The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…

Vocabulary researchers have started expanding their assessment toolbox by incorporating timed tasks and psycholinguistic instruments (e.g., priming tasks) to gain insights into lexical development (e.g., Elgort, 2011; Godfroid, 2020b; Nakata & Elgort, 2020; Vandenberghe et al., 2021). These timed sensitive and implicit word measures differ…

This dissertation aims to identify the locus of L2 processing inefficiency. Previous studies suggest that non-native processing is a specific result of an inefficient predictive mechanism that limits the ability of learners to generate linguistic expectations (Gruter, Rohde, & Schafer, 2014; 2016). Thus, this study employs two distinct online…

Indirect metaphors are pervasive in everyday language: People talk about "long" vacations, "short" tempers, and "colorful" language. But, why do we use concrete lexical items that are associated with the physical world when we talk about abstract, or non-physical, concepts? A potential answer is provided by proponents…