving. The results of the encoding were analysed and consideration was also given to the general design strategy and heuristics used by the expert and novice designers. The drawings and models produced during the generation of the protocols were also analysed and considered. A number of significant differences between the problem solving strategies adopted by the expert and novice designers were identified. First of all, differences were observed in the way expert and novice designers used the problem statement and solution validation during the process. Differences were also identified in the way holistic solutions were generated near the start of the process, and also in the cycles of exploration and the processes of integration. The way design and technological knowledge was used provided further insights into the differences between experts and novices, as did the role of drawing and modelling during the process. In more general terms, differences were identified in the heuristics and overall design strategies adopted by the expert and novice designers. The above findings provided a basis for discussing teaching strategies appropriate for novice designers. Finally, opportunities for future research were discussed.
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Prior research suggests management can employ cognitively demanding job attributes to promote employee creativity. However, it is not clear what specific type of cognitive demand is particularly important for creativity, what processes underpin the relationship between demanding job conditions and creativity and what factors lead to employee perceptions of demanding job attributes. This research sets out to address the aforementioned issues by examining: (i) problem-solving demand (PDS), a specific type of cognitive demand, and the processes that link PSD to creativity, and (ii) antecedents to PSD. Based on social cognitive theory, PSD was hypothesized to be positively related to creativity through the motivational mechanism of creative self-efficacy. However, the relationship between PSD and creative self-efficacy was hypothesized to be contingent on levels of intrinsic motivation. Social information processing perspective and the job crafting model were used to identify antecedents of PSD. Consequently, two social-contextual factors (supervisor developmental feedback and job autonomy) and one individual factor (proactive personality) were hypothesized to be precursors to PSD perceptions. The theorized model was tested with data obtained from a sample of 270 employees and their supervisors from 3 organisations in the People’s Republic of China. Regression results revealed that PSD was positively related to creativity but this relationship was partially mediated by creative self-efficacy. Additionally, intrinsic motivation moderated the relationship between PSD and creative self-efficacy such that the relationship was stronger for individuals high rather than low in intrinsic motivation. The findings represent a productive first step in identifying a specific cognitive demand that is conducive to employee creativity. In addition, the findings contribute to the literature by identifying a psychological mechanism that may link cognitively demanding job attributes and creativity.
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Processing information and forming opinions pose special challenges when attempting to effectively manage the new or complex tasks that typically arise in projects. Based on research in organizational and social psychology, we introduce mechanisms and strategies for collective information processing which are important for forming opinions and handling information in projects.
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This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.
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Background: Healthcare worldwide needs translation of basic ideas from engineering into the clinic. Consequently, there is increasing demand for graduates equipped with the knowledge and skills to apply interdisciplinary medicine/engineering approaches to the development of novel solutions for healthcare. The literature provides little guidance regarding barriers to, and facilitators of, effective interdisciplinary learning for engineering and medical students in a team-based project context. Methods: A quantitative survey was distributed to engineering and medical students and staff in two universities, one in Ireland and one in Belgium, to chart knowledge and practice in interdisciplinary learning and teaching, and of the teaching of innovation. Results: We report important differences for staff and students between the disciplines regarding attitudes towards, and perceptions of, the relevance of interdisciplinary learning opportunities, and the role of creativity and innovation. There was agreement across groups concerning preferred learning, instructional styles, and module content. Medical students showed greater resistance to the use of structured creativity tools and interdisciplinary teams. Conclusions: The results of this international survey will help to define the optimal learning conditions under which undergraduate engineering and medicine students can learn to consider the diverse factors which determine the success or failure of a healthcare engineering solution.
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Résumé : Une définition opérationnelle de la dyslexie qui est adéquate et pertinente à l'éducation n'a pu être identifiée suite à une recension des écrits. Les études sur la dyslexie se retrouvent principalement dans trois champs: la neurologie, la neurolinguistique et la génétique. Les résultats de ces recherches cependant, se limitent au domaine médical et ont peu d'utilité pour une enseignante ou un enseignant. La classification de la dyslexie de surface et la dyslexie profonde est la plus appropriée lorsque la dyslexie est définie comme trouble de lecture dans le contexte de l'éducation. L'objectif de ce mémoire était de développer un cadre conceptuel théorique dans lequel les troubles de lecture chez les enfants dyslexiques sont dû à une difficulté en résolution de problèmes dans le traitement de l'information. La validation du cadre conceptuel a été exécutée à l'aide d'un expert en psychologie cognitive, un expert en dyslexie et une enseignante. La perspective de la résolution de problèmes provient du traitement de l'information en psychologie cognitive. Le cadre conceptuel s'adresse uniquement aux troubles de lectures qui sont manifestés par les enfants dyslexiques.||Abstract : An extensive literature review failed to uncover an adequate operational definition of dyslexia applicable to education. The predominant fields of research that have produced most of the studies on dyslexia are neurology, neurolinguistics and genetics. Their perspectives were shown to be more pertinent to medical experts than to teachers. The categorization of surface and deep dyslexia was shown to be the best description of dyslexia in an educational context. The purpose of the present thesis was to develop a theoretical conceptual framework which describes a link between dyslexia, a text-processing model and problem solving. This conceptual framework was validated by three experts specializing in a specific field (either cognitive psychology, dyslexia or teaching). The concept of problem solving was based on information-processing theories in cognitive psychology. This framework applies specifically to reading difficulties which are manifested by dyslexic children.