Using a maturity model to move student engagement practices beyond the generational approach

This paper proposes that the generational approach to conceptualising first year student learning behaviour, while it has made a very useful contribution to understanding that behaviour, can be expanded upon. The generational approach has an explicit focus on student behaviour and it is suggested that a capability maturity model interpretation may provide a complementary extension of that as it allows an assessment of institutional capability to initiate, plan, manage and evaluate institutional student engagement practices. The development of a Student Engagement, Success and Retention Maturity Model (SESR-MM) is discussed along with Australasian FYE generational data and Australian SESR-MM data

Correlating Architecture Maturity and Enterprise Systems Usage Maturity to Improve Business/IT Alignment

This paper compares concepts of maturity models in the areas of Enterprise Architecture and Enterprise Systems Usage. We investigate whether these concepts correlate, overlap and explain each other. The two maturity models are applied in a case study. We conclude that although it is possible to fully relate constructs from both kinds of models, having a mature architecture function in a company does not imply a high Enterprise Systems Usage maturity

Contract Aware Components, 10 years after

The notion of contract aware components has been published roughly ten years ago and is now becoming mainstream in several fields where the usage of software components is seen as critical. The goal of this paper is to survey domains such as Embedded Systems or Service Oriented Architecture where the notion of contract aware components has been influential. For each of these domains we briefly describe what has been done with this idea and we discuss the remaining challenges.Comment: In Proceedings WCSI 2010, arXiv:1010.233

A Review on Software Architectures for Heterogeneous Platforms

The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strategy adopted by industry was to increase the robustness of a single processor by increasing its clock frequency and mounting more transistors so more calculations could be executed. However, it is known that the physical limits of such processors are being reached, and one way to fulfill such increasing computing demands has been to adopt a strategy based on heterogeneous computing, i.e., using a heterogeneous platform containing more than one type of processor. This way, different types of tasks can be executed by processors that are specialized in them. Heterogeneous computing, however, poses a number of challenges to software engineering, especially in the architecture and deployment phases. In this paper, we conduct an empirical study that aims at discovering the state-of-the-art in software architecture for heterogeneous computing, with focus on deployment. We conduct a systematic mapping study that retrieved 28 studies, which were critically assessed to obtain an overview of the research field. We identified gaps and trends that can be used by both researchers and practitioners as guides to further investigate the topic

Modelling and Forecasting the Yield Curve under Model uncertainty

This paper proposes a procedure to investigate the nature and persistence of the forces governing the yield curve and to use the extracted information for forecasting purposes. The latent factors of a model of the Nelson-Siegel type are directly linked to the maturity of the yields through the explicit description of the cross-sectional dynamics of the interest rates. The intertemporal dynamics of the factors is then modeled as driven by long-run forces giving rise to enduring effects, and by medium- and short-run forces producing transitory effects. These forces are re-constructed in real time with a dynamic filter whose embedded feedback control recursively corrects for model uncertainty, including additive and parameter uncertainty and possible equation misspecifications and approximations. This correction sensibly enhances the robustness of the estimates and the accuracy of the out-of-sample forecasts, both at short and long forecast horizons. JEL Classification: G1, E4, C5Frequency decomposition, Model uncertainty, monetary policy, yield curve