Schools, teachers, and curriculum change: A balancing act?

Educational change is a fact of life for teachers across the world, as schools are subjected to constant and ubiquitous pressures to innovate. And, yet, many school practices remain remarkably persistent in the face of such innovation. This paradox of innovation without change is perplexing for policymakers and practitioners alike. This paper investigates the gap between policy and practice, between innovation and the changes in social practices that occur in response to such innovation. It draws upon empirical data from two case studies in Scotland — schools responding to new curriculum policy—exploring contrasting approaches to the management of innovation. One is a laissez faire approach, and the other a more directive managerial strategy. Through an analytical separation of culture, structure, and agency, derived from the social theory of Margaret Archer, the paper sheds light on the social processes that accompanied innovation in these two settings demonstrating how teacher culture and differing management styles impact upon externally initiated policy

Empowerment of the European Parliament

One of the most remarkable democratic developments in Europe in recent decades has been the empowerment of the only directly elected supranational assembly in the world: the European Parliament (EP). We first review the development of the legislative powers of the EP vis-à-vis the other European Union (EU) institutions, discussing the theoretical models of the power of the EP and the main empirical methods that have been used to evaluate these models. We then turn to the impact of the growing power of the EP on political organization and behavior inside the legislature. We demonstrate that the "electoral connection" is weak and discuss what this means for understanding legislative politics in the EP. The concluding section demonstrates differences in behavior across policy areas, which have received scant attention, and suggests avenues for further research

Performance-based structural health monitoring through an innovative hybrid data interpretation framework

The utilization of Structural Health Monitoring (SHM) for performance-based evaluation of structural systems requires the integration of sensing with appropriate data interpretation algorithms to establish an expected performance related to damage or structural change. In this study, a hybrid data interpretation framework is proposed for the long-term performance assessment of structures by integrating two data analysis approaches: parametric (model-based, physics-based) and non-parametric (data-driven, model-free) approaches. The proposed framework employs a network of sensors through which the performance of the structure is evaluated and the corresponding maintenance action can be efficiently taken almost in real-time. The hybrid algorithm proposed can be categorized as a supervised classification algorithm. In the training phase of the algorithm, a Monte-Carlo simulation technique along with Moving Principal Component Analysis (MPCA) and hypothesis testing are employed for simulation, signal processing, and learning the underlying distribution, respectively. The proposed approach is demonstrated and its performance is evaluated through both analytical and experimental studies. The experimental study is performed using a laboratory structure (UCF 4-Span Bridge) instrumented with a Fiber Brag Grating (FBG) system developed in-house for collecting data under common bridge damage scenarios. The proposed hybrid approach holds potential to significantly enhance sensor network design, as well as continuous evaluation of the structural performance