This article explores the utility of content-embedded working memory capacity (WMC) tasks for advancing second language (L2) research. While both complex span and content-embedded tasks implement a dual-task paradigm that requires processing and maintenance of information, they differ in that the former demand maintenance of extraneous memory elements during processing, while the latter demand processing and maintenance of the same elements. Since manipulating information stored in working memory is critical for L2 processing and development, particularly in intentional learning contexts, content-embedded tasks may serve as strong predictors of several linguistic outcomes. We report preliminary evidence suggesting that both content-embedded tasks (available in IRIS [https://www.iris-database.org/details/iv6nR-HD9NQ]) and complex span tasks can be significant predictors of explicit L2 aptitude and L2 reading comprehension, but that content-embedded tasks can show advantages over complex span tasks in some instances. We discuss methodological implications for the measurement of WMC in L2 research.
