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Intelligent computer-assisted language learning

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Intelligent Computer Assisted Language Learning (ICALL), or Intelligent Computer Assisted Language Instruction (ICALI), involves the application of computing technologies to the teaching and learning of second or foreign languages.[1][2] ICALL combines Artificial intelligence with Computer Assisted Language Learning (CALL) systems to provide software that interacts intelligently with students, responding flexibly and dynamically to student’s learning progress.[2][3]

Natural language processing (NLP) and Intelligent tutoring systems (ITS) are prominent computing technologies in artificial intelligence that inform and influence ICALL.[4][5] Other computing technologies applied to ICALL include Knowledge representation (KP), Automatic Speech Recognition (ASR), Neural networks, User modelling, and Expert systems. In relation to language learning, ICALL utilizes linguistic theory and theories of second-language acquisition in its pedagogy.[4][5]

History

ICALL developed from the field of Computer Assisted Language Learning (CALL) in the late 1970s[1] and early 1980s.[4] ICALL is a smaller field, and not yet fully-formed.

Following the pattern of most language learning technologies, English is a prominent language featured in ICALL technology.[6] ICALL programs have also been developed in languages such as German,[7] Japanese,[7] Portuguese,[7] Mandarin Chinese,[8] and Arabic.[6] ICALL systems are also contributing to the learning of languages that are not as accessible to learn (due to a lesser amount of language resources), or less commonly learned languages, such as Cree.[3]

Features

Intelligent CALL is sometimes called parser-based CALL, due to the heavy reliance that ICALL has on parsing.[4] An example of the function of parsing in an ICALL software is a parser detecting errors in the syntax and morphology of sentences freely generated by student users. After using parsing to find any errors, ICALL can provide corrective feedback to students.[4] Parsing is considered a task of natural language processing.

The ability for students to receive feedback on random, uniquely produced sentences places ICALL in a more engaging teacher role. If students are struggling in certain areas, some ICALL systems will invent new sentences or questions in those areas, giving students more practice.[4] Basically, ICALL is meant to intelligently adapt to student learning needs as a student progresses; this often means (partially or wholly) fulfilling a tutor or teacher role.[7][9] Programs that attempt to fulfill this role are categorized as tutorial ICALL.[1]

Non-tutorial ICALL systems include various language tools and dialogue systems,[1] such as a digital interlocutor.[2] Programs for automatically evaluating student-written essays have also been invented,[4] such as the E-rater.[10]

Limitations

ICALL technology still has many issues and limitations, due to the recency of artificial intelligence being integrated into CALL systems, and the complexity of this enormous task.[1] Artificially intelligent educational software should do its best to encompass the linguistic knowledge and pedagogy of a language teacher in order to resolve these issues.[9] This includes tracking student learning, giving feedback, creating new challenging material in response to student’s needs, understanding effective teaching strategies, and be programmed to detect linguistic errors (grammar, spelling, semantics, morphology, and so on).[4][9]

Additionally, ICALL systems take a long time to develop, and must consult professionals in many disciplines.[9] Programming ICALL software is a necessarily multi-disciplinary project.[7]

Further research and developments in ICALL will benefit the fields of applied linguistics, computational linguistics, artificial intelligence, educational technology, to name a few. ICALL will also expand current knowledge about second language acquisition.[4] Despite its limitations, ICALL is a worthwhile field, especially as technology progresses.[7]

See also

References

  1. ^ a b c d e Contemporary computer-assisted language learning. Thomas, Michael, 1969-, Reinders, Hayo., Warschauer, Mark. London: Bloomsbury Academic. 2012. ISBN 978-1-4411-1300-9. OCLC 820029337.{{cite book}}: CS1 maint: others (link)
  2. ^ a b c Gamper, Johann; Knapp, Judith (2002). "A Review of Intelligent CALL Systems". Computer Assisted Language Learning. 15 (4): 329–342. doi:10.1076/call.15.4.329.8270. ISSN 0958-8221.
  3. ^ a b Bontogon, Megan; Arppe, Antti; Antonsen, Lene; Thunder, Dorothy; Lachler, Jordan (2018). "Intelligent Computer Assisted Language Learning (ICALL) for nêhiyawêwin : An In-Depth User-Experience Evaluation". Canadian Modern Language Review. 74 (3): 337–362. doi:10.3138/cmlr.4054. ISSN 0008-4506.
  4. ^ a b c d e f g h i Heift, Trude. (2007). Errors and intelligence in computer-assisted language learning : parsers and pedagogues. Schulze, Mathias, 1962-. New York: Routledge. ISBN 978-0-203-01221-5. OCLC 191541349.
  5. ^ a b Matthews, Clive (1993). "Grammar Frameworks in Intelligent CALL". CALICO Journal. 11 (1): 5–27.
  6. ^ a b Shaalan 1, Khaled F (2005). "An Intelligent Computer Assisted Language Learning System for Arabic Learners". Computer Assisted Language Learning. 18 (1–2): 81–109. doi:10.1080/09588220500132399. ISSN 0958-8221.{{cite journal}}: CS1 maint: numeric names: authors list (link)
  7. ^ a b c d e f Höhn, Sviatlana,. Artificial companion for second language conversation : chatbots support practice using conversation analysis. Cham, Switzerland. ISBN 978-3-030-15504-9. OCLC 1105896323.{{cite book}}: CS1 maint: extra punctuation (link) CS1 maint: multiple names: authors list (link)
  8. ^ Chen, Nancy F.; Wee, Darren; Tong, Rong; Ma, Bin; Li, Haizhou (2016-11-01). "Large-scale characterization of non-native Mandarin Chinese spoken by speakers of European origin: Analysis on iCALL". Speech Communication. 84: 46–56. doi:10.1016/j.specom.2016.07.005. ISSN 0167-6393.
  9. ^ a b c d Bailin, Alan; Levin, Lori (1989). "Introduction: Intelligent Computer-Assisted Language Instruction". Computers and the Humanities. 23 (1): 3–11. ISSN 0010-4817.
  10. ^ Attali, Yigal; Burstein, Jill (2006-02-01). "Automated Essay Scoring With e-rater® V.2". The Journal of Technology, Learning and Assessment. 4 (3). ISSN 1540-2525.
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