موضوع پايان نامه هاي لاتين Many scholars have studied lexical bundles and provided ben.... Many scholars have studied lexical bundles and provided beneficial information about their functional and structural patterns in written and spoken registers. There have been many studies analyzing the use of lexical bundles in different disciplines, genres, and registers. However, due to the difficulty of collecting spoken corpora, not much has been done in regard to understanding the use of lexical bundles in academic lectures. Thus, this study looked at the use of lexical bundles and their variations in the academic lectures of hard and soft sciences. For this purpose, two corpora, including 14 lectures in hard sciences and 15 lectures in soft sciences were selected from the Michigan Corpus of Academic Spoken English. The corpora were analyzed by AntConc 4.1.0 (Anthony, 2019), and 42 lexical bundles in soft sciences and 44 lexical bundles in hard sciences were identified. Also, the lexical bundles were analyzed structurally and functionally, according to the taxonomies introduced by Biber et al., (2004). In terms of function, the use of lexical bundles in these two divisions did not show any significant difference. There were 11 stance expressions in hard sciences, and 17 in soft sciences. The results also showed 21 discourse organizers in hard sciences, and 13 in soft sciences. Both corpora had 12 referential bundles. Thus, the functional patterns of lexical bundles in the two divisions of hard and soft sciences were not significantly different. Similarly, the two corpora did not show any significant difference in terms of structure: there were 31 verb phrase fragments in hard sciences, and 28 in soft sciences. The analysis also showed that there were 5 dependent clause fragments in hard sciences, and 2 in soft sciences. Also, there were 8 noun and prepositional phrase fragments in hard sciences, and 12 in soft sciences. Regarding the implications, the English teachers can use the results of this study to help the learners prepare themselves for the challenges of academic situations. Learners can also use this research for their self-study to boost their academic performance. Further, the recognition of frequent lexical bundles of each discipline helps the learners in their future lecture presentations, contributing to the expression of meanings.

from : Many scholars have studied lexical bundles and provided ben.... until : Many scholars have studied lexical bundles and provided beneficial information about their functional and structural patterns in written and spoken registers. There have been many studies analyzing the use of lexical bundles in different disciplines, genres, and registers. However, due to the difficulty of collecting spoken corpora, not much has been done in regard to understanding the use of lexical bundles in academic lectures. Thus, this study looked at the use of lexical bundles and their variations in the academic lectures of hard and soft sciences. For this purpose, two corpora, including 14 lectures in hard sciences and 15 lectures in soft sciences were selected from the Michigan Corpus of Academic Spoken English. The corpora were analyzed by AntConc 4.1.0 (Anthony, 2019), and 42 lexical bundles in soft sciences and 44 lexical bundles in hard sciences were identified. Also, the lexical bundles were analyzed structurally and functionally, according to the taxonomies introduced by Biber et al., (2004). In terms of function, the use of lexical bundles in these two divisions did not show any significant difference. There were 11 stance expressions in hard sciences, and 17 in soft sciences. The results also showed 21 discourse organizers in hard sciences, and 13 in soft sciences. Both corpora had 12 referential bundles. Thus, the functional patterns of lexical bundles in the two divisions of hard and soft sciences were not significantly different. Similarly, the two corpora did not show any significant difference in terms of structure: there were 31 verb phrase fragments in hard sciences, and 28 in soft sciences. The analysis also showed that there were 5 dependent clause fragments in hard sciences, and 2 in soft sciences. Also, there were 8 noun and prepositional phrase fragments in hard sciences, and 12 in soft sciences. Regarding the implications, the English teachers can use the results of this study to help the learners prepare themselves for the challenges of academic situations. Learners can also use this research for their self-study to boost their academic performance. Further, the recognition of frequent lexical bundles of each discipline helps the learners in their future lecture presentations, contributing to the expression of meanings.