CALL and computational linguistics



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CALL and computational linguistics



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 theoretical linguistics with the aim of characterizing a language with computational applications in mind.

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. The computer “understands” the input word by comparing it with a stored answer and gives feedback to the user. Cloze tests work on a similar principle, where the computer compares the words/phrases provided by the learner to a database of correct answers.

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 it 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.] 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.

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 EUROCALL (Europe) and CALICO (USA) have special interest groups (SIGs), respectively devoted to Natural Language Processing (NLP) and Intelligent CALL (ICALL).

Role changes for teachers and students

Teachers

Although the integration of CALL into a foreign language program can lead to great anxiety among language teachers, researchers consistently claim that CALL changes, sometimes radically, the role of the teacher but does not eliminate the need for a teacher altogether.

Instead of handing down knowledge to students and being the center of students’ attention, teachers become guides as they construct the activities students are to do and help them as students complete the assigned tasks. In other words, instead of being directly involved in students’ constructions of the language,

 the teacher interacts with students primarily to facilitate difficulties in using the target language (grammar, vocabulary, etc.) as use the language to interact with the computer and/or other people.

Elimination of a strong teacher presence has been shown to lead to larger quantity and better quality of communication such as more fluidity, more use of complex sentences and more sharing of students’ personal selves.

However, teacher presence is still very important to students when doing CALL activities. Teachers should be familiar enough with the resources to be used to anticipate technical problems and limitations.

 Students need the reassuring and motivating presence of a teacher in CALL environments. Not only are they needed during the initial learning curve, they are needed to conduct review sessions to reinforce what was learned.

Encouraging students to participate and offering praise are deemed important by students. Most students report preferring to do work in a lab with a teacher’s or tutor’s presence rather than completely on their own.

Students

Students, too, need to adjust their expectations of their participation in the class in order to use CALL effectively.

Rather than passively absorbing information, learners must negotiate meaning and assimilate new information through interaction and collaboration with someone other than the teacher, be that person a classmate or someone outside of the classroom entirely.

Learners must also learn to interpret new information and experiences on their own terms.

However, because the use of technology redistributes teachers’ and classmates’ attentions, less-able students can become more active participants in the class because class interaction is not limited to that directed by the teacher.

Moreover more shy students can feel free in their own students'-centered environment.

This will raise their self-esteem and their knowledge will be improving.

If students are performing collaborative project they will do their best to perform it within set time limits.

(from http://en.wikipedia.org/wiki/Computer-assisted_language_learning)

Exercises 1.6.



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