Gabriel Stylianides

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The purpose of the current study is to test whether we could create a system where students can learn by teaching a live machine-learning agent, called SimStudent. SimStudent is a computer agent that interactively learns cognitive skills through its own tutored-problem solving experience. We have developed a game-like learning environment where students(More)
This paper describes an application of a machine-learning agent, SimStudent, as a teachable peer learner that allows a student to learn by teaching. SimStudent has been integrated into APLUS (Artificial Peer Learning environment Using SimStudent), an on-line game-like learning environment. The first classroom study was conducted in local public high schools(More)
SimStudent is a computational model of learning with its cognitive fidelity of learning being demonstrated especially in the way it makes human-like errors (Matsuda et al., 2009). Using SimStudent as a teachable agent in an interactive peer-learning environment, we have investigated how tutee (i.e., SimStudent) learning affected tutor (i.e., human student)(More)
To study cognitive and social factors that facilitate the tutor-learning effect, we have developed an on-line game-like environment where students learn algebra equation solving by teaching a computer agent, called SimStudent. SimStudent is a first pedagogical teachable agent that commits to genuine inductive learning and studied in authentic classroom(More)
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