Affiliations: Department of EECS/ISIS, Box 351824, Station B,
Vanderbilt University, USA. E-mail: [email protected]
Note: [] Krittaya Leelawong is now with the Computer Science Program,
Division of Pure and Applied Sciences, Mahidol University, Salaya Campus,
Thailand
Abstract: The idea that teaching others is a powerful way to learn is
intuitively compelling and supported in the research literature. We have
developed computer-based, domain-independent Teachable Agents that students can
teach using a visual representation. The students query their agent to monitor
their learning and problem solving behavior. This motivates the students to
learn more so they can teach their agent to perform better. This paper presents
a teachable agent called Betty's Brain that combines learning by
teaching with self-regulated learning feedback to promote deep learning and
understanding in science domains. A study conducted in a 5th grade science
classroom compared three versions of the system: a version where the students
were taught by an agent, a baseline learning by teaching version, and a
learning by teaching version where students received feedback on self-regulated
learning strategies and some domain content. In the other two systems, students
received feedback primarily on domain content. Our results indicate that all
three groups showed learning gains during a main study where students learnt
about river ecosystems, but the two learning by teaching groups performed
better than the group that was taught. These differences persisted in the
transfer study, but the gap between the baseline learning by teaching and
self-regulated learning group decreased. However, there are indications that
self-regulated learning feedback better prepared students to learn in new
domains, even when they no longer had access to the self-regulation
environment.
Keywords: Learning by teaching, teachable agents, metacognitive strategies, self-regulated learning
