SLS Corpus Lab Meeting 
Wednesday, January 31, 2024, 9:00 – 10:00 EST
In-person: Wells 243B (with breakfast)
Online: https://msu.zoom.us/my/charlenepolio

Please join us for a discussion of lab activities and two talks.  Everyone is welcome. 

‘If you are only knowing these three things, you can enjoy your trip’: A collostructional analysis of verbs in the progressive and non-progressive construction in L1 and L2 Korean.  

Steve Gagnon, Michigan State University, Ph.D. student in Second Language Studies 

Abstract: This corpus-based study explores verbs which are used in the progressive -ko iss construction across L1 and L2 Korean varieties. I take a quantitative approach using collostructional analysis (Stefanowitsch & Gries, 2003) to assess association strengths between certain verbs and their preference for either the progressive or non-progressive construction in the Sejong Corpus (provided by the National Institute of Korean Language). A qualitative exploration of instances of -ko iss which differ between L1 and L2 Korean due to typological differences is included. Preliminary results can help shed a light on notable variation patterns in the psychological associations of verbs in the tense/aspect system in L1 and L2 Korean (Stefanowitsch, 2006) and aid in creating teaching materials to address such variation in the classroom. 

Introducing TURLEC: A Learner Corpus for Turkish L2 

Yigit Savuran, Anadolu University and University of Florida (formerly), Michigan State University, Visiting scholar in Second Language Studies 

This study provides a detailed account of TURLEC – Turkish Learner Corpus. Building on my Ph.D work, which aimed to reveal proficiency descriptors for four skills at various CEFR levels, the main motivation to build a learner corpus is to outline what words learners are actually able to use at those levels. With the written and spoken products of learners of Turkish L2 at the university level coming from various countries with numerous L1 backgrounds, TURLEC entails 735 texts and ~104.000 tokens. After rigorous anonymization, annotation and error-tagging efforts, TURLEC reveals ~18000 words with 3584 lemmas, which will further be profiled based on the CEFR levels. As accessible literature indicates, TURLEC is the first learner corpus built to offer a vocabulary profile for Turkish L2, which is an ever-growing field of study with booming number of students.