Grammatical complexity has been considered as an important research construct closely related to second language (L2) writing development. Although theoretical models were developed to demonstrate what grammatical complexity is, few studies have been conducted to analyze how this construct is represented from an empirical perspective. This chapter presents a data-driven investigation on the representation of grammatical complexity with an exploratory factor analysis (EFA). The investigation is based on (1) a corpus of scientific research reports written by Hong Kong students in an English Medium Instruction (EMI) scientific English course, and (2) an EFA, which is a statistical approach to uncover an underlying structure of a phenomenon, which fits this research purpose well. A corpus has been built with the science writing from EMI undergraduate students in Hong Kong. After corpus cleaning, Second Language Syntactic Complexity Analyzer – a software – was applied to output the values of fourteen effective measures of grammatical complexity for running the EFA in SPSS, and a step-by-step instruction was described in the chapter. The final model includes three latent factors: clausal (subordination) complexity, nominal phrasal complexity, and coordinate phrasal complexity. This EFA model is generally consistent with the argument of investigating grammatical complexity as a multidimensional construct (Biber et al., 2011; Norris & Ortega, 2009). In the end, we highlighted the research and pedagogical implications that readers should pay attention to when the EFA is applied in other EMI contexts in the future.

This chapter reviews corrective feedback studies that focused on the effectiveness of oral corrective feedback on specific morphosyntactic targets in English as a second language. Specifically, this chapter addressed the question of whether the grammatical complexity of the target structure investigated affects the effectiveness of corrective feedback as an instructional intervention. Not only was complexity defined on the basis of formal criteria, but it also incorporated a semantic component from the perspective of the redundancy and transparency of the form–meaning mapping. Eleven studies published between 2006 and 2018 qualified for the research synthesis. The overall findings indicated that, in general, corrective feedback is more effective for simpler grammatical features. The chapter concludes that type of language feature is a relevant dimension to consider in the effectiveness of corrective feedback. The chapter calls for future research on the role of grammatical complexity using categorization methods that consider both formal and semantic complexity features.