Colette Dubuisson

Grammar, Order & Position of Wh-Signs in Quebec Sign Language

In the quest for language universals, one of the properties that linguists generally take to be universal is that a substantial portion of the lexical items are produced sequentially by speakers; i.e. are ordered in time. There are three aspects to word order: (1) a functional aspect; order conveys information about functional grouping of words and provides some indication of how to interpret sentences; (2) an articulatory aspect; some order is required because more than one sound cannot usually be produced at a time; (3) an order aspect; linguistic theories postulate either that a language has a basic order determined by universal principles, or that there is a single universal order for all languages. On the basis of data from sign languages we argue that this third property is not universal in either of its formulations. There are other means that a language can use to indicate what elements combine functionally and in that case the language has no specific order imposing these combinations. We therefore consider that not all languages have a basic order and that only languages in which word order has an important functional role will exhibit a basic order.

CATEGORIES IN QUEBEC SIGN LANGUAGE: REFLECTIONS ON CATEGORIZATION ACROSS MODALITIES

Our goal in this chapter is twofold. First, we describe some basic properties of categorization in Langue des Signes Quebecoise (Quebec Sign Language: LSQ). Second, properties of the gestural modality of a sign language seem to bring about a categorization different from that induced by the modality of an oral language; therefore, we explore some consequences for the categorization of linguistic material in general and the nature of “universality” in linguistics.

Création du logiciel d’alphabétisation bilingue pour les Sourds “Le français sur le bout des doigts”: évaluation de l’outil et de la démarche de développement

Designed for a literate, hearing clientele, traditional CALL tools do not necessarily meet the needs of deaf people, and are not adapted to their learning styles, especially in the area of literacy. Current developments lead us to believe that, in order for deaf people to subscribe to literacy campaigns and to ensure that such measures are efficient, two conditions must be met: Quebec Sign Language must be the language of instruction (Dubuisson et al., 1997) and the participation of deaf people must be felt at every stage of the development of course material. Research has shown that in architecture, for example, the participation of the target clientele in the design process of the product can lead to the emergence of significant solutions (Vezeau et al., 1999). In light of the quantity of Web systems and products that are hardly used or difficult to use, Rubin (1994) reminds us of the need to consider the user, and not only the machine or the system, in the development process. The main goal of our research is to establish design parameters (developmental process, type of software, and content) for CALL software aimed at deaf adults. Only the data relating to the developmental process will be presented here. We will analyze and discuss the responses obtained through interviews with deaf members of the development team, audiotapes (on which an interpreter recorded the words of the team members), and videotapes of meetings. The interpretation of this data will give way to a qualitative assessment of the efficiency of the approach in the development of material adapted to the needs of the target population.

USING THE INTELLIGENT COMPUTER-AIDED LEARNING SYSTEM “G” IN LINGUISTICS

G is a Computer Aided Learning system based Artificial Intelligence concepts. However, G is not an expert system and is not devoted to a particular field or subject. G is based on 3 main models: The content, the so-called pedagogical tools and the learner. Content units, pedagogical tools and other features are related; they are implemented as objects within a procedural data base. The learner model is fuzzy, it is build bynamically and includes levels of pertinence for content units and skills. G does not permit the definition of a scenario or preprogrammed path within the content. Learning is achieved within a dialog between learner and machine, both learner and machine using questions and answers. Dialog is in natural language.