Towards user/system collaboration in developing a student model for intelligent computer assisted language learning

ReCALL ◽  
1993 ◽  
Vol 5 (8) ◽  
pp. 3-8 ◽  
Author(s):  
Susan Bull
Keyword(s):  
Collaborative Learning ◽  
Language Learning ◽  
Approaches To Learning ◽  
Current Work ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Student Model ◽  
Accurate Representation ◽  
Model Based ◽  
Intelligent Computer

This paper examines research in the field of collaborative learning, concentrating on aspects suitable for use in an intelligent computer assisted language learning (ICALL) system. Current work on the project focuses on the construction of a student model, based on the notion that a model constructed and repaired through collaboration between the system and student will lead to a more accurate representation of the learner's beliefs, and is less likely to be regarded with suspicion by the student. Further, the act of collaboration should promote reflection on both the language to be learnt and the student's approaches to learning.

Learning languages: Implications for student modelling in ICALL

ReCALL ◽  
1994 ◽  
Vol 6 (1) ◽  
pp. 34-39 ◽  
Author(s):  
Susan Bull
Keyword(s):  
Second Language Acquisition ◽  
Language Learning ◽  
Approaches To Learning ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Student Model ◽  
Traditional Student ◽  
Student Models ◽  
Learning Software ◽  
Great Burden

Many factors affect the learning of a foreign language. When designing computer assisted language learning software it is usually not sufficient to think only about creating an exercise in the language, but students should be modelled in order to allow the program to take account of individuals' beliefs and learning. However, student models are criticised for various reasons, the most common of which include: 1. Modelling the learner places a great burden on the system, as it has sole responsibility for the creation of an accurate student model. 2. Student models are inadequate because it is not possible to model all aspects of a student's knowledge and learning. This paper describes the student model of an intelligent computer assisted language learning (ICALL) system which strives to overcome problems of traditional student models by taking into account issues important in the field of second language acquisition, and research in collaborative approaches to learning.

LANGUAGE LEARNING THROUGH SOCIAL COMPUTING: OCCASIONAL PAPERS OF THE APPLIED LINGUISTICS ASSOCIATION OF AUSTRALIA, 16.Robert Debski, June Gassin, and Mike Smith (Eds.). Melbourne: ALAA & The Horwood Language Centre, 1997. Pp. viii + 224. A$12.00 paper.

1999 ◽  
Vol 21 (3) ◽  
pp. 502-503
Author(s):  
Carol A. Chapelle
Keyword(s):  
Collaborative Learning ◽  
Language Learning ◽  
Teaching And Learning ◽  
Classroom Practices ◽  
Social Computing ◽  
Applied Linguistics ◽  
Target Language ◽  
The Internet ◽  
Computer Assisted ◽  
Computer Assisted Language Learning

The papers in Language learning through social computing introduce the classroom practices and philosophical underpinnings of computer-assisted language learning (CALL), which builds on collaborative approaches to L2 teaching and learning. The majority of the essays address general issues in collaborative learning through CALL, describing the authors' experience and reflections on L2 activities designed to engage learners in interesting discussions and projects, many of which rely on target language materials from the Internet.

On using intelligent computer-assisted language learning in real-life foreign language teaching and learning

ReCALL ◽  
2011 ◽  
Vol 23 (1) ◽  
pp. 4-24 ◽  
Author(s):  
Luiz A. Amaral ◽  
Detmar Meurers
Keyword(s):  
Foreign Language ◽  
Language Learning ◽  
Teaching And Learning ◽  
Language Teaching ◽  
Foreign Language Teaching ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Intelligent Computer ◽  
Activity Design ◽  
Language Teaching And Learning

AbstractThis paper explores the motivation and prerequisites for successful integration of Intelligent Computer-Assisted Language Learning (ICALL) tools into current foreign language teaching and learning (FLTL) practice. We focus on two aspects, which we argue to be important for effective ICALL system development and use: (i) the relationship between activity design and restrictions needed to make natural language processing tractable and reliable, and (ii) pedagogical considerations and the influence of activity design choices on the integration of ICALL systems into FLTL practice.

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