مجید عسگری

مجید عسگری

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۱.

The Role of Transcribing Group Discussion Task in Promoting Autonomy and Oral Proficiency of University EFL Learners(مقاله علمی وزارت علوم)

کلید واژه ها: learner autonomy oral proficiency self - correction peer - correction transcription

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تعداد بازدید : ۴۱۳ تعداد دانلود : ۲۱۷
This study investigated the effect of transcribing group-discussion tasks on the development of university students' autonomy and oral proficiency. A quasi-experimental research design was followed to compare the performances of four groups: two experimental groups and two control groups (each group divided into low and high proficiency students). The study lasted for 12 weeks, and the teacher assigned a classroom oral discussion task in each session. The students were divided into discussion groups of three or four students, with low and high proficiency learners in different groups. The participants had to record their group discussion tasks. Control groups’ students had to submit their recorded conversations to their instructor, but they did not do any post-task activity. However, the experimental groups’ students had to transcribe their recorded speaking tasks, to find their own and their peers' grammatical mistakes, and to correct them. Finally, while working in groups, students discussed the texts and reformulated their mistakes. Employing ANCOVA to analyze the results, researchers found that experimental groups significantly outperformed the students of the control groups on post-tests of oral proficiency and learner autonomy. Thus, transcription followed by reflection on inaccurate production contributed to the superior performance of participants in the experimental groups.
۲.

RePersian - A Fast Relation Extraction Tool in Persian

تعداد بازدید : ۱۳۲ تعداد دانلود : ۷۶
The task of extracting semantic relations from raw data is called relation extraction. One of the most important fields in open information extraction is the automatically extraction of relations in any domain, especially in web mining. There are many works and approaches for relation extraction in English and other languages. Some of these approaches are based on parsing trees. Dependency parsing in the Persian language is difficult and time-consuming, since Persian is a low resource language and has also a dependency grammar and lexical structure, which affects also the speed of relations extraction in Persian. In this paper we will introduce a fast relation extraction method in Persian called RePersian. RePersian is dependent on part-of-speech (POS) tags of a sentence and special relation patterns, which are extracted by analyzing sentence structures in Persian. For finding relation patterns, RePersian searches through POS-tags that are given in regular expression forms. By matching the correct POS pattern to a relation pattern, RePersian extracts the semantic relations in a sentence. We appraise RePersian in two different scenarios on the Dadegan Persian dependency tree dataset. RePersian had on average the precisions 78.05%, 80.4% and 54.85% in finding the first argument on a relation, the second argument and the right relation between them.

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