AIC Seminar Series
Examining the Generality of Self-Explanation on Second Language Learning
| Ruth Wylie | Carnegie Mellon University | |
Notice: Hosted by Vinay Chaudhri
Date: Tuesday June 14, 2011 at 16:00
Location: EJ228 (SRI E building) (Directions)
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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.
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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. Ruths 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, Ruths
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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