These claims from the promotional materials of well-known digital companies sound as if they have found the philosophers’ stone to language learning, the perfect answer and practical solution to the puzzles and challenges of learning new languages. True, this is advertising language, but, still one wonders as a researcher whether – in the face of such claims – there is any point in continuing research on the nature of bilingualism and in studying the mechanisms of language learning.

The current issue of BLC seeks to address the topic of digital language learning from the perspective of bilingualism and second language (L2) acquisition/learning research. The main contribution is Li and Lan's (Reference Li and Lan2022a) Keynote article which presents an overall picture of how digital language learning (DLL) applications and other technology-enhanced innovations such as mobile computing, VR, and digital games offer new – potentially promising – ways to assist L2 acquisition and foreign language teaching and instruction. The Keynote article makes use of insights from bilingualism and second language research as well as from psycholinguistic and neuro-cognitive studies of language acquisition to provide an analytical framework for understanding DLL as a new avenue for language learning.

Li and Lan's keynote article elicited 11 commentaries from well-known experts. Many commentators praise the keynote article for synthetizing different research strands and for offering a theoretical framework for DLL studies. At the same time, commentators take issue with some of the claims and assumptions made by the Keynote authors. Several authors question the view that by providing simulated or real contexts for L2 learning, DLL enables adult L2 learning to occur in a similar fashion as child L1 acquisition, the best contextualized learning scenario according to the Keynote authors. Han (Reference Han2022) challenges this view and argues instead that L2 language teaching needs to acknowledge and implement the robust differences between child L1 and adult L2 acquisition that have been reported in much previous SLA research. Similar concerns with immersion-based language learning are raised by other commentators (Chien, Hung, Ku, Wu & Chan, Reference Chien, Hung, Ku, Wu and Chan2022; Lantolf, Reference Lantolf2022; Mayer, Reference Mayer2022; Spector, Reference Spector2022). A second criticism concerns the opposition set out in the Keynote article between modern DLL and ‘traditional’ language teaching, which portrays language teaching as decontextualized, classroom-based, translation-based, and teacher-centred, which is an outdated of view of current language teaching according to some (Godwin-Jones, Reference Godwin-Jones2022; Han, Reference Han2022; Lantolf, Reference Lantolf2022). A third set of comments extends the Keynote article in a number of ways. Caldwell-Harris (Reference Caldwell-Harris2022) illustrates how contextualization and VR may create interesting learning environments. Two commentaries point to the needs of previously neglected potential users of DLL applications, Puebla and García (Reference Puebla and García2022) to older adults and Ma and Yan (Reference Ma and Yan2022) to high-performance young students. Finally, two commentators raise additional perspectives for DLL, Chen (Reference Chen2022) notes the potential benefits of robot-assisted language learning and MacWhinney (Reference MacWhinney2022) calls for a shared platform for collaborations between technology developers and L2 researchers.

Li and Lan (Reference Li and Lan2022b) use their Authors’ Response for a rebuttal of the critical points raised by the commentators. They reiterate their claim from the Keynote article that ‘the best contextualized learning scenario is one that can enable adult L2 learning to occur like in child L1 learning’. Li and Lan (Reference Li and Lan2022b) also maintain their view that ‘… students acquire language better through contextualized learning…’, but they admit that adults may also learn something from traditional language learning. Finally, Li and Lan (Reference Li and Lan2022b) acknowledge that future development of DLL technology and research needs to take into consideration the needs of different learner types and of new technological affordances for personalized learning such as those pointed out in a number of commentaries. The impression that remains after reading the Keynote article, the commentaries, and the authors’ response is that DLL does indeed provide promising new ways for L2 learning, but that a lot more research is needed before DLL tools and applications can fully realize their potential.

We hope our readers will enjoy the keynote article together with the commentaries and the Author's Response as well as the interesting regular research articles presented in the current issue.