ليست موضوع پايان نامه هاي لاتين 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. Multimodal discourse analysis (MDA) has gained increasing attention in recent years, particularly in the context of critical discourse analysis (CDA), ideology, and social semiotics. However, despite the growing body of literature, there remains a significant gap in understanding how different modes of communication—such as text, imagery, and gestures—interact with and are influenced by ideological frameworks, especially over time and with the advent of new technologies. This study aims to address this gap by conducting a comprehensive scoping review of MDA literature from 2010 to 2023. The review draws on a corpus of peer-reviewed journal articles that focus on multimodal discourse analysis, critical discourse analysis, and social semiotics. The study employed a qualitative methodology, utilizing thematic analysis to identify key trends, ideologies, and frameworks within the reviewed literature. This approach allowed for an in-depth examination of how meaning was constructed and conveyed through diverse communicative modes across various social, cultural, and technological contexts. The findings revealed a predominant reliance on qualitative methods, particularly content and semiotic analysis, while highlighting a lack of longitudinal studies and limited exploration of emerging digital tools. These insights underscore the need for further research into the relationship between multimodality and ideology, as well as the implications of new communication technologies. Ultimately, this review provides a critical foundation for advancing both theoretical and practical approaches to multimodal discourse analysis.

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.