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)
We have built Sim Student, a computational model of learning, and applied it as a peer learner that allows students to learn by teaching. Using Sim Student, we study the effect of tutor learning. In this paper, we discuss an empirical classroom study where we evaluated whether asking students to provide explanations for their tutoring activities facilitates(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)
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)
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)