Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-12-03T19:11:33.495Z Has data issue: false hasContentIssue false

Feedback generation and linguistic knowledge in ‘SLIM’ automatic tutor

Published online by Cambridge University Press:  09 December 2002

RODOLFO DELMONTE
Affiliation:
Department of Language Sciences, Universitá Ca’ Foscari, Ca’ Garzoni-Moro – San Marco 3417, 30124 Venezia, [email protected]

Abstract

SLIM is a prototype interactive multimedia self-learning linguistic software for foreign language students at beginner-false beginner level. It allows students to work both in an autonomous self-directed mode or in a way of programmed learning in which the process of self-instruction is pre-programmed and monitored. In this latter mode it incorporates assessment and evaluation tools in order to behave as an automatic tutor. It is organized into three basic components: audiovisual materials; a linguistic database recording all language material in text format; the supervisor. Audiovisual materials are partially taken from commercially available courses; the linguistic database is a highly sophisticated classification of all words and utterances of the course, both in written and spoken form, from all possible linguistic aspects. The supervisor is both an attractive, enjoyable and strongly pedagogically based software that allows the user to work on language materials. The most outstanding feature of SLIM is the use of speech analysis and recognition which is a fundamental aspect of all second language learning programmes. We also assume that a learning model can be represented by a finite state automaton made up by a fixed number of possible states – corresponding to the macro and microlevels at which the student's competence may be modelled – each one being internally constituted by the actual linguistic objects of knowledge of the language that make it up.

Type
Research Article
Copyright
© 2002 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)