Julian Levine: The Role of Contextualization in L2 Vocabulary Measurement

March 7, 2023

Tuesday, March 7, 2023

2:00 - 4:00 PM (PST) at Berkeley Way West 1204 and via Zoom

Open to GSE faculty, students, and community.

Request a zoom link from convenors@bear.berkeley.edu

Abstract:

Vocabulary knowledge undergirds every major language skill (reading, listening, writing, speaking) and is essential to achieving high levels of proficiency in a language. Given the importance of vocabulary in language acquisition, valid and reliable instruments for its measurement are necessary. Yet despite the fact that such assessments have been in use for decades, they have typically not been subjected to extensive and systematic validation procedures. As such, lots of questions remain unanswered; one particular issue that has not received sufficient attention concerns the role of contextualization in vocabulary measurement. Should vocabulary words be tested in context, such that items mirror target language use situations? Or is it better to test words in isolation, so as to mitigate the influence of confounding facets? Three hypotheses are considered regarding context-dependence and vocabulary measurement: that contextualized and decontextualized knowledge lie on a spectrum of word knowledge, that words vary in their degree of context-dependence, and that contextualized and decontextualized items measure different constructs. These ideas require further investigation to provide more accurate measures of vocabulary in L2 learners.

About the speaker:

Julian Levine earned an MA in Education (Social Research Methodologies) from UC Berkeley in 2022. As an educator, he taught English in South Korea for two and a half years, and also spent a year and a half tutoring calculus at the UC Berkeley Athletic Study Center. He is currently pursuing a PhD in Education at the UCI School of Education, with a specialization in human development. As a member of the Digital Learning Lab at UCI, he is conducting research on the Converse to Learn project, investigating the impact of AI-powered conversational agents on children's learning outcomes. His research focuses on vocabulary, reading comprehension, and language acquisition.