Using tracking technologies to study the effects of linguistic complexity in CALL input and SCMC output

Abstract

With more integration of CALL in the language classroom, it is becoming increasingly important to understand the impact of CALL features on L2 performance. Tracking technologies provide an unobtrusive glimpse into learners’ behaviors in CALL (Fischer, 2007). Collentine (2011) employed tracking technologies to study the relationship between learners’ exploratory behaviors in a task-based 3D world and the linguistic complexity of their SCMC production. Yet, learners’ exploratory behaviors actually increased their exposure to input, and the combination of exploratory behaviors and input was hypothesized to yield more complexity in output. This study uses tracking technologies to focus explicitly on this input-output relation. A total of 60 third-year university learners of Spanish participated in CALL tasks entailing a 3D world – containing embedded tracking technologies – to discover clues about a crime; then, dyads chatted in SCMC to solve the crime. The study employed three regression analyses to study the relationship between linguistic complexity in input from the 3D world and SCMC production. The results suggest that, for learners to produce linguistic complexity while engaged in task-based CALL, learner input must contain both certain linguistic features and generous amounts of information.