Yingzhao Chen explores how language learners use interactive tools to best learn new vocabulary when reading online

Yingzhao Chen joined Michigan State University’s Second Language Studies (SLS) program in Fall 2018 with a focus on interdisciplinary research centered around second language learning and processing, as well as cross-linguistic influence. She is particularly interested in what types of instruction improve vocabulary learning and how the types of instruction may impact the lexical representations of the newly learned words in learners’ mental lexicon. Prior to joining the SLS program, she worked as an EFL teacher in Beijing and received a MA in Second Language Acquisition from the University of Maryland after finishing her BA in English Language and Literature from Sun Yat-sen University in China.

Yingzhao’s recent work includes conducting a multisite preregistered replication study on vocabulary learning with collaborators are from Europe, North American, and Asia, titled “First language effects on incidental vocabulary learning through bimodal input: A multisite, preregistered, and close replication of Malone (2018)”. Yingzhao and her collaborators are replicating a study on vocabulary learning through multimodal input. In addition, they intend to examine how learners’ first language backgrounds affect their learning through multimodal input. The proposal of the study has been accepted to a special issue of Studies in Second Language Acquisition, to be published in 2024.

She is also currently working on her dissertation, “Comparing L1 and L2 Glosses in Vocabulary Learning from Digital Reading”. Her dissertation explores how hyperlinked glosses (i.e., short definitions of words) written in learners’ first or second language influence vocabulary learning from reading. The amount of time learners spend on each gloss is tracked and learning gains are measured in terms of learners’ speed and accuracy in recognizing and recalling the newly learned words. The study investigates the effects of (a) target word frequency in texts, (b) learners’ gloss engagement, and (c) L2 proficiency. Yingzhao hopes that the findings from her study will benefit learners, teachers, and digital learning platform designers and shed light on how to design materials best for the development of word knowledge that can be retrieved fluently in everyday tasks such as reading, with implications for learners, teachers, and digital learning program designers. Her dissertation has recently won her the 2021 Duolingo Research Grant, an award launched in 2020 to support student research about language learning and teaching with technology. She has also received a 2022 NFMLTA/MLJ Dissertation Writing Support Grant for $2,500.00.