INTELLIGENT LANGUAGE TUTORS: THEORY SHAPING TECHNOLOGY.V. Melissa Holland, Jonathan D. Kaplan, & Michelle R. Sams (Eds.). Mahwah, NJ: Erlbaum, 1995. Pp. xviii + 384. $79.95 cloth, $39.95 paper.

1998 ◽  
Vol 20 (3) ◽  
pp. 445-446
Author(s):  
Mark Warschauer
Keyword(s):  
Artificial Intelligence ◽  
Second Language Acquisition ◽  
Language Learning ◽  
Learning Environments ◽  
Language Processing ◽  
Language Games ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Second Language Acquisition Theory ◽  
Intelligent Computer

This book presents and discusses efforts to develop Intelligent Computer Assisted Language Learning (ICALL) programs based on advances in artificial intelligence (AI) and natural language processing (NLP). Sixteen of the book's 20 chapters provide descriptions of particular ICALL programs, divided into three categories: text-based language tutors and learning environments, dialogue-based language games, and graphics-based language tutors and learning environments. Four chapters at the end offer general commentary on ICALL from the perspectives of experimental psychology (by Brian MacWhinney), linguistics and AI (by Alan Bailin), second language acquisition theory (by Nina Garret), and educational theory (by Rebecca Oxford).

An Environment for Learner Corpus Research and Error Analysis

2014 ◽  
Vol 4 (3) ◽  
pp. 34-51 ◽  
Author(s):  
Larraitz Uria ◽  
Montse Maritxalar ◽  
Igone Zabala
Keyword(s):  
Error Analysis ◽  
Language Learning ◽  
Language Learners ◽  
Language Processing ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Learner Corpus ◽  
Depth Study ◽  
Points Of View ◽  
Intelligent Computer

This article presents an environment developed for Learner Corpus Research and Error Analysis which makes it possible to deal with language errors from different points of view and with several aims. In the field of Intelligent Computer Assisted Language Learning (ICALL), our objective is to gain a better understanding of the language learning process. In the field of Natural Language Processing (NLP), we work on the development of applications that will help both language learners and teachers in their learning/teaching processes. Using this environment, several studies and experiments on error analysis have been carried out, and thanks to an in-depth study on determiner-related errors in Basque, some contributions in the above mentioned fields of research have been made.

Providing graduated corrective feedback in an intelligent computer-assisted language learning environment

ReCALL ◽  
2017 ◽  
Vol 29 (3) ◽  
pp. 313-334 ◽  
Author(s):  
Haiyang Ai
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Learning ◽  
Corrective Feedback ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
L2 Development ◽  
Design Effectiveness ◽  
Intelligent Computer ◽  
Scholarly Attention

AbstractCorrective feedback (CF), a response to linguistic errors made by second language (L2) learners, has received extensive scholarly attention in second language acquisition. While much of the previous research in the field has focused on whether CF facilitates or impedes L2 development, few studies have examined the efficacy of gradually modifying the explicitness or specificity of CF as a function of a learner’s response to the feedback. Yet, the type and extent of CF needed by a learner, as suggested by Vygotsky (1978), sheds light on whether a learner is developing his or her abilities in a particular area and the ways in which they do it. This paper reports on a study that explores the design, effectiveness and learners’ perception toward agraduated(Aljaafreh & Lantolf, 1994) approach to CF, i.e., feedback that progresses from very general and implicit to very specific and explicit, in an intelligent computer-assisted language learning (ICALL) environment. The results show that the graduated approach to CF is effective in helping learners to self-identify and self-correct a number of grammatical issues, although an onsite tutor provides necessary remedies when the ICALL system occasionally fails to do its part. Implications for CF research, particularly on the notion of individualized feedback, are also discussed.

scholarly journals Joining the blocks together – an NLP pipeline for CALL development

2019 ◽  
pp. 397-401
Author(s):  
Monica Ward
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Computational Linguistics ◽  
Language Processing ◽  
Learning Process ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Tools And Techniques ◽  
Intelligent Computer

Intelligent Computer-Assisted Language Learning (ICALL) involves using tools and techniques from computational linguistics and Natural Language Processing (NLP) in the language learning process. It is an inherently complex endeavour and is multi-, inter-, and trans-disciplinary in nature. Often these tools and techniques are designed for tasks and purposes other than language learning, and this makes their adaptation and use in the CALL domain difficult. It can be even more challenging for Less-Resourced Languages (LRLs) for CALL researchers to adapt or incorporate NLP into CALL artefacts. This paper reports on how two existing NLP resources for Irish, a morphological analyser and a parser, were used to develop an app for Irish. The app, Irish Word Bricks (IWB), was adapted from an existing CALL app – Word Bricks (Mozgovoy & Efimov, 2013). Without this ‘joining the blocks together’ approach, the development of the IWB app would certainly have taken longer, may not have been as efficient or effective, and may not even have been accomplished at all.

scholarly journals An iCALL approach to morphophonemic training for Irish using speech technology

2019 ◽  
pp. 314-320
Author(s):  
Neasa Ní Chiaráin ◽  
Ailbhe Ní Chasaide
Keyword(s):  
Language Learning ◽  
Language Processing ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Digital Learning ◽  
Aural Skills ◽  
Speech Technology ◽  
Learning Platforms ◽  
Synthetic Voices ◽  
Intelligent Computer

A key benefit in intelligent Computer Assisted Language Learning (iCALL) is that it allows complex linguistic phenomena to be incorporated into digital learning platforms, either for the autonomous learner or to complement classroom teaching. The present paper describes (1) complex phonological/morphophonemic alternations of Irish, which are problematic for many learners; (2) an iCALL platform, An Scéalaí, which uses speech technology and Natural Language Processing (NLP) prompts to train writing and aural skills – in this paper the target is the morphophonemic alternations of (1); and (3) a perception experiment to guide how the platform might be used for prompt-based self-correction. The perception experiment has been carried out using newly built synthetic voices based on deep neural network technology.

Call–Non-English L2 Instruction

1996 ◽  
Vol 16 ◽  
pp. 158-181 ◽  
Author(s):  
K. Bernd Conrad
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Learning ◽  
Foreign Language Learning ◽  
Theory And Practice ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
International Perspectives ◽  
Work Done ◽  
Second Language Acquisition Theory

Research in computer-assisted language learning (CALL) has neither traditionally nor recently had a language or setting-specific emphasis, one that would have established a distinction between second language learning (SLL) as opposed to foreign language learning (FLL) applications in its attempts to answer principled CALL questions. For example the two anthologies of essays, studies, and reports on CALL theory and practice by Smith (1987; 1989), the papers on CALL research compiled by Dunkel (1991b), and the collection of international perspectives edited by Pennington and Stevens (1992) summarize work done in the 1980s and provide directions and guidelines for work to be done in the 1990s with implications for both SLL and FLL. As this continues to be the case in recent CALL research, an FLL emphasis in the chapter of non-English L2 instructional context has been maintained exclusively for the discussion of software; whenever the rationale for the design and implementation of FLL software was based on second language acquisition theory or findings from empirical ESL-oriented CALL investigations, the respective research source was examined and cited.

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