Exploring multiple profiles of L2 writing using multi-dimensional analysis

In this paper, we explore the application of corpus-based multi-dimensional analysis (MDA) pioneered by Biber (1988, 1995, 2006) in understanding microscopic linguistic variation in an L2 writing corpus. The primary goals of our study are: (1) to identify the functional dimensions of L2 academic essays from the corpus collected for this special issue of the Journal of Second Language Writing, and (2) to analyze linguistic variation in the corpus across parameters of time and average assessment scores (in language, vocabulary, and total average score). The corpus was tagged for part-of-speech and additional semantic categories (e.g., semantic categories of verbs and nouns) using the Biber tagger (Biber, 2006). Rates of occurrence were computed for over 80 linguistic features across 209 essays based on tag counts for each text. The values of these variables were then subjected to an exploratory factor analysis. A total of four functional dimensions were identified and interpreted. These are: (1) Involved vs. Informational Focus, (2) Addressee-Focused Description vs. Personal Narrative, (3) Simplified vs. Elaborated Description, and (4) Personal Opinion vs. Impersonal Evaluation/Assessment. Overall, our study shows a successful application of MDA on a micro-level producing a range of functional profiles along different parameters in L2 writing.