Educational technology, reimagined

"Educational technology" is often equated in the popular imagination with "computers in the schools." But technology is much more than merely computers, and education is much more than mere schooling. The landscape of child-accessible technologies is blossoming in all sorts of directions: tools for communication, for physical construction and fabrication, and for human-computer interaction. These new systems and artifacts allow educational designers to think much more creatively about when and where learning takes place in children's lives, both within and outside the classroom.     

The potential for bias in reporting of industry-sponsored clinical trials

Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.     

Decision-making under uncertainty: using MLMC for efficient estimation of EVPPI

Statistics and Computing - In this paper, we develop a very efficient approach to the Monte Carlo estimation of the expected value of partial perfect information (EVPPI) that measures the average...     

Use of Sensitivity Analysis to Assess Reliability of Metabolic and Physiological Models

Because ethical considerations often preclude directly determining the human health effects of treatments or interventions by experimentation, such effects are estimated by extrapolating reactions predicted from animal experiments. Under such conditions, it must be demonstrated that the reliability of the extrapolated predictions is not excessively affected by inherent data limitations and other components of model specification. This is especially true of high-level models composed of ad hoc algebraic equations whose parameters do not correspond to specific physical properties or processes. Models based on independent experimental data restricting the numerical space of parameters that do represent actual physical properties can be represented at a more detailed level. Sensitivities of the computed trajectories to parameter variations permit more detailed attribution of uncertainties in the predictions to these low-level properties. S-systems, in which parameters are estimated empirically, and physiological models, whose parameters can be estimated accurately from independent data, are used to illustrate the applicability of trajectory sensitivity analysis to lower-level models.     

Enabling high-dimensional range queries using <Emphasis Type="Italic">k</Emphasis>NN indexing techniques: approaches and empirical results

Many modern search applications are high-dimensional and depend on efficient orthogonal range queries. These applications span web-based and scientific needs as well as uses for data mining. Although k-nearest neighbor queries are becoming increasingly common due to mobile and geospatial applications, orthogonal range queries in high-dimensional data remain extremely important and relevant. For efficient querying, data is typically stored in an index optimized for either kNN or range queries. This can be problematic when data is optimized for kNN retrieval and a user needs a range query or vice versa. Here, we address the issue of using a kNN-based index for range queries, as well as outline the general computational geometry problem of adapting these systems to range queries. We refer to these methods as space-based decompositions and provide a straightforward heuristic for this problem. Using iDistance as our applied kNN indexing technique, we also develop an optimal (data-based) algorithm designed specifically for its indexing scheme. We compare this method to the suggested naïve approach using real world datasets. The data-based algorithm consistently performs better.     

Of Journal Editors and Editorial Boards: Who Are the Trailblazers in Increasing Editorial Board Gender Equality?

Female academics continue to be under‐represented on the editorial boards of many, but not all, management journals. This variability is intriguing, because it is reasonable to assume that the size of the pool of female faculty available and willing to serve on editorial boards is similar for all management journals. This paper therefore focuses on the characteristics of the journal editors to explain this variability; journal editors or editors‐in‐chief are the most influential people in the selection of editorial board members. The authors draw on social identity and homosocial reproduction theories, and on the gender and careers literature to examine the relationship between an editor's academic performance, professional age and gender, and editorial board gender equality. Longitudinal data are collected at five points in time, using five‐year intervals, from 52 management journals. To account for the nested structure of the data, a three‐level multilevel model was estimated. Overall, it is found that the prospects of board membership improve for women when editors are high‐performing, professionally young or female. The authors discuss these findings and their implications for management journals with low, stagnant or declining representation of women in their boards.