Using spoken language technology for generating feedback to prepare for the TOEFL iBT® test: a user perception study

Abstract

Recent technology advancements have increased the prospects for automated spoken language technology to provide feedback on speaking performance. In this study we examined user perceptions of using an automated feedback system for preparing for the TOEFL iBT® test. Test takers and language teachers evaluated three types of machine-generated feedback: domain sub-scores, task scores, and scores based on individual linguistic features. Results showed that the vast majority of the participants perceived all feedback types to be useful, although the teachers showed slightly more scepticism than the students. We believe that these findings provide initial support for making such feedback available to those preparing for the TOEFL iBT test or other similar tests of spoken language proficiency. Study outcomes also inform our understanding of the role of technology in test preparation and the extent to which the use of technology changes preparation behaviours and preferences.

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