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AIC Seminar Series

Examining the Generality of Self-Explanation on Second Language Learning

Ruth WylieCarnegie Mellon University

Notice:  Hosted by Vinay Chaudhri

Date:  2011-06-14 at 16:00

Location:  EJ228 (SRI E building)  (Directions)

   Abstract

Prompting students to self-explain during problem solving has proven to be an effective instructional strategy across many domains. However, despite being called a “domain general” strategy, very little work has been done in areas outside of math and science. Thus, it remains an open question whether the self-explanation effect will hold in new domains where acquiring explicit knowledge is not a pedagogical goal, like second language grammar learning. To address this and related questions, I have developed a suite of tutoring systems to teach English as a Second Language (ESL) students the English article system (when to use “a”, “an”, “the” or no article at all). The tutoring systems have been the basis for a series of five randomized controlled experiments in adult ESL classrooms. Results on both immediate and long-term retention measures show that, similar to findings in math and science domains, self-explanation is effective in aiding learning of second language grammar. However, unlike in math and science, prompting students to self-explain during grammar learning is inefficient compared to practice alone. These studies demonstrate the importance of tempering generalizations about learning in cognitive and educational psychology with more precise claims and supporting theory. More generally, these studies are a nice demonstration of how educational technology can be used to run tightly controlled, finely instrumented, studies within existing courses.

   Bio for Ruth Wylie

Ruth Wylie is a PhD student in the Human-Computer Interaction Institute at Carnegie Mellon University and a fellow in the IES-funded Program for Interdisciplinary Education Research. She received her undergraduate degree in Cognitive Science at the University of California, Berkeley and spent two years working as a foreign language teacher in rural Japan. Ruth’s research focuses on understanding human learning and how to improve it using technology-based instructional experiments to explore the generality of instructional principles. Specifically, she has conducted the first series of studies to investigate the effects of prompted self-explanation on second language grammar learning. As her results from language learning differ from those previously seen in math and science domains, Ruth’s work demonstrates the importance of understanding the nature or representation of the target knowledge when designing effective instruction. In her work, Ruth takes an interdisciplinary approach that integrates methods and theory of human-computer interaction, learning sciences, and cognitive psychology.

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