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فاطمه اطاعت

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ترتیب بر اساس: جدیدترینپربازدیدترین

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۱.

Heideggerian Space and Time in Ted Hughes’s and Allen Ginsberg’s Poems(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Heidegger Postmodern Poetry Space Time Allen Ginsberg Ted Hughes

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The purpose of the present study is to explore the two concepts of time and space in postmodern lyric poetry of the two poets of the 1950s through the lens of the Heideggerian existential theory of time and space, which regards time as a horizon for understanding Being and distinguishes three different types of space: (1) world-space, (2) regions , and (3) Dasein's spatiality. To fulfill this objective, some selected poems of the two poets, including Allen Ginsberg and Ted Hughes, were analyzed temporally and spatially. The findings suggested that the two poets tend to treat time and space existentially and reject eternality. It was revealed that they are existential poets whose existence is manifested in their quest for identity within the immediate world or the global world as well as their concerns for their homeland and ideals. In their poems, time and space are intermingled with Being and reflect each individual’s relationship with the world. The result of the analysis of poems showed that their poetry is not just the language of imagination and perception, but also the language of existence. The world is regarded as an existential space-time continuum and being-in-the-world is the fundamental ontological situation for Dasein. Accordingly, the world, like poetry, is a disclosure of things in nearness or distance, which matters to human beings
۲.

Addressing Challenges of L2 Grammar Learning with a Focus on English Relative Clauses: AI-supported Language Learning(مقاله علمی وزارت علوم)

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کلیدواژه‌ها: Artificial Intelligence syntax relative clauses AI-Assisted Language Learning

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The present study investigates the challenges of learning English grammar with a focus on the syntactic analysis of relative clauses (RCs) in Persian in contrast to English to identify the most common errors made by Persian learners of English. In addition, it aims to enhance L2 grammar learning and overcome challenges using AI-assisted tools such as Wordtune, Instatext, and ChatGPT in classroom activities. The quantitative data were collected through the RC tests adapted from the models used by Izumi (2003), comprising three test types: sentence combination, interpretation, and grammaticality judgment. These tests were administered before and after the implementation of AI-powered strategies. The result of the tests in intermediate learners revealed that the most recurrent interlingual error was “the use of object pronouns” instead of gaps, while the challenges in “RC reduction” were among the most common intralingual errors. The findings highlight not only the major differences in RC structures between the two languages but also present an innovative approach that uses AI to address these challenges, offering insights for teachers and instructors. Addressing such errors and utilizing technological advances can pave the way for learners and teachers to have more effective learning and teaching strategies.

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