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Description
Within the context of globalization, English has become the dominant language in engineering, placing significant pressure on authors to compress dense complex academic knowledge into restricted 150-250 words in abstracts. While previous studies have largely investigated syntactic complexity, especially the exploration of the internal syntactic structures of noun phrases, this study aims to examine the frequency and structural patterns of complex noun phrases in engineering research abstracts; therefore evaluating how grammatical devices facilitate information compression. Through a mixed-methods design, the study manually coded a selected corpus of 26 English engineering abstracts (5,444 words) published from 2015 to 2026. The findings reveal that complex noun phrases are more dominant than simple noun phrases. The use of recursive right-branching complements and adjuncts elements, together with extensive nominalization maintain academic impartiality, while pre-modifiers structures provide information compression to ensure technical accuracy. In addition, pedagogical implications are offered as academic writing instruction in the context of EFL and Content and Language Integrated Learning. Besides, these findings also emphasize the importance of a genre-based approach based on Systemic Functional Linguistics for abstract writing, as well as highlighting the cognitive load caused by excessive structural compression.
Keywords: Noun phrases, syntactic complexity, information compression, engineering abstracts, academic writing
Biography
Nguyen Thi Kim Khanh is an undergraduate student at Hanoi University of Science and Technology (HUST). Her research focuses on syntactic studies, cognitive linguistics, and Systemic Functional Linguistics, particularly how technical knowledge is compressed into academic discourse. Engaged in technical translation and ELT, she bridges theoretical linguistic frameworks with practical applications. She aims to contribute to English language education and applied linguistics in Vietnam.
Nguyen Khanh Ngoc is a senior English Language student at HUST. Her academic interests encompass linguistics, language education, and interdisciplinary research. She actively participates in project-based activities to enhance her analytical and research skills. Ngọc is particularly interested in the intersection of language and emerging technologies like Artificial Intelligence. Dedicated to continuous learning, she aims to contribute to meaningful educational development.
Nguyen Thanh Nam is a fourth-year student at the Faculty of Foreign Languages, HUST. Specializing in language education, he focuses on integrating language learning with technical and STEM contexts. His research highlights pedagogical approaches like lexical simplification and content-based instruction to enhance comprehension. Passionate about teaching, Nam aims to exchange ideas at international conferences to broaden his academic perspective and professional expertise.
Pham Thi Minh Thu is a final-year student majoring in English for Science and Technology at HUST. Her research interests include applied linguistics, second language acquisition, and EFL pedagogy, aiming to improve English education in Vietnam. She has developed solid foundational skills in literature review, survey design, and data analysis. Thu aspires to support the growth of local and international English language research communities.
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