740 resultados para Academic performance prediction


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University libraries play an important role in contributing to student and faculty members’ academic achievement. This study examines perceptions of university library usage to consider factors that influence achievement of students, academics and administrators. A thorough review of relevant literature examined approaches to determining user satisfaction of students and faculty, and factors that influence library usage. It highlighted the value of usage on educational performance. It enabled development of a theoretical framework leading to the Factors of Academic Library Usage (FALU) model, which was developed to investigate the effect of usage factors. FALU was tested in Kuwait university libraries. The study used validated questionnaires from 792 students, 143 academics and 121 administrators to measure five library factors. Interviews were conducted across the three University libraries. The findings are useful in measuring the correlation between the current academic library usage and educational performance.

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Purpose: To investigate the impact of simulated hyperopia and sustained near work on children’s ability to perform a range of academic-related tasks. Methods: Fifteen visually normal children (mean age: 10.9 ± 0.8 years; 10 males and 5 females) were recruited. Performance on a range of standardised academic-related outcome measures was assessed with and without 2.50 D of simulated bilateral hyperopia (administered in a randomised order), before and after 20 minutes of sustained near work, at two separate testing sessions. Academic-related measures included a standardised reading test (the Neale Analysis of Reading Ability), visual information processing tests (Coding and Symbol Search subtests from the Wechsler Intelligence Scale for Children) and a reading-related eye movement test (the Developmental Eye Movement test). Results: Simulated bilateral hyperopia and sustained near work each independently impaired reading, visual information processing and reading-related eye movement performance (p<0.001). A significant interaction was also demonstrated between these factors (p<0.001), with the greatest decrement in performance observed when simulated hyperopia was combined with sustained near work. This combination resulted in performance reductions of between 5% and 24% across the range of academic-related measures. A significant moderate correlation was also found between the change in horizontal near heterophoria and the change in several of the academic-related outcome measures, following the addition of simulated hyperopia. Conclusions: A relatively low level of simulated bilateral hyperopia impaired children’s performance on a range of academic–related outcome measures, with sustained near work further exacerbating this effect. Further investigations are required to determine the impact of correcting low levels of hyperopia on academic performance in children.

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Purpose: Astigmatism is an important refractive condition in children. However, the functional impact of uncorrected astigmatism in this population is not well established, particularly with regard to academic performance. This study investigated the impact of simulated bilateral astigmatism on academic-related tasks before and after sustained near work in children. Methods: Twenty visually normal children (mean age: 10.8 ± 0.7 years; 6 males and 14 females) completed a range of standardised academic-related tests with and without 1.50 D of simulated bilateral astigmatism (with both academic-related tests and the visual condition administered in a randomised order). The simulated astigmatism was induced using a positive cylindrical lens while maintaining a plano spherical equivalent. Performance was assessed before and after 20 minutes of sustained near work, during two separate testing sessions. Academic-related measures included a standardised reading test (the Neale Analysis of Reading Ability), visual information processing tests (Coding and Symbol Search subtests from the Wechsler Intelligence Scale for Children) and a reading-related eye movement test (the Developmental Eye Movement test). Each participant was systematically assigned either with-the-rule (WTR, axis 180°) or against-the-rule (ATR, axis 90°) simulated astigmatism to evaluate the influence of axis orientation on any decrements in performance. Results: Reading, visual information processing and reading-related eye movement performance were all significantly impaired by both simulated bilateral astigmatism (p<0.001) and sustained near work (p<0.001), however, there was no significant interaction between these factors (p>0.05). Simulated astigmatism led to a reduction of between 5% and 12% in performance across the academic-related outcome measures, but there was no significant effect of the axis (WTR or ATR) of astigmatism (p>0.05). Conclusion: Simulated bilateral astigmatism impaired children’s performance on a range of academic–related outcome measures irrespective of the orientation of the astigmatism. These findings have implications for the clinical management of non-amblyogenic levels of astigmatism in relation to academic performance in children. Correction of low to moderate levels of astigmatism may improve the functional performance of children in the classroom.

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Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

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Acquired brain injury (ABI) is the leading cause of death and disability amongst children and adolescents andpresents itself with challenges associated in cognitive, social, emotional, and behavioural domains. These changes may interfere with academic performance and social inclusion, influencing self-esteem and personal success. The current study examined a subset of data to capture the sense of academic and social belonging for students with ABI as a function of the classroom teachers’ subjective perception of ability, their ABI knowledge, and student identification. Overall, a discrepancy was found between educators’ subjective ratings of student performance and students’ neurocognitive capacity. Educator knowledge and identification of ABI influenced student success in academic and social domains independent of teaching approach. This research has implications for the identification of ABI in the classroom and related challenges students experience. Educators are underprepared for the reintegration of students returning to school and lack appropriate knowledge and strategies to accommodate individual needs.

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Performance modelling is a useful tool in the lifeycle of high performance scientific software, such as weather and climate models, especially as a means of ensuring efficient use of available computing resources. In particular, sufficiently accurate performance prediction could reduce the effort and experimental computer time required when porting and optimising a climate model to a new machine. In this paper, traditional techniques are used to predict the computation time of a simple shallow water model which is illustrative of the computation (and communication) involved in climate models. These models are compared with real execution data gathered on AMD Opteron-based systems, including several phases of the U.K. academic community HPC resource, HECToR. Some success is had in relating source code to achieved performance for the K10 series of Opterons, but the method is found to be inadequate for the next-generation Interlagos processor. The experience leads to the investigation of a data-driven application benchmarking approach to performance modelling. Results for an early version of the approach are presented using the shallow model as an example.

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This study examines the relationships between multiple intelligences, academic achievement and motor performance in a group of secondary school children. Four hundred and eighty schoolchildren participated in this study (171 female and 309 male) with an average age of 13.33 years (SD: 1.41). The Revised self-efficacy Inventory for Multiple Intelligences (IAIM-R) and the motor test Sportcomp were applied, and the average results of the academic year they had made were obtained. The analysis of the results showed how female scored significantly higher on the Linguistic, Spatial and Interpersonal intelligences, and older pupils scored significantly higher on the linguistic and naturalistic intelligences. It was the logical-mathematical intelligence which showed significant relationships with academic performance and it was the intelligence that better predicted this achievement. It was the bodily-kinesthetic intelligence that was significantly related to motor competence and the best intelligence that predicted its achievement. Finally, indicate that schoolchildren with better scores in the motor test were those who scored higher in both academic achievement and all the multiple intelligences, with the exception of musical intelligence.

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The purpose of this research was to develop and test a multicausal model of the individual characteristics associated with academic success in first-year Australian university students. This model comprised the constructs of: previous academic performance, achievement motivation, self-regulatory learning strategies, and personality traits, with end-of-semester grades the dependent variable of interest. The study involved the distribution of a questionnaire, which assessed motivation, self-regulatory learning strategies and personality traits, to 1193 students at the start of their first year at university. Students' academic records were accessed at the end of their first year of study to ascertain their first and second semester grades. This study established that previous high academic performance, use of self-regulatory learning strategies, and being introverted and agreeable, were indicators of academic success in the first semester of university study. Achievement motivation and the personality trait of conscientiousness were indirectly related to first semester grades, through the influence they had on the students' use of self-regulatory learning strategies. First semester grades were predictive of second semester grades. This research provides valuable information for both educators and students about the factors intrinsic to the individual that are associated with successful performance in the first year at university.

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Purpose – The purpose of this paper is to examine the use of bid information, including both price and non-price factors in predicting the bidder’s performance. Design/methodology/approach – The practice of the industry was first reviewed. Data on bid evaluation and performance records of the successful bids were then obtained from the Hong Kong Housing Department, the largest housing provider in Hong Kong. This was followed by the development of a radial basis function (RBF) neural network based performance prediction model. Findings – It is found that public clients are more conscientious and include non-price factors in their bid evaluation equations. With the input variables used the information is available at the time of the bid and the output variable is the project performance score recorded during work in progress achieved by the successful bidder. It was found that past project performance score is the most sensitive input variable in predicting future performance. Research limitations/implications – The paper shows the inadequacy of using price alone for bid award criterion. The need for a systemic performance evaluation is also highlighted, as this information is highly instrumental for subsequent bid evaluations. The caveat for this study is that the prediction model was developed based on data obtained from one single source. Originality/value – The value of the paper is in the use of an RBF neural network as the prediction tool because it can model non-linear function. This capability avoids tedious ‘‘trial and error’’ in deciding the number of hidden layers to be used in the network model. Keywords Hong Kong, Construction industry, Neural nets, Modelling, Bid offer spreads Paper type Research paper

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Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

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The present study intends to understand the parents' perception about children's academic stress and child care related issues. A group of 139 parents, 68 fathers and 71 mothers, participated in the study voluntarily and they were selected following convenience sampling technique. In order to achieve the objective of the study, a specially designed semi-structured questionnaire was used. Findings disclosed that about one-third of the fathers (29.4%) and one-tenth of the mothers (9.9%) frankly admitted that they could not provide quality care and guidance to their children and in this regard significant difference was observed between fathers and mothers (p<.05). More than four-fifth of the parents stated that they should be friendly with their children so that children feel comfortable to share their personal issues with them. More than one-fifth fathers (27.9%) and one-fourth mothers (16.9%) applied corporal punishment as they believed it is necessary to discipline them and/or for better academic performance.

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We hypothesized that Industry based learning and teaching, especially through industry assigned student projects or training programs, is an integral part of science, technology, engineering and mathematics (STEM) education. In this paper we show that industry-based student training and experience increases students’ academic performances independent to the organizational parameters and contexts. The literature on industry-based student training focuses on employability and the industry dimension, and neglects in many ways the academic dimension. We observed that the association factors between academic attributes and contributions of industry-based student training are central and vital to the technological learning experiences. We explore international initiatives and statistics collected of student projects in two categories: Industry based learning performances and on campus performances. The data collected were correlated to five (5) universities in different industrialized countries, e.g., Australia N=545, Norway N=279, Germany N=74, France N=107 and Spain N=802 respectively. We analyzed industry-based student training along with company assigned student projects compared with in comparisons to campus performance. The data that suggests a strong correlation between industry-based student training per se and improved performance profiles or increasing motivation shows that industry-based student training increases student academic performance independent of organizational parameters and contexts. The programs we augmented were orthogonal to each other however, the trend of the students’ academic performances are identical. An isolated cohort for the reported countries that opposed our hypothesis warrants further investigation.

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We hypothesized that Industry based learning and teaching, especially through company assigned student projects or training programs, is an integral part of science, technology, engineering and mathematics (STEM) education. In this paper we show that industry-based student training and experience increases students’ academic performances independent to the organizational parameters and contexts. The literature on industry-based student training focuses on employability and the industry dimension, and neglects in many ways the academic dimension. We observed that the association factors between academic attributes and contributions of industry-based student training are central and vital to the technological learning experiences. We explore international initiatives and statistics collected of student projects in two categories: Industry based learning performances and on campus performances. The data collected were correlated to five (5) universities in different industrialized countries, e.g., Australia N=545 projects, Norway N=279, Germany N=74, France N=107 and Spain N=802. We analyzed industry-based student training along with company assigned student projects compared with in comparisons to campus performance. The data that suggests a strong correlation between industry-based student training per se and improved performance profiles or increasing motivation shows that industry-based student training increases student academic performance independent of organizational parameters and contexts. The programs we augmented were orthogonal to each other however, the trend of the students’ academic performances are identical. An isolated cohort for the reported countries that opposed our hypothesis warrants further investigation.

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This work investigates the academic stress and mental health of Indian high school students and the associations between various psychosocial factors and academic stress. A total of190 students from grades 11 and 12 (mean age: 16.72 years) from three government-aided and three private schools in Kolkata India were surveyed in the study. Data collection involved using a specially designed structured questionnaire as well as the General Health Questionnaire. Nearly two-thirds (63.5%) of the students reported stress due to academic pressure – with no significant differences across gender, age, grade, and several other personal factors. About two-thirds (66%) of the students reported feeling pressure from their parents for better academic performance. The degree of parental pressure experienced differed significantly across the educational levels of the parents, mother’s occupation, number of private tutors, and academic performance. In particular, children of fathers possessing a lower education level (non-graduates) were found to be more likely to perceive pressure for better academic performance. About one-thirds (32.6%) of the students were symptomatic of psychiatric caseness and 81.6% reported examination-related anxiety. Academic stress was positively correlated with parental pressure and psychiatric problems, while examination-related anxiety also was positively related to psychiatric problems. Academic stress is a serious issue which affects nearly two thirds of senior high school students in Kolkata. Potential methods for combating the challenges of academic pressure are suggested.

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This study sought to assess the extent to which the entry characteristics of students in a graduate-entry medical programme predict the subsequent development of clinical reasoning ability. Subjects comprised 290 students voluntarily recruited from three successive cohorts of the University of Queensland's MBBS Programme. Clinical reasoning was measured once a year over a period of three years using two methods, a set of 10 Clinical Reasoning Problems (CRPs) and the Diagnostic Thinking Inventory (DTI). Data on gender, age at entry into the programme, nature of primary degree, scores on selection criteria (written examination plus interview) and academic performance in the first two years of the programme were recorded for each student, and their association with clinical reasoning skill analysed using univariate and multivariate analysis. Univariate analysis indicated significant associations between CRP score, gender and primary degree with a significant but small association between DTI and interview score. Stage of progression through the programme was also an important predictor of performance on both indicators. Subsequent multivariate analysis suggested that female gender is a positive predictor of CRP score independently of the nature of a subject's primary degree and stage of progression through the programme, although these latter two variables are interdependent. Positive predictors of clinical reasoning skill are stage of progression through the MBBS programme, female gender and interview score. Although the nature of a student's primary degree is important in the early years of the programme, evidence suggests that by graduation differences between students' clinical reasoning skill due to this factor have been resolved.