Daniel Schwartz

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This paper discusses Betty’s Brain, a teachable agent in the domain of river ecosystems that combines learning by teaching with self-regulation mentoring to promote deep learning and understanding. Two studies demonstrate the effectiveness of this system. The first study focused on components that define student-teacher interactions in the learning by(More)
This paper describes the use of qualitative reasoning mechanisms in designing computer-based teachable agents that users explicitly teach to solve problems using concept maps. Users can construct the required problem-solving knowledge structures without becoming involved in sophisticated programming activities. Once taught, the agent attempts to answer(More)
The importance of software in daily life for casual and business purposes has led to a strong increase in the formal integration of usability in commercial software development processes. However, usability still appears to be largely an afterthought for Free/Libre/Open Source Software (FLOSS). The intent of this Special Interest Group (SIG) is to encourage(More)
We discuss computer environments that invite students to learn by instructing “teachable agents” (TA’s) who venture forth and attempt to solve problems that require knowledge of disciplines such as mathematics, science or history. If the agents have been taught properly they solve the problems they confront; otherwise they need to be further educated. The(More)
Enclosed please find a preliminary proof of your chapter in Smart Machines in Education (Forbus and Feltovich). These are your first set of proofs—we have reformatted your chapter to fit a 6x9 inch trim size, translated your graphics to incorporate this book’s styles and fonts, and the editor has added queries (usually in red) about particular elements in(More)
This paper extends our previous work on simulation-based Intelligent Learning Environments and SmartTools to computer-based Teachable Agents. Teachable Agents have been inspired by our work in classrooms where students have found it very motivating to teach and help others in problem solving tasks. These interactions also helped students to appreciate(More)
Using hidden Markov models (HMMs) and traditional behavior analysis, we have examined the effect of metacognitive prompting on students’ learning in the context of our computer-based learning-by-teaching environment. This paper discusses our analysis techniques, and presents evidence that HMMs can be used to effectively determine students’ pattern of(More)
Page 1 of 5 Knowledge Engineering for Very Large Decision-analytic Medical Models Marek J. Druzdzel, Ph.D., Agnieszka Onisko, M.S., Daniel Schwartz, M.D., John N. Dowling, M.D. and Hanna Wasyluk, M.D., Ph.D. 1 Decision Systems Laboratory, School of Information Sciences, Intelligent Systems Program, and Center for Biomedical Informatics, University of(More)
A 90 nm CMOS TX path architected for operation without inter-stage SAW filters is shown. The SAW elimination strategy is purely low noise design but the architecture still achieves DG.09 weighted TX current drain of 50 mA from the battery. The combination of a passive interleaved switching mixer plus digital gain control allows 2% EVM at 2 dbm and 4.2% at(More)