‘Sometimes maligned for its allegedly behaviorist connotations but critical for success in many fields from music to sport to mathematics and language learning, practice is undergoing something of a revival in the applied linguistics literature’ (Long & Richards 2007, p. xi). This research timeline provides a systematic overview of the contributions of computer-assisted language learning (CALL) to the role, nature, and development of individual practice in language learning. We focus on written language practice in Tutorial CALL, corrective feedback and language awareness-raising in Intelligent CALL (ICALL), and individualization of the learning process through tailoring of learning sequences and contingent guidance.

Presented at the American Association for Applied Linguistics Annual Conference, Denver, Colorado; 21 March 2009.

In this paper we present the Report Manager of our Web-based tutoring system for German – an interface to a persistent learner report that students can inspect and manipulate. The learner report collects and retains information on the learner’s progress and performance that is saved between visits. It also provides access to a journaling system that records prior inputs along with detailed error analysis, and a bookmarking system that tracks exercise completion. Finally, results can be printed or emailed to an instructor. In the Fall semester 2003, we conducted a study with 87 learners of German to investigate how their study habits are affected by an inspectable learner report. Our study indicates that students reviewed their learner profiles frequently – 33 times on average over the course of a semester – and that 70% of the students repeated exercises after having inspected their learner profile. So, while detailed user profiles and performance tracking are invaluable tools for CALL researchers, our study suggests that students also utilize and are influenced by the information.

This paper describes a study in which we investigated the effects of corrective feedback on learner uptake in CALL. Learner uptake is here defined as learner responses to corrective feedback in which, in case of an error, students attempt to correct their mistake(s). 177 students from three Canadian universities participated in the study during the Spring semester 2003. The study considered three feedback types: Meta-linguistic, Meta-linguistic + Highlighting, and Repetition + Highlighting. Study results indicate that feedback that provides an explanation of the error and also highlights the error in the student input (Meta-linguistic + Highlighting) is most effective at eliciting learner uptake. The study also considered two learner variables, gender and language proficiency. Our data suggest that none of the two learner characteristics has a significant impact on student responses to corrective feedback.

This paper discusses learners’ responses to metalinguistic feedback and their strategies in error correction in a Web-based Intelligent Language Tutoring System (ILTS) for German. The system consists of a grammar and a parser which analyses student input and provides error-specific feedback to grammar and vocabulary exercises. Furthermore, the ILTS employs a Student Model that matches feedback messages to learner expertise and provides remedial exercises. Two beginner German classes, 33 students in all, used the ILTS for grammar practice, submitting a total of 4405 sentences for analysis. The results indicate that for the vast majority of sentences (79.5%) students read and attended to system feedback. Moreover, as iterations increased students paid more attention to the feedback messages.