Analysis of noun + noun sequences in discipline-specific published research articles

dc.contributor.advisor Gray, Bethany
dc.contributor.advisor Ranalli, Jim
dc.contributor.advisor Cotos, Elena
dc.contributor.advisor Huffman, Sarah
dc.contributor.advisor Ballester, Cristina Pardo
dc.contributor.author Bordbarjavidi, Fatemeh
dc.contributor.department Department of English
dc.date.accessioned 2023-08-25T19:17:33Z
dc.date.available 2023-08-25T19:17:33Z
dc.date.issued 2023-08
dc.date.updated 2023-08-25T19:17:33Z
dc.description.abstract Nouns as nominal pre-modifiers (e.g., agency relationships) are considered one component of grammatical complexity in writing (Biber et al., 2011). Previous research has primarily focused on how the frequency of noun+noun sequences vary across disciplines (Gray, 2015). However, there is a lack of research documenting other characteristics of noun+noun sequences in discipline-specific writing and no pedagogical list of noun+noun sequences. This study aimed to explore the use of noun+noun sequences in Applied Linguistics, going beyond frequency variation to consider the range, complexity, and functional/semantic characteristics of noun+noun combinations across the disciplines. A methodology is introduced to develop a discipline-specific pedagogical list of noun+noun sequences (NNSL). The study investigated 640 texts (4,744,248 million words) from ApLing corpus stratified across eight sub-disciplines (pragmatics, CALL, SLA, assessment, ESP, corpus linguistics, sociolinguistics, pronunciation). Python scripts were developed to calculate the frequency and range of noun+noun sequences. Frequent noun+noun sequences (normed frequency >= 10 pmw; range = at least in 20 texts; occurred at least in 5 texts in 2 sub-disciplines) were then analyzed according to: a) The semantic types of nouns (following Thompson & Gray, 2021); b) The functional relationship between the head noun and modifying noun (following Biber et al. 1999); and c) The use of morphologically complex nouns. The results of analyzing 216 noun+noun sequences (overall frequency= 91,154) showed that Applied Linguists use noun+noun sequences, as well as nominalizations very commonly. Semantic analysis of the noun+noun sequences showed that abstract nouns are more common as head noun (N2) (e.g., target language), while communication nouns are more common as pre-modifying noun (N1) (e.g., language test). The combinations of semantic categories showed that different combinations are possible. The most common combinations are communication + abstract as in language policy. For functional analysis, new label categories (genitive, statistical relationship, and other) were created and added to Biber et al.’s (1999) framework to analyze noun+noun sequences that did not fit into any existing category. The functional relationship analysis showed that identity, (e.g., language community), content (e.g., subject areas), purpose (e.g., learning process), and objectives (e.g., discourse analysis) are the most common logical relationship between the nouns in this field. The study has implications and suggestions for pedagogical purposes of using NNSL in EAP courses in the field, and also provide a sample ready-to use lesson plan on the use of NNSL.
dc.format.mimetype PDF
dc.identifier.doi https://doi.org/10.31274/td-20240329-61
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/aw4N7Jyr
dc.language.iso en
dc.language.rfc3066 en
dc.subject.disciplines Linguistics en_US
dc.subject.keywords academic writing en_US
dc.subject.keywords corpus linguistics en_US
dc.subject.keywords Data-Driven Learning en_US
dc.subject.keywords grammatical complexity en_US
dc.subject.keywords noun+noun sequences en_US
dc.title Analysis of noun + noun sequences in discipline-specific published research articles
dc.type dissertation en_US
dc.type.genre dissertation en_US
dspace.entity.type Publication
relation.isOrgUnitOfPublication a7f2ac65-89b1-4c12-b0c2-b9bb01dd641b
thesis.degree.discipline Linguistics en_US
thesis.degree.grantor Iowa State University en_US
thesis.degree.level dissertation $
thesis.degree.name Doctor of Philosophy en_US
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