主講人：Luke Plonsky
主講人簡介
Luke Plonsky (PhD, Michigan State University) is Associate Professor of Applied Linguistics at Northern Arizona University, where he teaches courses in SLA and research methods. His work in these and other areas has resulted in over 90 articles, book chapters, and books. Luke is Senior Associate Editor of Studies in Second Language Acquisition, Managing Editor of Foreign Language Annals, Co-Editor of De Gruyter Mouton's Series on Language Acquisition, and Co-Director of the IRIS Database (iris-database.org). In addition to prior appointments at Georgetown and University College London, Luke has lectured in China, Japan, The Netherlands, Poland, Spain, and Puerto Rico.
1
講座信息
講座時間：2021年12月6日（周一）
下午 1:30-3:00
講座平台：騰訊會議
會議 ID：798 290 829
內容簡介
For decades, researchers in the field of second language acquisition have examined the relationship between individual differences, such as aptitude and motivation, and second language (L2) achievement. These efforts have led to a body of empirical work that is vast and diverse in terms of settings, samples, instruments, and outcomes. This talk will attempt to make sense of this domain by examining the core relationships of interest through the lens of meta-analysis (i.e., a systematic approach to synthesizing findings across a body of empirical studies). More specifically, after situating individual differences in the context of SLA, I will present an overview of meta-analytic findings on a range of individual differences as they relate to L2 achievement. I will also discuss when and why those relations have been found to vary across different methodological and substantive features.
2
講座信息
講座時間：2021年12月7日（周二）
下午 1:30-3:00
講座平台：騰訊會議
會議ID:432 104 306
內容簡介
Research on language learner psychology relies heavily on surveys. Such instruments can be very useful for measuring latent (non-observable) variables such as motivation, anxiety, and grit. They are also popular among researchers because they can be designed in a relatively short amount of time. However, developing psychometrically sound scales for measuring individual difference variables is actually quite challenging and requires great care if we want the measure to yield high-validity data for a given study. This talk will go over some of the major considerations—both conceptual and practical—in designing and developing scales for measuring learner individual differences. Recent examples from L2 research will be used to illustrate the points be made throughout.
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