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Using Computer Assisted Language Learning for Improving Learners Linguistic Competence

Authors: Iram Shehzadi Sabir, Ahsan Afzaal;

Using Computer Assisted Language Learning for Improving Learners Linguistic Competence

Abstract

Developing Linguistic competence has always been a problem for second language learners and especially for English learners. Linguistic competence includes lexical, phonological and syntactical knowledge and skills and other dimensions of Language as a system. Learners are not given enough knowledge about how to use the language appropriately and even if they do learn to use it appropriately they are unable to decide when, where and how to use the knowledge. Many language teachers have tried improving learner’s communicative competence in language classrooms by creating situations, or through role plays but the problem remains the same because the real life like situations can never be created in a language classroom. On the other hand, Computer Assisted Language Learning materials use authentic as well as real life situations to improve students Linguistics competence through making learners interact with native English speakers, by listening to authentic dialogue and then responding to it, by reading authentic material close to social life and then responding to it either orally or in the written form etc. It not helps students to use language correctly but also appropriately because language learned through CALL is unconscious. Based upon data collected through questionnaires, observation sheet and interviews; current research has found that most of the students were satisfied with learning language through CALL instead of the traditional language classroom. Not only they enjoyed learning a language but improved their language skills and especially listening and speaking skills.

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Keywords

Computer Assisted Language Learning; Learners' Linguistics Competence

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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