Abstract
To date, a growing body of second language (L2) research has investigated linguistic alignment as a pedagogical intervention, focusing on L2 learners’ alignment behaviors in task-based interactions (e.g., Jung, YeonJoo, YouJin Kim & John Murphy. 2017. The role of task repetition in learning word-stress patterns through auditory priming tasks. Studies in Second Language Acquisition 39(2). 319–346; Kim, YouJin, YeonJoo Jung & Stephen Skalicky. 2019. Linguistic alignment, learner characteristics, and the production of stranded prepositions in relative clauses: Comparing FTF and SCMC contexts. Studies in Second Language Acquisition 41(5). 937–969). Linguistic alignment refers to a tendency where one speaker’s utterances align with particular language features of those of the other speaker in dialogue. The current study investigated how L2 speakers’ alignment behaviors differ in natural dialogues between L2-L1 and L2-L2 dyads in terms of language style (i.e., stylistic alignment) and the role of non-linguistic factors in the occurrence of stylistic alignment. The study analyzed a corpus of 360 texts using a computational tool. Results showed that stylistic alignment occurred to a greater extent in the L2-L2 dyad than in the L2-L1 dyad with respect to the word range, word frequency, word imageability, and proportion of bigrams proportion produced by the interlocutors. Furthermore, findings demonstrated the degree of stylistic alignment on each of the four selected lexical features was affected by numerous factors including age, group membership, nonnative speaker status, familiarity between interlocutors, and linguistic distance between L1 and L2. The effect of each factor on stylistic alignment in conversation is discussed in detail.
About the authors
YeonJoo Jung is an assistant professor in the Department of English Education at Pusan National University in South Korea. Her interests include the application of experimental techniques from psychology to second language (L2) processing and acquisition research as well as the use of natural language processing tools in assessing linguistic features of written and spoken data produced by L2 learners.
Scott Crossley is a Professor at Georgia State University. His interests include the application and development of natural language processing tools in educational technology. He has published articles on the use of natural language processing tool to examine lexical acquisition, writing proficiency, reading comprehension, discourse processing, language assessment, and automatic feedback in intelligent tutoring systems.
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