Empowering Expression for Users with Aphasia through Constrained Creativity

Creative activities allow people to express themselves in rich, nuanced ways. However, being creative does not always come easily. For example, people with speech and language impairments, such as aphasia, face challenges in creative activities that involve language. In this paper, we explore the concept of constrained creativity as a way of addressing this challenge and enabling creative writing. We report an app, MakeWrite, that supports the constrained creation of digital texts through automated redaction. The app was co-designed with and for people with aphasia and was subsequently explored in a workshop with a group of people with aphasia. Participants were not only successful in crafting novel language, but, importantly, self-reported that the app was crucial in enabling them to do so. We refect on the potential of technology-supported constrained creativity as a means of empowering expression amongst users with diverse needs

Specifying Logic Programs in Controlled Natural Language

Writing specifications for computer programs is not easy since one has to take into account the disparate conceptual worlds of the application domain and of software development. To bridge this conceptual gap we propose controlled natural language as a declarative and application-specific specification language. Controlled natural language is a subset of natural language that can be accurately and efficiently processed by a computer, but is expressive enough to allow natural usage by non-specialists. Specifications in controlled natural language are automatically translated into Prolog clauses, hence become formal and executable. The translation uses a definite clause grammar (DCG) enhanced by feature structures. Inter-text references of the specification, e.g. anaphora, are resolved with the help of discourse representation theory (DRT). The generated Prolog clauses are added to a knowledge base. We have implemented a prototypical specification system that successfully processes the specification of a simple automated teller machine.Comment: 16 pages, compressed, uuencoded Postscript, published in Proceedings CLNLP 95, COMPULOGNET/ELSNET/EAGLES Workshop on Computational Logic for Natural Language Processing, Edinburgh, April 3-5, 199

Maximising the impact of careers services on career management skills: a review of the literature

The review identified an international body of work on the development and implementation of competency frameworks in reaction to CMS, including the ‘Blueprint’ frameworks, which are a series of inter-related national approaches to career management skills (originating in the USA and taken up subsequently, and with different emphases, by Canada, Australia, England and Scotland). There is, as yet, little empirical evidence to support the overall efficacy of CMS frameworks, but they have the advantage of setting out what needs to be learned (usually as a clear and identifiable list of skills, attributes and attitudes) and, often, how this learning is intended to happen. The international literature emphasised the iterative nature and mixture of formal and informal learning and life experiences that people needed to develop CMS. It suggested that, though there was no single intervention or group of interventions that appeared most effective in increasing CMS, there were five underpinning components of career guidance interventions that substantially increased effectiveness, particularly when combined. These included the use of narrative/writing approaches; the importance of providing a ‘safe’ environment; the quality of the adviser-client relationship; the need for flexibility in approach; the provision of specialist information and support; and clarity on the purpose and aims of action planning. The review also identified a possible emergent hierarchy around the efficacy of different modes of delivery of career guidance interventions on CMS development. Interventions involving practitioner contact and structured groups appeared more effective than self-directed interventions or unstructured groups. Computer-based interventions were found to work better when practitioner input was provided during the intervention or when they were followed up by a structured workshop session to discuss and review the results.Skills Funding Agenc