Doris B. Chinlisa M. DohmenBritte H. Cheng • Marily A. OppezzoCatherine C. ChaseDaniel L. Schwartz

One valuable goal of instructional technologies in K-12 education is to prepare students for future learning. Two classroom studies examined whether Teachable Agents (TA) achieves this goal. TA is an instructional technology that draws on the social met- aphor of teaching a computer agent to help students learn. Students teach their agent by creating concept maps. Artificial intelligence enables TA to use the concept maps to answer questions, thereby providing interactivity, a model of thinking, and feedback. Elementary schoolchildren learning science with TA exhibited "added- value" learning that did not adversely affect the "basic- value" they gained from their regular curriculum, despite trade-offs in instructional time. Moreover, TA prepared students to learn new science content from their regular lessons, even when they were no longer using the software.