In classroom-based studies, peer tutoring has proved to be an effective learning strategy, both for the tutees and for their peer tutors. Today, the increasingly widespread availability of computers and Internet access in the homes and after-school programs of students offers a new venue for peer learning. In seeking to translate the successes of peer-assisted learning from the classroom to the Internet, one major hurdle to overcome is that of motivation. When teachers are no longer supervising student activity and when participation itself becomes voluntary, peer tutoring protocols may stop being educationally productive. In order to successfully leverage these peer interactions, we must find a way to facilitate and motivate learning among a group of unsupervised peers. In this dissertation, we respond to this challenge by reconceptualizing the interactions among peers within the context of a different medium: that of games. In designing a peer tutoring experience as a two-player game, we gain a valuable set of tools and techniques for affecting student participation, engagement, goals, and strategies.
Our contributions: (1) We define a criteria for games--the Teacher's Dilemma criteria--that motivates players to challenge one another with problems of appropriate difficulty; (2) We show three games that satisfy the Teacher's Dilemma criteria when played by rational players under idealized conditions; (3) We demonstrate, using computer simulations of strategic dynamics, that game-play will converge towards meeting these criteria, through time, under more realistic conditions; (4) We design a suite of software that incorporates a Teacher's Dilemma game into several web-based activities for different learning domains; (5) We collect data from thousands of students using these activities, and examine how the games actually affected the game-play strategy and learning among these students. The game-theoretic analysis establishes the possibility for a game-based mechanism for motivating appropriate challenges, the simulations support the plausibility of this approach given non-optimal players, the implemented software systems demonstrate the scalability of this model, and the data analysis supports the real-world applicability of this game-based approach to motivating appropriate challenges for learning among unsupervised peers.
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