Although restating part of a student's correct response correlates with learning and various types of restatements have been incorporated into tutorial dialogue systems, this tactic has not been tested in isolation to determine if it causally contributes to learning. When we explored the effect of tutor restatements that support inference on student learning, it did not benefit all students equally. We found that students with lower incoming knowledge tend to benefit more from an increased level of these types of restatement while students with higher incoming knowledge tend to benefit more from a decreased level of such restatements. This finding has implications for tutorial dialogue system design since an inappropriate use of restatements could dampen learning.
CITATION STYLE
Jordan, P., Albacete, P., & Katz, S. (2015). Exploring the effects of redundancy within a tutorial dialogue system: Restating students’ responses. In SIGDIAL 2015 - 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference (pp. 51–59). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-4607
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