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Category: Vol. 1 : No. 1, Sep 2012
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Volume 1 (1); September 15, 2012

Research Paper

Analytic View toward Lexical Network Structure in Language Learning besides First Language.

Sayedi R and Azizi M.

Int. J. Appl. Ling. Stud., 1(1): 01-05, 2012; pii:S232251221200001-1

ABSTRACT

This study is an attempt to demonstrate that an artificial neural network meant to simulate the potential learning mechanisms of second language learners was able to produce and not produce a small selection of nouns and verbs in a similar manner as L2 learners using four features related to lexical network models. This study helps support the potential for lexical network models to explain lexical production in L2 learners. Earlier studies have found empirical support for lexical networks in L2 learners. However, these past studies used either Boolean models or computational tools to investigate lexical growth. The studies did not use lexical features related to network models to simulate lexical production and learning. Thus, this study provides a broader perspective on how lexical features can inform lexical production. Lexical Network Theory asserts that the semantic portion of the lexicon is best seen as a network of word senses, where each sense is connected by links to other semantically-related senses of the same word, and, indirectly, to other words in the same semantic field. To this end, a neural network was trained to simulate L2 word production using a variety of word properties related to connectionist networks. Theories of connectionism and their links to artificial neural networks are relatively new. While neural network models exploring lexical acquisition in bilingual learners are common, few researchers in second language acquisition have examined neural network approaches to lexical production. When L2 neural network models have been explored, they have been in the absence of actual linguistic features or through the use of non-learning networks. Our purpose is to demonstrate how word properties that are linked to network models can be used to simulate word production by second language learners. We first did a corpus analysis of both L1 and L2 spoken discourse to select produced and unproduced words. Then we constructed an artificial neural network with the outputs for the words as either produced or unproduced and tested whether the network can correctly categorize the words based on word properties. The study demonstrates that artificial neural networks can categorize produced and unproduced words to a significant degree.
Key words: Hypernymy, Polysemy, Concreteness, Meaningfulness

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Research Paper

Finding Equivalence in Medical Texts: A Contrastive Study.

Sorayyaie Azar A and Moghimi Dehkordy A.

Int. J. Appl. Ling. Stud., 1(1): 06-10, 2012; pii:S232251221200002-1

ABSTRACT

Translation process is global knowledge process. Finding equivalences in order to have better comprehension in all of the texts, either scientific or unscientific, it needs to gain more knowledge and information on source language and target language. This study focuses on findings equivalences on some medical sentences especially on technical words which were not translated in Persian language as well. In the findings section the examples show that the translated technical words are completely different from the original concept and meanings of the target language. The data is from the book included the translated articles about the Anastasia. By considering and contrasting them from the medical Dictionary and having an interview with an informant specialist, we noticed that there are equivalences for these technical words but physicians prefer using the technical words among their professional office talk.
Key words: Translation, Equivalence, Medical Texts 

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Research Paper

The effect of personality on the English as foreign language learners’ performance on listening comprehension: extroverts vs. Introverts.

Araghi SM, Fam A and Ziaei E.

Int. J. Appl. Ling. Stud., 1(1): 11-16, 2012; pii:S232251221200003-1

ABSTRACT

This study explores the relationship between affective variables and listening strategies. The main objective is to investigate the relationship between extroversion/introversion personality variables and the English as Foreign Language learners’ performance on listening strategies. The study was conducted on a group of 140 male and female Iranian EFL learners from two different Azad University, i.e. Tehran-South and Roudehen who participated and answered a Nelson proficiency test. 40 homogeneous subjects chosen from each university responded to Eysenck Personality Questionnaire and based on the result of this questionnaire, the subjects were divided into extroverts and introverts. IELTS listening comprehension test as the final exam of for their course was developed to elicit the listening scores of each group. Finally, to observe whether or not there is any significant difference between the two groups in term of listening, the collected data was put in SPSS 18 and the results showed that Extroversion/Introversion personality trait has significant effect on the EFL learners’ listening, i.e. Extroverts’ perform better than Introverts.
Key words: Introverts, Extroverts, Listening Strategies

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Research Paper

Studying students’ awareness of their linguistic progress.

Asoudeh F.

Int. J. Appl. Ling. Stud., 1(1): 17-21, 2012; pii:S232251221200004-1

ABSTRACT

This paper attempts to study the capacity for self-evaluation of university students undergoing tests involving linguistic and formal reasoning. Subjects were asked to estimate the number of correct answers and subsequently to compare their performance with that of their peers. We divided the subjects into three groups on the basis of performance: poor, middle and top performers. The results demonstrate that all the subjects in all tests showed good awareness of their level of actual performance. Analyzing comparative assessments, the results reported in literature by Kruger and Dunning were confirmed: poor performers tend to significantly overestimate their own performance whilst top performers tend to underestimate it. This can be interpreted as a demonstration that the accuracy of comparative self-evaluations depends on a number of variables: cognitive and metacognitive factors and aspects associated with self-representation. Our conclusion is that cognitive and metacognitive processes work as “submerged” in highly subjective representations, allowing dynamics related to safeguarding the image one has of oneself to play a role.
Key words: Metacognition, Self- Evaluation, Cognitive Performance, University Students, Self- Image.

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Research Paper

The role of task complexity on EFL learners’ oral production in English language institutions.

AAzizi M, Asoudeh F, Sorayaie Azar A. 

Int. J. Appl. Ling. Stud., 1(1): 22-27, 2012; pii:S232251221200005-1

ABSTRACT

This study attempts to examine the effect of simple and complex tasks on Iranian L2 learners’ oral production in English language institutes in EFL context by measuring three aspects of learner production: accuracy, fluency, and complexity. The findings suggest that the cognitive complexity of a particular task influences the nature of learner oral production (Deng, 2005). Studies in task-based language learning and assessment claim that the cognitive complexity of a specific task influences the learners’ task performance. The effect of task type the complexity of tasks on L2 learners’ performance in second language, in terms of fluency, accuracy, and complexity has recently attracted the attention of many researchers (Ellis, 2005; Yuan & Ellis, 2003; Skehan & Foster 2001; Robinson 2001 a, 2005, 2007). This study is specifically concerned with the design features of oral task which contributes to their different degrees of accuracy and fluency. In this paper we noticed that learners cannot give full attention to the three aspects of language production simultaneously and a focus on one aspect is at the expense of the others. Therefore, some tasks may lead learners to prioritize fluency, others to prioritize complexity or accuracy of production.
Key words: Simple Task, Complex Task, Cognitive Complexity, Accuracy and Fluency

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