Published online by Cambridge University Press: 21 April 2006
This article describes how information gap tasks can be designed as instruments for data collection and analysis and as treatments in interaction research. The development of such tasks is illustrated and data are presented on their role in drawing learners' attention to second language (L2) forms that are difficult to notice through classroom discussion alone. Because the tasks presented here are closed-ended and precision oriented and require the exchange of uniquely held information, they promote modified interaction among participants and orient their attention to form, function, and meaning. These processes can be observed by the researcher during task implementation. Thus, the tasks reduce researcher dependence on externally applied treatments and analytical instruments not integral to the interaction itself. To illustrate this methodology in use, we report on a study in which six pairs of intermediate-level English L2 learners carried out three types of information gap tasks in their classrooms. They first read passages on familiar topics, whose sentences contained L2 forms that were low in salience and difficult to master but developmentally appropriate. To complete the tasks, the learners were required to identify, recall, and compare the forms, their functions, and their meanings. Data revealed close relationships among learners' attentional processes, their recall of form, function, and meaning, and the interactional processes that supported their efforts.In carrying out the design and implementation of the tasks in this article, we have worked most closely with Kristine Billmyer and MaryAnn Julian, and also Jin Ahn, Marni Baker-Stein, Mara Blake-Ward, Lyn Buchheit, Junko Hondo, Sharon Nicolary, and Jack Sullivan. Among the many graduate students who have provided assistance are Vivian Chen, Yao Chen, Yi-Chen Chen, Cathy Fillman, Leslie Harsch, Hanae Katayana, Ji Hwan Kim, Atsuko Matsui, Lisa Mullen, Amy Nichols, Matthew Salvatore, Margaret Skaarup, Lauren Smith, Cheng-Chen Tseng, Debbie Tsui, Melissa Yi, Wei-Chieh Yu, and Mira Yun.