Informing Academic Writing Pedagogy through the Study of Phrase-frames

Abstract

Second Language Development (SLD) research has investigated aspects of complexity, accuracy, and fluency (CAF) to understand how English language learners (ELLs) develop linguistic faculties related to language production, especially in academic writing (Biber & Gray, 2010; Biber, Gray & Ponpoon, 2011; Kyle & Crossley, 2018; Lu & Ai, 2015). Contributing to the current body of SLD research, this study addresses complexity in expert academic argumentative essays by investigating language at the phrasal level through phrase-frames (PFs). Phrase-frames are fixed or semi-fixed syntactic structures with a variable slot that might be considered another measure of syntactic complexity. This study aimed to identify if native and non-native expert writers in the Michigan Corpus of Upper-Level Student Papers (MICUSP) displayed significant differences in their use of these frames concerning their predictability, variability, and function. Results of the study indicated expert academic writers in this corpus use highly variable, highly unpredictable structures which confirm the complexity, elaboration, and explicitness unique to the academic register. Understanding of these register features through the identified PFs was used to develop sample pedagogical materials to promote more complex writing in academic genres.

A Corpus-based Analysis of Rhetorical Moves and P-frames in an Omani Learner Corpus of Research Project Abstracts

“…Frequency and range thresholds for retrieving multiword units were applied in order to exclude items which may reflect the idiosyncratic choices of individual writers. Previous studies have set frequency cut offs for p-frames at various | Research Papers levels and number of occurrences in the corpus, for example 16 pmw (per million words) for 5 grams and 12 pmw for 6 grams (Lu et al, 2018), and ranging from one occurrence (Walcott, 2021) to five (Casal & Kessler, 2020). Dispersion thresholds have also been based on various types of measurements such as the number of texts (e.g., five texts in Casal & Kessler, 2020; three or more texts in Lu et al, 2018), and distribution across sub-corpora (two disciplines in Walcott, 2021; two or more disciplines in Lu et al, 2018).…”