A pattern language for goals

Previous work has established the value of goal-oriented approaches to requirements engineering. Achieving clarity and agreement about stakeholders’ goals and assumptions is critical for building successful software systems and managing their subsequent evolution. In general, this decision-making process requires stakeholders to understand the implications of decisions outside the domains of their own expertise. Hence it is important to support goal negotiation and decision making with description languages that are both precise and expressive, yet easy to grasp. This paper presents work in progress to develop a pattern language for describing goal refinement graphs. The language has a simple graphical notation, which is supported by a prototype editor tool, and a symbolic notation based on modal logic.

The language of poverty: an exploration of the narratives of the poor

Within the development discourse, the narratives of the poor are a well utilized rhetorical tool to describe poverty and its causes. However, narratives can also reveal the beliefs and ‘world-view’ of the narrators. To explore this influence, the authors applied a discursive approach, to deconstruct the narratives of 101 slum dwellers in Kibera, Nairobi. The results revealed that poverty was largely attributed to external constraints, beyond an individual's control. Despite wanting a better life, participants held low expectations for the future. Hopes and dreams were placed on their children. While risk and uncertainty was a constant theme, large differences were found between genders as to the aspirations for the future. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment.

'Your secret language': classics in the British colonies of West Africa

What were the cultural politics of classics in British colonies? Did classical education operate as a sign of oppression, or as a tool for forging an anti-colonial politics? Why did Europeans bring the classics to West Africa, and how did they manage the developing dynamic when West Africans laid independent claim to the classical heritage? This ground-breaking study examines the ways in which European colonisers and West African nationalists clashed, or collaborated, over the uses of Latin, Greek and the classics.

An overview of mixed-effects statistical models for second language researchers

As in any field of scientific inquiry, advancements in the field of second language acquisition (SLA) rely in part on the interpretation and generalizability of study findings using quantitative data analysis and inferential statistics. While statistical techniques such as ANOVA and t-tests are widely used in second language research, this review article provides a review of a class of newer statistical models that have not yet been widely adopted in the field, but have garnered interest in other fields of language research. The class of statistical models called mixed-effects models are introduced, and the potential benefits of these models for the second language researcher are discussed. A simple example of mixed-effects data analysis using the statistical software package R (R Development Core Team, 2011) is provided as an introduction to the use of these statistical techniques, and to exemplify how such analyses can be reported in research articles. It is concluded that mixed-effects models provide the second language researcher with a powerful tool for the analysis of a variety of types of second language acquisition data.

The utility and application of mixed-effects models in second language research

Second language acquisition researchers often face particular challenges when attempting to generalize study findings to the wider learner population. For example, language learners constitute a heterogeneous group, and it is not always clear how a study’s findings may generalize to other individuals who may differ in terms of language background and proficiency, among many other factors. In this paper, we provide an overview of how mixed-effects models can be used to help overcome these and other issues in the field of second language acquisition. We provide an overview of the benefits of mixed-effects models and a practical example of how mixed-effects analyses can be conducted. Mixed-effects models provide second language researchers with a powerful statistical tool in the analysis of a variety of different types of data.