Exploring the effectiveness of a novel feedback mechanism within an intelligent tutoring system

Abstract

The purpose of this study was to explore the effectiveness of a new feedback mechanism within an intelligent tutoring system called AutoTutor LITE. Participants were randomly assigned to one of three feedback manipulation conditions within the context of complex scientific material: 1 learners' characteristics curves; 2 random; 3 no feedback. Results revealed that the participants receiving the new feedback mechanism LCC showed significantly higher learning gains when compared to the random feedback or no feedback manipulations. Additionally, there were no differences discovered between random feedback and no feedback. Interpretation and implications of results are discussed.