Agents represent a technology that emphasizes the social aspects of learn-ing
as much as the cognitive processes. Over several years, our research team has
developed Bet-ty’s Brain, a multi-agent environment that utilizes the
learning-by-teaching paradigm to help middle school students learn science. In
Betty’s Brain, students teach a virtual Teachable Agent (TA) called Betty using
a visual causal map representation. Once taught, Betty, can answer ques-tions,
explain her answers, and when requested by the student take quizzes, which are
a set of questions created and graded by a mentor agent named Mr. Davis. The
TA’s quiz performance helps students indirectly assess their own knowledge, and
it also motivates them to learn more and improve their TA’s quiz scores.
Overall, the learning and teaching task is complex, open-ended, and
choice-rich. Thus, learners must employ a number of cognitive and metacognitive
strategies to succeed in their tasks. Experimental studies run in middle school
classrooms show that students learn science content and do develop some
metacognitive strategies through interactions with Betty and Mr. Davis.
researchers have also developed Teachable Agent systems, and I will discuss
some of them. I will briefly discuss how Teachable Agent technologies have
evolved over the years, and look into the future, where advanced AI and Machine
Learning technologies can support Teach-able Agents that van interact in more
natural ways with their human instructors.