This study investigates how working memory (WM) capacity and L2 linguistic knowledge affect L2 literal and inferential reading comprehension, considering the presence or absence of background knowledge. Eighty upper-intermediate to advanced adult English learners participated, completing tasks to assess WM capacity, background knowledge, L2 linguistic knowledge, and reading comprehension (both literal and inferential). Stepwise regression analyses revealed that WM capacity had a stronger influence on both literal and inferential comprehension when background knowledge was absent. For literal comprehension, L2 linguistic knowledge was the sole predictor when background knowledge was present, while WM capacity dominated in its absence. Inferential comprehension was consistently predicted by WM capacity, regardless of background knowledge. These findings indicate that WM capacity and L2 linguistic knowledge influence L2 reading comprehension differently depending on background knowledge and the type of comprehension. Implications include incorporating WM training into L2 reading instruction and employing diverse WM assessment methods to measure WM independently of L2 linguistic proficiency.

This study investigated the relative contributions of linguistic knowledge and strategy use to L2 listening success, especially in bottom-up and top-down dominant listening tasks. Participants (n = 130) were Korean college students in a required listening course. The tested variables for linguistic knowledge were sentence processing speed, grammar, receptive vocabulary, and productive vocabulary. Listening strategy use was measured with a metacognitive awareness listening questionnaire. We hypothesized that linguistic knowledge will make greater contributions to Bottom-Up-Listening-Comprehension (BULC) than to Top-Down-Listening Comprehension (TDLC), and different aspects of strategies will be accessed in each comprehension type due to different psycholinguistic features of the tasks. A series of stepwise multiple regressions were conducted and confirmed our prediction. The unique variance explained by linguistic knowledge was 27.8% in BULC, but 22.4% in TDLC. Strategy items that address problem solving and mental translation were significantly related to BULC, while items dealing with directed attention and person knowledge had significant explanatory power for TDLC.