5 resultados para Test-problem Generator

em Digital Commons at Florida International University


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The purpose of this study was to investigate the effectiveness of training educators in the pre-behavioral intervention process of functional behavioral assessment. An original evaluation instrument was developed entitled, The Survey for Students Exhibiting Challenging Behavior. The instrument included measures of participating educators, knowledge of function of problem behavior and their ability to generate recommendations for a behavior intervention plan. The instrument was distributed to schools in a large urban district and completed by special educators. Educators trained and untrained in the functional behavioral assessment process were compared in the study. ^ The study incorporated a post-test only design. All instruments were analyzed using a factorial ANOVA. Those educators who were trained in the district functional behavioral assessment program answered general questions related to function of problem behavior significantly better than those who did not receive training. There is no significant difference between educators on their ability to generate recommendations for behavior intervention plans. It is important that educators receive training in functional behavioral assessment to gain an understanding of the basic notions being function of problem behavior. Current training does not translate into educators' ability to make strong recommendations for behavior intervention plans. ^

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The span of control is the most discussed single concept in classical and modern management theory. In specifying conditions for organizational effectiveness, the span of control has generally been regarded as a critical factor. Existing research work has focused mainly on qualitative methods to analyze this concept, for example heuristic rules based on experiences and/or intuition. This research takes a quantitative approach to this problem and formulates it as a binary integer model, which is used as a tool to study the organizational design issue. This model considers a range of requirements affecting management and supervision of a given set of jobs in a company. These decision variables include allocation of jobs to workers, considering complexity and compatibility of each job with respect to workers, and the requirement of management for planning, execution, training, and control activities in a hierarchical organization. The objective of the model is minimal operations cost, which is the sum of supervision costs at each level of the hierarchy, and the costs of workers assigned to jobs. The model is intended for application in the make-to-order industries as a design tool. It could also be applied to make-to-stock companies as an evaluation tool, to assess the optimality of their current organizational structure. Extensive experiments were conducted to validate the model, to study its behavior, and to evaluate the impact of changing parameters with practical problems. This research proposes a meta-heuristic approach to solving large-size problems, based on the concept of greedy algorithms and the Meta-RaPS algorithm. The proposed heuristic was evaluated with two measures of performance: solution quality and computational speed. The quality is assessed by comparing the obtained objective function value to the one achieved by the optimal solution. The computational efficiency is assessed by comparing the computer time used by the proposed heuristic to the time taken by a commercial software system. Test results show the proposed heuristic procedure generates good solutions in a time-efficient manner.

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Physical therapy students must apply the relevant information learned in their academic and clinical experience to problem solve in treating patients. I compared the clinical cognitive competence in patient care of second-year masters students enrolled in two different curricular programs: modified problem-based (M P-B; n = 27) and subject-centered (S-C; n = 41). Main features of S-C learning include lecture and demonstration as the major teaching strategies and no exposure to patients or problem solving learning until the sciences (knowledge) have been taught. Comparatively, main features of M P-B learning include case study in small student groups as the main teaching strategy, early and frequent exposure to patients, and knowledge and problem solving skills learned together for each specific case. Basic and clinical orthopedic knowledge was measured with a written test with open-ended items. Problem solving skills were measured with a written case study patient problem test yielding three subscores: assessment, problem identification, and treatment planning. ^ Results indicated that among the demographic and educational characteristics analyzed, there was a significant difference between groups on ethnicity, bachelor degree type, admission GPA, and current GPA, but there was no significant difference on gender, age, possession of a physical therapy assistant license, and GRE score. In addition, the M P-B group achieved a significantly higher adjusted mean score on the orthopedic knowledge test after controlling for GRE scores. The S-C group achieved a significantly higher adjusted mean total score and treatment management subscore on the case study test after controlling for orthopedic knowledge test scores. These findings did not support their respective research hypotheses. There was no significant difference between groups on the assessment and problem identification subscores of the case study test. The integrated M P-B approach promoted superior retention of basic and clinical science knowledge. The results on problem solving skills were mixed. The S-C approach facilitated superior treatment planning skills, but equivalent patient assessment and problem identification skills by emphasizing all equally and exposing the students to more patients with a wider variety of orthopedic physical therapy needs than in the M P-B approach. ^

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This thesis extended previous research on critical decision making and problem solving by refining and validating a measure designed to assess the use of critical thinking and critical discussion in sociomoral dilemmas. The purpose of this thesis was twofold: 1) to refine the administration of the Critical Thinking Subscale of the CDP to elicit more adequate responses and for purposes of refining the coding and scoring procedures for the total measure, and 2) to collect preliminary data on the initial reliabilities of the measure. Subjects consisted of 40 undergraduate students at Florida International University. Results indicate that the use of longer probes on the Critical Thinking Subscale was more effective in eliciting adequate responses necessary for coding and evaluating the subjects performance. Analyses on the psychometric properties of the measure consisted of test-retest reliability and inter-rater reliability.

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The electronics industry, is experiencing two trends one of which is the drive towards miniaturization of electronic products. The in-circuit testing predominantly used for continuity testing of printed circuit boards (PCB) can no longer meet the demands of smaller size circuits. This has lead to the development of moving probe testing equipment. Moving Probe Test opens up the opportunity to test PCBs where the test points are on a small pitch (distance between points). However, since the test uses probes that move sequentially to perform the test, the total test time is much greater than traditional in-circuit test. While significant effort has concentrated on the equipment design and development, little work has examined algorithms for efficient test sequencing. The test sequence has the greatest impact on total test time, which will determine the production cycle time of the product. Minimizing total test time is a NP-hard problem similar to the traveling salesman problem, except with two traveling salesmen that must coordinate their movements. The main goal of this thesis was to develop a heuristic algorithm to minimize the Flying Probe test time and evaluate the algorithm against a "Nearest Neighbor" algorithm. The algorithm was implemented with Visual Basic and MS Access database. The algorithm was evaluated with actual PCB test data taken from Industry. A statistical analysis with 95% C.C. was performed to test the hypothesis that the proposed algorithm finds a sequence which has a total test time less than the total test time found by the "Nearest Neighbor" approach. Findings demonstrated that the proposed heuristic algorithm reduces the total test time of the test and, therefore, production cycle time can be reduced through proper sequencing.