The Role of Extended Time and Item Content on a High‐Stakes Mathematics Test

The premise of a great deal of current research guiding policy development has been that accommodations are the catalyst for student performance differences. Rather than accepting this premise, two studies were conducted to investigate the influence of extended time and content knowledge on the performance of ninth‐grade students who took a statewide mathematics test with and without accommodations. Each study involved 1,250 accommodated students (extended time only) with learning disabilities and 1,250 nonaccommodated students demonstrating no disabilities. In Study One, a standard differential item functioning (DIF) analysis illustrated that the usual approach to studying the effects of accommodations contributes little to our understanding of the reason for performance differences across students. Next, a mixture item response theory DIF model was used to explore the most likely cause(s) for performance differences across the population. The results from both studies suggest that students for whom items were functioning differently were not accurately characterized by their accommodation status but rather by their content knowledge. That is, knowing students' accommodation status (i.e., accommodated or nonaccommodated) contributed little to understanding why accommodated and nonaccommodated students differed in their test performance. Rather, the data would suggest that a more likely explanation is that mathematics competency differentiated the groups of student learners regardless of their accommodation and/or reading levels.     

The invisible impact of educational research

Although there are policy calls for educational research to discover ‘what works’ and thereby inform decision making directly, the research literature argues instead for research to have a ‘conceptual’ impact on practice. Empirical studies also suggest that, when teachers use research, their use is conceptual; research influences the content and the process of their thinking, changing attitudes and perceptions and making educational decision making more intelligent. This study investigates the ways in which educational research has achieved impact on practice from the perspective of the researchers. A sample of highly-rated impact case studies in the UK’s research assessment exercise (REF2014) were subject to content analysis, using qualitative coding techniques. Analysis shows that most research is ‘invisible’ to education practitioners because it is embedded in educational policies, technologies, and services. This ‘invisible use’ is unlikely to realise the conceptual benefits claimed for research utilisation. If educational research is to make educational decision making more intelligent at its point of use, it will be necessary to re-think current notions of quality in research impact.     

Does a focal firm's technology entry timing depend on the impact of the technology on co-opetitors?

In this paper, I explore the role that the impact of a technological change on a firm's co-opetitors plays in the firm's technology entry timing. I hypothesize that where a co-opetitor dominates in the co-opetitor-firm relationship, a firm's technology entry timing does not depend on the impact of the technology on the firm's capabilities as predicted by previous research. Rather, it depends on the impact of the change on the dominant co-opetitor. If the change is incremental to a dominant customer, for example, the focal incumbent firm will start development of the new technology before new entrants, irrespective of whether it is radical or incremental to focal firms. If the change is radical to the dominant co-opetitor, new entrant focal firms will start development of the new technology before incumbent focal firms. I explore these hypotheses using the case of three major technological changes in supercomputers: vector processors, minisupercomputers, and massively parallel processors.     

Exploring the experience of ten Australian Honours students

Honours study is viewed as a transition from undergraduate to postgraduate study and/or to enhanced career prospects. In Australia, Honours is usually an adjunct to the standard undergraduate degree. This paper provides an ethnographic study of 10 Australian Honours students. Seeing their experience through their reflections, in their own voices, reveals that Honours may be more than transitional – these students were transformed personally. Such emotionally charged transformations require academics to reflect on the best forms of support for Honours students.     

How home gets to school: Parental control strategies predict children's school readiness

At-risk families’ control style (autonomy support and coercive control) was examined in relation to children's school readiness; children's social skills and mastery motivation were hypothesized mediating variables. In two different, low-income samples from diverse ethnic backgrounds, one preschool sample recruited from Head Start (N = 199) and a school transition sample composed of children entering elementary school (N = 344), parental control styles were related to children's academic readiness modestly but significantly in the preschool sample and weakly in the school transition sample. Children's social skills and mastery motivation skills (persistence and goal orientation) were significantly related to the academic measures of school readiness, and fully mediated the association between parents’ use of coercive behavioral control and academic readiness. Such mediation could not be tested for parental support of children's autonomy. The results indicate that a developmental cascade exists between parental control strategies and academic indices of school readiness, emphasizing the importance of family context models of school readiness. Furthermore, strong correlations between the domains of school readiness were found in both samples, reinforcing calls for a multidimensional approach to supporting school readiness in early childhood education programs.     

Spurious Latent Classes in the Mixture Rasch Model

Mixture Rasch models have been used to study a number of psychometric issues such as goodness of fit, response strategy differences, strategy shifts, and multidimensionality. Although these models offer the potential for improving understanding of the latent variables being measured, under some conditions overextraction of latent classes may occur, potentially leading to misinterpretation of results. In this study, a mixture Rasch model was applied to data from a statewide test that was initially calibrated to conform to a 3‐parameter logistic (3PL) model. Results suggested how latent classes could be explained and also suggested that these latent classes might be due to applying a mixture Rasch model to 3PL data. To support this latter conjecture, a simulation study was presented to demonstrate how data generated to fit a one‐class 2‐parameter logistic (2PL) model required more than one class when fit with a mixture Rasch model.     

Corresponding drivability control and energy control strategy in uninterrupted multi-speed mining trucks

An hybrid uninterrupted multi-speed transmission (HUMST), based on the integration of a planetary gear set and a 3-speed automatic manual transmission (3-AMT), is developed to satisfy the specific performance indexes of mining trucks. The power-split device can alleviate and eliminate the inherent torque interruption of the 3-AMT during gear shift by implementing the designed cooperative shift control strategy which is optimized by quadratic performance index. In order to achieve fast torque coordination while guaranteeing the driving comfort performance, the torque profiles of the power split device and the traction motor are optimized by Linear-quadratic regulator (LQR) algorithm. Dynamic programming (DP) is implemented as a benchmark to demonstrate the maximum fuel efficiency of the proposed HUMST. Because of the high computational cost of optimal control strategies such as DP, an improved real-time control strategy (IRTCS) using modified Gaussian distribution function is proposed to significantly reduce the computing load. As efficiency-oriented energy control strategy would result in frequent gear shifts, to achieve a desirable tradeoff between the overall efficiency and the shift stability, multi-objective genetic algorithm (MGA) is integrated to optimize the overall performance. The detail mathematical and dynamic model shows that the proposed shifting strategy with LQR can effectively suppress shift jerk, and the proposed IRTCS with MGA can reduce shift frequency by 70.78% to improve the drivability, only sacrificing 4.86% of overall efficiency compared to that of DP.