Non-selective language activation in L2 lexical inference and text comprehension: Comparing skilled and less-skilled readers

Abstract

Non-selective language activation refers to the automatic co-activation of L1 and L2 information. In L2 reading, the activated L1 information can be utilized to different degrees to facilitate lexical inference and text comprehension. The current study examined the contributions of L1-L2 translation and lexical inference to text comprehension. Hierarchical regression models showed that in general, lexical inference contributed to text comprehension over L1-L2 translation. The results indicated that L2 learners did not use activated L1 information mechanically. That is because successful lexical inference incorporates learners’ ability to strategically utilize contextual information and integrate word meanings to update the context. The study further classified the participants into two groups using k-means cluster. Among the less skilled group of participants, L1-L2 translation was related to both lexical inference and text comprehension. However, lexical inference was not significantly related to text comprehension. Among the more skilled group of participants, lexical inference predicted text comprehension only after school, grade to start English learning, and L1-L2 translation were controlled for. The results of the two groups demonstrated that while L1 information was utilized in both groups, strategic and effective usage of information in two languages differentiated skilled L2 readers from less skilled L2 readers.

Keywords

• Non-selective language activation
• Translation equivalent
• Lexical inferencing
• L2 reading