EUROCALL 2014

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Language Practice and Tutorial CALL

Tutorial CALL—the interaction of language learners with the computer—has changed from a mainstay in computer-assisted language learning to a fringe aspect of its research and development in the last two decades. This is in stark contrast to a renewed emphasis on instructed language learning with practice and awareness-raising activities in both applied linguistics research and practical language teaching methodology. To improve the quality of the learner computer interaction, its central components—corrective and preemptive feedback, contextualization and tailoring, and (metalinguistic) text augmentation and feature-based retrieval—need to be enhanced.

Tutorial CALL (Hubbard & Braidin-Siskin, 2004)—the interaction of language learners with the computer—has changed from a mainstay in computer-assisted language learning to a fringe aspect of its research and development in the last two decades. This is in stark contrast to a renewed emphasis on instructed language learning with practice and awareness-raising activities in both applied linguistics research and practical language teaching methodology. To improve the quality of the learner computer interaction, its central components—corrective and preemptive feedback, contextualization and tailoring, and (metalinguistic) text augmentation and feature-based retrieval—need to be enhanced. I will argue in this context that human language technologies (Heift & Schulze, 2007; Schulze, 2000, 2001) have the—as yet largely unrealized—potential to help ameliorate these core components of tutorial CALL. In the course of my presentation, this argument will be exemplified in two ways: by discussing (1) broader language-learning activities and tasks which can be facilitated for learners and instructors through the use of these technologies, and by reviewing (2) technologies that are suitably robust for useful employment in language learning contexts. I will also draw attention to implications for CALL research that relies on the longitudinal study of complex systems (Larsen-Freeman & Cameron, 2008).

Author(s):

Mathias Schulze    
Waterloo Centre for German Studies
University of Waterloo
Canada

Mathias (Mat) Schulze is an Associate Professor of German and the director of the Waterloo Centre for German Studies in Ontario, Canada. His main research interests are the application of Artificial Intelligence research findings to CALL (ICALL) and the complex nature of language learning in online and hybrid courses. Together with Bryan Smith, he edits the CALICO Journal.

 

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