Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…

In order to develop pragmatic competence in a language other than our own (L2), it is important to have enough knowledge of the cultural norms of the target language and enough opportunities to interact with a wide range of speakers to deploy different speech acts, registers, levels of politeness, conversational moves, and the like. The…

The new era of mobile computing promises greater variety in applications, highly improved usability, and speedier networking. The 3G iPhone from Apple is the poster child for this trend, but there are plenty of other developments that point in this direction. Previous surveys, in LLT, and by researchers at the UK's Open University, have…

Online reading is evolving beyond the perusal of static documents with Web pages inviting readers to become commentators, collaborators, and critics. The much-ballyhooed Web 2.0 is essentially a transition from online consumer to consumer/producer/participant. An online document may well include embedded multimedia or contain other forms of…

Linguistic computing can make two important contributions to second language (L2) reading instruction. One is to resolve longstanding research issues that are based on an insufficiency of data for the researcher, and the other is to resolve related pedagogical problems based on insufficiency of input for the learner. The research section of the…