Brain Network Differences in Second Language Learning Depend on Individual Competencies

Integrating new words into an existing semantic network is a core challenge of second language (L2) acquisition. We investigated how evidence-based learning strategies and individual performance shape the neurocognitive dynamics of vocabulary learning. Eighty- three adults with German or French as their native language (L1) learned 48 Finnish (L2) nouns over 14 days using a mobile app that systematically varied retrieval practice, corrective feedback, multisensory learning, and distributed learning. Before and after training, EEG was recorded during a translation recognition task designed to elicit the N400, an index of semantic integration. Vocabulary accuracy increased from 0.41% pre-learning to 75.5% post- learning ( d _z = 3.96), and the N400 incongruity effect increased significantly, F (1, 75) = 99.52, p < .001, η² _g = .32, reflecting successful integration of new L2 words into the mental lexicon. High performers showed larger N400 responses and distinct ERP template-map preponderance (i.e., the proportion of epoch time points assigned to a given template map) indicating more efficient and specialized neural processing. Despite systematic manipulation of learning strategies, no single approach yielded consistent behavioral or neural advantages, suggesting that overall exposure and cumulative practice—rather than any specific strategy— were the key drivers of robust learning. ERP template-map analyses further revealed that learning not only amplified neural responses but also shifted the preponderance of maps in the N400 window, signaling a qualitative reorganization of semantic processing. These findings bridge cognitive neuroscience and language education, suggesting that the depth and success of vocabulary learning may depend more on the degree of integration achieved than on the specific instructional strategy employed.