CALL and Computational Linguistic

CALL and computational linguistics are separate but somewhat interdependent fields of study. The basic goal of computational linguistics is to “teach” computers to generate and comprehend grammatically-acceptable sentences… for purposes of translation and direct communication with computers where the computer understands and generates natural language. Computational linguistics takes the principles of

A very simple example of computers understanding natural language in relation to second language learning is vocabulary drill exercises. The computer prompts the learner with a word on either the L1 or target language and the student responds with the corresponding word.

On a superficial level, the core issue for humans and computers using language is the same; finding the best match between a given speech sound and its corresponding word string, then generating the correct and appropriate response. However, humans and machines process speech in fundamentally different ways. Humans use complex cognitive processes, taking into account variables such as social situations and rules while speech for a computer is simply a series of digital values to generate and parse language.journal=Language Learning and Technology |volume=2 |issue=1 |pages=45–60 |id= |url= |accessdate= 2007-12-02 }} For this reason, those involved in CALL from a computational linguistics perspective tend to be more optimistic about a computer’s ability to do error analysis and other pedagogical tasks than those who come into CALL via language teaching. ^[2]

The term Human Language Technologies is often used to describe some aspects of computational linguistics, having replaced the former term Language Engineering. There has been an upsurge of work in this area in recent years, especially with regard to machine translation and speech synthesis and speech analysis. The professional associations EUROCALLCALICO (USA) have special interest groups (SIGs), respectively devoted to Natural Language Processing (NLP) and Intelligent CALL (ICALL). See Module 3.5 at the ICT4LT website for further information. (Europe) and

[edit] Theoretical basis for CALL instruction design

Computers have become so widespread in schools and homes and their uses have expanded so dramatically that the majority of language teachers now think about the implications. Technology can bring about changes in the teaching methodologies of foreign language beyond simply automating fill-in-the-gap exercises. ^[3] The use of the computer in and of itself does not constitute a teaching method, but rather the computer forces pedagogy to develop in new ways that exploit the computer's benefits and that work around its limitations. ^[1] To exploit the computers’ potential, we need language teaching specialists who can promote a complementary relationship between computer technology and appropriate pedagogic programs. ^[3]

A number of pedagogical approaches have developed in the computer age, including the communicative and integrative/experimentative approaches outlined above in the History of CALL. Others include constructivism, whole language theory and sociocultural theory although they are not exclusively theories of language learning. With constructivism, students are active participants in a task in which they “construct” new knowledge based on experience in order to incorporate new ideas into their already-established schema of knowledge. Whole language theory postulates that language learning (either native or second language) moves from the whole to the part; rather than building sub-skills like grammar to lead toward higher abilities like reading comprehension, whole language insists the opposite is the way we really learn to use language. Students learn grammar and other sub-skills by making intelligent guesses bases on the input they have experienced. It also promotes that the four skills (reading, writing, listening and speaking) are interrelated. ^[4] Sociocultural theory states that learning is a process of becoming part of a desired community and learning that communities rules of behavior. ^[5]

What most of these approaches have in common is taking the central focus away from the teacher as a conveyor of knowledge to giving students learning experiences that are as realistic as possible, and where they play a central role. Also, these approaches tend to emphasize fluency over accuracy to allow students to take risks in using more student-centered activities, and to cooperate, rather than compete. ^[3] The computer provides opportunity for students to be less dependent on a teacher and have more freedom to experiment on their own with natural language in natural or semi-natural settings.