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

@article{Amaral2011OnUI,
  title={On using intelligent computer-assisted language learning in real-life foreign language teaching and learning},
  author={Luiz A. Amaral and Walt Detmar Meurers},
  journal={ReCALL},
  year={2011},
  volume={23},
  pages={4 - 24}
}
Abstract This 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… 
Language learning tasks and automatic analysis of learner language : connecting FLTL and NLP design of ICALL materials supporting use in real-life instruction
TLDR
The results show that teachers can characterise, author and employ ICALL materials as part of their instruction programme, and that the underlying computational machinery can provide the required automatic processing with sufficient efficiency.
Form and meaning in dialog-based computer-assisted language learning
TLDR
There are small differences in the language skill development afforded by different types of computer-provided instruction, and it is found that constrained, explicit form-oriented instruction yields in general greater immediate learning gains, while the free, more implicit and meaning- oriented instruction yields more delayed effects.
Computer assisted language learning : an outline and discussion of current issues
This paper gives a brief overview of current issues and recent developments in the field of computer assisted language learning (CALL) and intelligent computer assisted language learning (ICALL). We
Automatic proficiency level prediction for Intelligent Computer-Assisted Language Learning
TLDR
This thesis work proposes a framework for selecting sentences suitable as exercise items which encompasses a number of additional criteria such as well-formedness and independence from a larger textual context, and shows that models trained partly or entirely on reading texts can effectively predict the proficiency level of learner essays.
Computer-assisted language learning (CALL) in support of (re)-learning native languages: the case of Runyakitara
TLDR
Results from the evaluation study indicate that RU_CALL has the ability to assess users’ knowledge of Runyakitara and to enhance grammar and writing skills in the language.
The intelligent integrated computer-assisted language learning (iiCALL) environment: work in progress
TLDR
The paper shows the needs from the perspective of learner types, it gives a technological overview, and it points out the current system architecture of the iiCALL environment.
Computer Assisted Language Learning (CALL) in support of (re)-learning native languages: the case of Runyakitara
This study presents the results from a CALL system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue
Analyzing learner language: towards a flexible natural language processing architecture for intelligent language tutors
TLDR
It is argued that a demand-driven, annotation-based natural language processing (NLP) architecture is well-suited to handle the demands posed by the heterogeneous learner input which results when supporting a wider range of FLT activity types.
Intelligent tutoring systems for language learning
  • Vanja Slavuj, Bozidar Kovacic, Igor Jugo
  • Computer Science
    2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
  • 2015
TLDR
The paper at hand outlines and briefly discusses the issues surrounding the development and use of ITSs for language learning, taking also into account the broader context of (I)CALL, and gives an overview of such systems already in use.
Intelligent Sentence Writing Tutor: A System Development Cycle
TLDR
This article focuses on the use of natural language processing NLP to facilitate second language learning within the context of academic English and establishes links to previous and concurrent research in the fields of second language acquisition and ICALL intelligent computer assisted language learning.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 99 REFERENCES
Designing intelligent language tutoring systems for integration into foreign language instruction
TLDR
The overall contribution of the project is to take a concrete step in the direction of bridging the gap between the development of NLP technology for ICALL and the actual use of such technology in real life foreign language programs.
Intelligent Tutoring Systems for Foreign Language Learning
TLDR
The results of experiments show that a specific CALL program, STORYBOARD, is of interest both as a traditional text reconstruction exercise and as a tool in second language writing activities.
Intelligent Tutoring Systems for Foreign Language Learning: The Bridge to International Communication
TLDR
This book presents readers with the state of the art in the field in a single volume, with contributors from computer science, linguistics, and psychology.
Analyzing learner language: towards a flexible natural language processing architecture for intelligent language tutors
TLDR
It is argued that a demand-driven, annotation-based natural language processing (NLP) architecture is well-suited to handle the demands posed by the heterogeneous learner input which results when supporting a wider range of FLT activity types.
Intelligent Computer Feedback for Second Language Instruction
TLDR
If the potential of computer-assisted language instruction as individualized supervised learning is to be realized, programs that support detailed error analysis and feedback targeted to specific deficiencies in the student’s performance must be developed.
An intelligent tutoring system for deaf learners of written English
TLDR
Progress is described toward a prototype implementation of a system that will take a piece of text written by a deaf student, analyze that text for grammatical errors, and engage that student in a tutorial dialogue, enabling the student to generate appropriate corrections to the text.
Revisiting current paradigms in computer assisted language learning research and development
TLDR
The current state-of-the-art in in the field is discussed and a more inclusive approach to design and implement CALL projects is proposed.
From recording linguistic competence to supporting inferences about language acquisition in context
TLDR
A student model that includes a representation of the learner's ability to use language in context and to perform tasks, as well as for an explicit activity model that provides information on the language tasks and the inferences for the student model they support are argued.
Analyzing Learner Language : Towards A Flexible NLP Architecture for Intelligent Language Tutors
Intelligent Language Tutoring Systems (ILTS) typically focus on analyzing learner input to diagnose learner errors and provide individualized feedback. Despite a long history of ILTS research (cf.
Computer vs. Workbook Instruction in Second Language Acquisition
TLDR
The results of the study show that given the same grammar notes and exercises, ongoing intelligent computer feedback is more effective than simple workbook answer sheets for developing learners' grammatical skill in producing Japanese particles and sentences.
...
1
2
3
4
5
...