Current trends in CALL such as mobile learning, gamification, and use of social media appear to represent major shifts in the digital language learning landscape. However, these and other... Show More

Current trends in CALL such as mobile learning, gamification, and use of social media appear to represent major shifts in the digital language learning landscape. However, these and other applications of technology to mediate language learning may be informed by reflecting not only on the present but perhaps more importantly on relevant insights from past research and practice. This article draws on selected studies and the author's experience to lay out five key lessons learned over more than three decades in CALL. These lessons involve understanding: 1) the cycle of technology adoption; 2) the dimensions of technology mediation in the language learning process; 3) the promise and limitations of CALL research; 4) the critical importance of teacher education and professional development in an age of continuous change; and 5) the need for learner training for effective technology use. Teachers, researchers, and developers alike are encouraged to reflect on these lessons as they create and seek to control the technologies, tasks, and activities of the future.

This article explores the theoretical foundations of qualitative research in online language learning. It will look at the distinction between offline and online language learning and discuss... Show More

This article explores the theoretical foundations of qualitative research in online language learning. It will look at the distinction between offline and online language learning and discuss whether different ways of knowledge generation are appropriate for those different learning environments. Quantitative and qualitative methodologies will be examined and their fit with various learning theories evaluated. Fundamental theoretical differences between epistemologies supporting a realist ontology and those favouring relativist ontologies will be presented and set in the context of online language learning research. Finally, an argument will be presented that in a sociocultural framework, going beyond quantitative research approaches is necessary to adequately understand the experiences of learners and teachers who share a common interest in novel digital environments.

One of the greatest impacts of corpus linguistics on language teaching has been in the recognition of the importance of collocation. A very influential guide for language teachers with regard to... Show More

One of the greatest impacts of corpus linguistics on language teaching has been in the recognition of the importance of collocation. A very influential guide for language teachers with regard to teaching collocation has been the Lexical Approach. Activities pointing students to rich collocational information in monolingual dictionaries, in texts and specifically in collocation dictionaries provided ways for language learners to engage with collocation information: to notice, to remember and to acquire. In recent years, there has been a growing interest in Data Driven Learning and new tools are now available to allow students to access collocation information from corpora for themselves. After introducing some pedagogic considerations, this article presents some of the features of The Prime Machine which were developed to support DDL activities focussed on collocation.

While current research on the flipped classroom generally focuses on test results and (or) student/teacher perceptions as a measurement of its pedagogical efficacy, students' adaptation to it and... Show More

While current research on the flipped classroom generally focuses on test results and (or) student/teacher perceptions as a measurement of its pedagogical efficacy, students' adaptation to it and the essential conditions for its application are rarely explored. This exploratory case study aims to rectify this by examining how university students adapted to flipped classrooms implemented in a public university in East China. The findings suggest that while the flipped model is impeded by entrenched polarity between students in terms of their learning dispositions and academic competence, students do develop a prototype of theories of learning, a sense of better self through learning from their peers and an awareness of the importance of intrinsic motivation. A gradualist approach is thus proposed for implementing flipped classrooms, which requires longitudinal studies accordingly to understand its long-term effects on learning behavior hitherto left unexplored.

This study extracts the comments from a large scale of Chinese EFL learners' translation corpus to study the taxonomy of translation errors. Two unsupervised machine learning approaches are used to... Show More

This study extracts the comments from a large scale of Chinese EFL learners' translation corpus to study the taxonomy of translation errors. Two unsupervised machine learning approaches are used to obtain the computational evidences of translation error taxonomy. After manually revision, ten types of English to Chinese (E2C) and eight types Chinese to English (C2E) translation errors are finally confirmed. There probably exists three categories of top-level errors according to the hierarchical clustering results. In addition, three supervised learning methods are applied to automatically recognize the types of errors, among which the highest performance reaches F1 = 0.85 on E2C and F1 = 0.90 on C2E translation. Further comparison to the intuitive or theoretical studies on translation taxonomy shows some phenomenon accompanied by language skill improvement of Chinese learners. Analysis on translation problems based on machine learning provides the objective insight and understanding on the students' translations.