Digital Language Learning (DLL): Insights from Behavior, Cognition, and the Brain

Ping Li*, Yu Ju Lan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)


How can we leverage digital technologies to enhance language learning and bilingual representation? In this digital era, our theories and practices for the learning and teaching of second languages (L2) have lagged behind the pace of scientific advances and technological innovations. Here we outline the approach of digital language learning (DLL) for L2 acquisition and representation, and provide a theoretical synthesis and analytical framework regarding DLL's current and future promises. Theoretically, DLL provides a forum for understanding differences between child language and adult L2 learning, and the effects of learning context and learner characteristics. Practically, findings from learner behaviors, cognitive and affective processing, and brain correlates can inform DLL-based language pedagogies. Because of its highly interdisciplinary nature, DLL can serve as an approach to integrate cognitive, social, affective, and neural dimensions of L2 learning with new and emerging technologies including VR, AI, and big data analytics.

Original languageEnglish
Pages (from-to)361-378
Number of pages18
Issue number3
Publication statusPublished - 2022 May 13


  • bilingual representation
  • digital language learning
  • neurocognition of language
  • second language acquisition
  • social learning

ASJC Scopus subject areas

  • Education
  • Language and Linguistics
  • Linguistics and Language


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