L2 Learners’ Lexical Inferencing:Perceptual Learning Style Preferences, Strategy Use, Density of Text, and Parts of Speech as Possible Predictors

سال انتشار: 1393
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 721

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تاریخ نمایه سازی: 11 تیر 1396

چکیده مقاله:

This study was intended first to categorize the L2 learners in terms of their learning style preferences and second to investigate if their learning preferences are related to lexical inferencing. Moreover, strategies used for lexical inferencing and text related issues of text density and parts of speech were studied to determine their moderating effects and the best predictors of lexical inferencing. To this end, a posttest group design with 142 students studying engineering was adopted for the study. Perceptual style preferences questionnaire was administered to identify the students‟ major learning styles, followed by strategy training for deriving the meaning of unknown words. Finally, lexical inferencing texts were given to the students to study and extract the meaning of unknown words and concurrently determine the type of strategy used for lexical inferencing. The results indicated that a great proportion of students belonged to the kinesthetic category of styles while the predominant treatments in the class were audio-visually structured. The analysis also revealed that tactile, kinesthetic, and group categories of style preferences are meaningfully related. Moreover, it was found that learning style preferences lead to statistically different lexical ineferncing. As for the strategies, the „syntactic knowledge analysis‟ showed the highest correlation with „auditory learners‟. Lexical density and parts of speech were also shown to moderate the effect of perceptual style preferences on lexical ability. On the whole, strategy and perceptual style preferences were found to be the two best predictors of successful lexical inferencing

کلیدواژه ها:

L2 ، lexical inferencing ، parts of speech ، preferences in perceptual learning styles ، strategy training ، text density


Hossein Pourghasemian

Assistant Professor, Qom University of Technology, Iran

Gholam Reza Zarei

Associate Professor, Isfahan University of Technology, Iran

Hassan Jalali

Assistant Professor, Isfahan University of Technology, Iran