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.     

Development of School Attendance Difficulties: An Exploratory Study

This article discusses aspects of school attendance difficulties, focusing on why a minority of children decide to miss school. It is an exploratory study representing a developmental approach that aims to establish the immediate determinants of school absence to gain more understanding of the nature of attendance difficulties and eventually inform practitioner methods. Questionnaires, designed to measure attitudes, perceptions and parent–child interaction over school absence were administered to two hundred and nine 12–13 year olds attending a comprehensive school. Thirty-five individual interviews were carried out with good and poor attenders to clarify the questionnaire responses. It was concluded that school attendance difficulties develop like other defiant behaviour problems, with parental reaction playing a major role. Government policies encouraging the use of punitive measures with parents of poor attenders do not provide practitioners or pastoral staff with the sophisticated working methods necessary to help poor attending children achieve an education.     

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.     

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.