Second Workshop on Studying the Language of Young Learners

Studying the Language of Young Learners: Methodological Advances and Challenges

Research on young second language (L2) learners, as well as young learner (inter-)language specifically, has gained increasing attention in recent years, driven by calls for greater diversity and representativeness in both Second Language Acquisition (SLA) and Learner Corpus Research (LCR). Although a growing number of learner corpora are available (Fernández & Davis, 2021), corpora representing young learner language, broadly defined, remain comparatively rare. While empirical findings from young learners are of exceptional theoretical and applied importance, they also raise distinct methodological challenges at every stage of the research process, from study design and data elicitation to annotation, analysis, and interpretation (Granger, 2015; Myles, 2015, 2021; Tracy-Ventura & Paquot, 2021).

This workshop focuses explicitly on these methodological issues. It is intended as an interdisciplinary forum for researchers working with young learner populations, typically situated in institutional (primary or secondary school) contexts, to exchange insights, innovations, and best practices that advance the methodological foundations of our field (Gilquin, 2015, 2021; Paquot & Plonsky, 2017).

We invite single- or multiple-authored papers that address methodological aspects of research on young learner language, including but not limited to:

• Corpus design and compilation for young learner data (ethical considerations, sampling, metadata, longitudinal vs. cross-sectional designs) (Gilquin, 2015; Granger & Paquot, 2017; Paquot et al., 2024).
• Task design and elicitation methods, including age-appropriate, engaging, or multimodal tasks (Cameron, 2001; Pinter, 2017; Ellis, 2003).
• Annotation challenges (e.g., handling non-target-like or emergent language, multimodal learner output, interlanguage features, discourse-pragmatic annotation) (Lüdeling & Hirschmann, 2015; MacWhinney, 2000; Werner, 2017).
• Analytical approaches and reflections, such as:
• Statistical and computational techniques suited for unbalanced or sparse data (Gries, 2015; Alexopoulou et al., 2017).
• Frameworks for modelling developmental trajectories (Biber et al., 2020; Housen & Kuiken, 2009; Pallotti, 2020).
• Methodological triangulation, including integration of learner corpora with questionnaires, observations, eye-tracking, keystroke logging, or psycholinguistic experiments  (Meunier & Littré 2013; Marsden et al., 2016).
• Replicability and transparency in studies with young learners  (Marsden et al., 2016; Paquot & Plonsky, 2017).
• Data management and ethics, including consent procedures, anonymization, and working with educational administrators and institutions
• Technology-enhanced approaches,  including digital recording environments, automatic annotation tools, as well as NLP applications for child/learner language (Wittenburg et al., 2006).