Misfits : people and their problems. What might it all mean?

In the analysis of data, which arise from the administration of multiple choice tests or survey instruments and which are assumed to conform to a measurement model such as Rasch, it is normal practice to check item fit statistics in order to ensure that the items used in the instrument cohere to form a unidimensional trait measure. However, checking whether individuals also fit the measurement model appears to be less common. It is shown that poor person-fit compromises item parameter estimates and so it is argued that person-fit should be checked routinely in the calibration of instruments and in scoring individuals. Unfortunately, the meanings that can be ascribed to person-fit statistics for attitude instruments is not clear. A proposal for seeking the required clarity is developed. [Author abstract

School non-completers: Profiles and initial destinations

This study examines non-completion of Year 12 at school for a nationally representative sample of young people who were 15 years old and still attending school in 2003. The study explores relationships between non-completion and selected socio-demographic and school-related factors, and changes in rates of school non-completion from the early 1980s to 2005. There is a particular emphasis on how socio-demographic and school-related factors over that period have influenced early school leaving. This study also examines the use of an alternative measure of ‘school completion’, which incorporates participation in a vocational education and training program after leaving school

A Study into the assessment and reporting of employability skills of senior secondary students

In order to investigate the most effective ways of assessing and reporting on the employability skills of senior secondary students, the Commonwealth Department of Education, Science and Training (DEST) commissioned this report. The main activity was to evaluate options for assessing and reporting on eight employability skills against five criteria—validity, reliability, objectivity, feasibility, and usability—and to recommend a preferred approach. This work was undertaken by the Australian Council for Educational Research (ACER) in the period July 2007 to January 2008, during which time the (new) Department of Education, Employment and Workplace Relations (DEEWR) became responsible for the initiative. The starting point for this work was to come to terms with the eight employability skills and their respective facets from the Employability Skills Framework (ACCI & BCA, 2002). The employability skills are: Communication; Initiative & Enterprise; Learning; Planning & Organising; Problem Solving; Self-management; Teamwork; and Technology. Facets are elements of the skill that employers have identified as important, with the specific mix and priority of facets being job-dependent. One of the facets of Communication, for example, is ‘Reading independently’. As an adjunct activity to this study, the University of Western Sydney conducted a survey of the current level of employer satisfaction with the eight identified employability skills and how employers assess them (Costley, Power, Watson, Steele, & Sproats, 2007). Consultations were undertaken with employers, and representatives of parent organisations, school systems including teachers and leaders, and Australia’s three peak business organisations, ACCI, BCA, and the Australian Industry Group (AIG). An advisory group set up by DEST had the same representation. In addition, expert input was sought on detailed matters of assessment and reporting

Research and national debate on Australian schooling

This paper is a response to the paper prepared by Masters that is titled 'The case for an Australian Certificate of Education'. It argues that a national debate is needed urgently on the many issues that have arisen in Australian education. These issues include not only the curriculum provided for students at the final stages of secondary schooling, and the certification of attainment of educational outcomes on completion of 12 years of schooling, but also the curriculum of schools across Australia, particularly at the lower and middle secondary school levels. In addition, there are related issues associated with participation in higher education and the completion of a first degree at an Australian university. All too often, decisions are made at all levels of education on ideological grounds and without consideration of the body of research findings that are available to guide the making of decisions and the monitoring of development and change. This paper draws on readily available research to show the similarities and differences between the state education systems to argue a case for informed debate that draws on the large body of evidence that is available

Computer adventure games as problem-solving environments

Claims that computer-based adventure games are productive environments for the development of general problem-solving ability were tested in a study of 40 students' interactions with a novel computer-based adventure game. Two sets of factors that are thought to influence problem-solving performance were identified in the literature – domain-specific knowledge (schema) and general problem-solving strategies. Measures of both domain-specific knowledge and general strategy use were developed and applied in the study. A cognitive model to explain performance is developed in which there are complex relationships among key concepts. General strategies were found to have important influences on problem-solving performance, but schema was negatively related to performance. The implications of these findings for both classroom practice and future research designs are discussed. [Author abstract

Selected Physical Properties of Jointed Goatgrass (Aegilops cylindrica Host.)

Selected physical properties of jointed goatgrass samples collected in western Nebraska and eastern Colorado were determined. Measured properties were spikelet dimensions (length 10.8 ± 0.35 mm; width 2.59 ± 0.25 mm), particle density (0.761 ± 0.016 g/m3), bulk density (351 ± 26.9 kg/m3), terminal velocity (301 ± 25.9 m/min), angle of repose (26.3 ± 0.286°), internal coefficient of friction (0.494 ± 0.007), and equilibrium moisture contents at 10% RH (6.56 ± 1.03% w.b.), 30% RH (7.43 ± 1.21% w.b.), 50% RH (9.01 ± 0.67% w.b.), 70% RH (11.89 ± 0.61% w.b.), and 90% RH (20.39 ± 2.38% w.b.). Jointed goatgrass had substantially lower particle density and bulk density values than those reported in the literature for hard red winter wheat

Selected Physical Properties of Jointed Goatgrass (Aegilops cylindrica Host.)

Selected physical properties of jointed goatgrass samples collected in western Nebraska and eastern Colorado were determined. Measured properties were spikelet dimensions (length 10.8 ± 0.35 mm; width 2.59 ± 0.25 mm), particle density (0.761 ± 0.016 g/m3), bulk density (351 ± 26.9 kg/m3), terminal velocity (301 ± 25.9 m/min), angle of repose (26.3 ± 0.286°), internal coefficient of friction (0.494 ± 0.007), and equilibrium moisture contents at 10% RH (6.56 ± 1.03% w.b.), 30% RH (7.43 ± 1.21% w.b.), 50% RH (9.01 ± 0.67% w.b.), 70% RH (11.89 ± 0.61% w.b.), and 90% RH (20.39 ± 2.38% w.b.). Jointed goatgrass had substantially lower particle density and bulk density values than those reported in the literature for hard red winter wheat

Risk of injury analysis in depth jump and squat jump

Introduction: The depth jump (DJ) and squat jump (SJ) are accepted ways to assess and train power producing ability but are not without risk of injury. Methods: Sixteen male participants (age = 21.7 ± 1.54 yrs., height = 177.7 ± 11.4 cm, mass = 77.7 ± 13.6 kg) were evaluated for power exertion capabilities while being assessed for risk of injury in the knee and low back through a range of resistances based on a percentage of participants’ heights in the DJ (0% through 50%) and bodyweights for the SJ (0% through 100%). Two variables were used to assess the risk of injury in the knee: valgus angle and internal abduction moment (IAM). Four variables were used in the low back: compression and shear force at the L5/S1 vertebrae, intra-abdominal pressure (IAP), and erector muscle tension. Results: With increasing DJ drop height, participants showed increased risk of injury in the knee through the valgus angle and IAM. In the low back, significant correlation occurred between increasing drop height and the shear force and IAP while compression force and erector muscle tension were more correlated with the power exertion of the participants than the drop height. With increasing SJ resistance, no significant increased risk of knee injury was detected. However, all low back variables except the IAP were significantly influenced by the increased resistance. Conclusion: Risk of injury in the knee and low back can be strongly dependent not only on the type of jump, but also the amount of resistance. The resulting power exerted by the athlete can also influence the risk of injury

Comparison of artificial neural network analysis with other multimarker methods for detecting genetic association

<p>Abstract</p> <p>Background</p> <p>Debate remains as to the optimal method for utilising genotype data obtained from multiple markers in case-control association studies. I and colleagues have previously described a method of association analysis using artificial neural networks (ANNs), whose performance compared favourably to single-marker methods. Here, the perfomance of ANN analysis is compared with other multi-marker methods, comprising different haplotype-based analyses and locus-based analyses.</p> <p>Results</p> <p>Of several methods studied and applied to simulated SNP datasets, heterogeneity testing of estimated haplotype frequencies using asymptotic <it>p </it>values rather than permutation testing had the lowest power of the methods studied and ANN analysis had the highest power. The difference in power to detect association between these two methods was statistically significant (<it>p </it>= 0.001) but other comparisons between methods were not significant. The raw <it>t </it>statistic obtained from ANN analysis correlated highly with the empirical statistical significance obtained from permutation testing of the ANN results and with the <it>p </it>value obtained from the heterogeneity test.</p> <p>Conclusion</p> <p>Although ANN analysis was more powerful than the standard haplotype-based test it is unlikely to be taken up widely. The permutation testing necessary to obtain a valid <it>p </it>value makes it slow to perform and it is not underpinned by a theoretical model relating marker genotypes to disease phenotype. Nevertheless, the superior performance of this method does imply that the widely-used haplotype-based methods for detecting association with multiple markers are not optimal and efforts could be made to improve upon them. The fact that the <it>t </it>statistic obtained from ANN analysis is highly correlated with the statistical significance does suggest a possibility to use ANN analysis in situations where large numbers of markers have been genotyped, since the <it>t</it> value could be used as a proxy for the <it>p </it>value in preliminary analyses.</p

Minor differences in haplotype frequency estimates can produce very large differences in heterogeneity test statistics

<p>Abstract</p> <p>Background</p> <p>Tests for association between a haplotype and disease are commonly performed using a likelihood ratio test for heterogeneity between case and control haplotype frequencies. Using data from a study of association between heroin dependence and the DRD2 gene, we obtained estimated haplotype frequencies and the associated likelihood ratio statistic using two different computer programs, MLOCUS and GENECOUNTING. We also carried out permutation testing to assess the empirical significance of the results obtained.</p> <p>Results</p> <p>Both programs yielded similar, though not identical, estimates for the haplotype frequencies. MLOCUS produced a p value of 1.8*10^-15and GENECOUNTING produced a p value of 5.4*10^-4. Permutation testing produced a p value 2.8*10^-4.</p> <p>Conclusion</p> <p>The fact that very large differences occur between the likelihood ratio statistics from the two programs may reflect the fact that the haplotype frequencies for the combined group are not constrained to be equal to the weighted averages of the frequencies for the cases and controls, as they would be if they were directly observed rather than being estimated. Minor differences in haplotype frequency estimates can result in very large differences in the likelihood ratio statistic and associated <it>p </it>value.</p