Improving novice Tetris players with feedback from AI model based tutors

Authors
Sibert, Catherine
ORCID
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Other Contributors
Gray, Wayne D., 1950-
Schoelles, Michael J.
Reid, Larry D.
Issue Date
2015-05
Keywords
Cognitive science
Degree
MS
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
Computer based tutoring systems have largely been focused on static tasks, where the tutor guides the student through a single solution. Tutors for dynamic tasks are much more difficult to create, as the solution constantly changes as the task progresses. This study uses Tetris™ as a testbed for a tutor of a complex, dynamic task. Subjects were trained under a number of different feedback conditions using a computer model designed to approximate the behavior of human players. While each feedback system was hypothesized to affect human behavior in a particular way, no significant differences were observed in player behavior after training, but several interesting trends were suggested and continue to be explored.
Description
May 2015
School of Humanities, Arts, and Social Sciences
Department
Dept. of Cognitive Science
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
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