A balancing act: how can intelligent computer-generated feedback be provided in learner-to-learner interactions?

Abstract

Task-based synchronous computer-mediated communication (CMC) may represent an optimal psycholinguistic environment for form-meaning connections, but learners do not receive feedback from a trusted authority. Intelligent computer-assisted language learning (ICALL) provides feedback, but the encouragement of communicative interaction remains largely unexplored. To combine the benefits of ICALL and CMC, we are designing a parser-based system that provides feedback on particle usage for first-year L2 Korean learners while they chat in CMC. Both to facilitate the use of a new orthography by beginning learners and to make processing feasible for the ICALL system, we guide the content of the activity by using picture-based information-gap tasks and a game record, and we control the range of allowable learner input by using a word bank. These constraints enable the system to address L2 errors in meaningful, goal-driven interactions.