Markov Logic: An Interface Layer for Artificial Intelligence
Markov Logic: An Interface Layer for Artificial Intelligence
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Many subjects such as languages, history, biology, geography, law, and medicine require the memorization of large numbers of unstructured facts and vocabulary. While there are many techniques and tools for memorizing such information, sustaining motivation remains a major barrier towards progress in these subjects. In order to help fill this gap, we brainstormed, experimented, and paper-prototyped to create Picard, a Facebook game that intertwines creative and social elements to turn rote learning into a creative, engaging experience. Picard, inspired by Pictionary, encourages players to come up with creative stories and images to help remember a particular card. Players compete and cooperate with their friends on Facebook to create the most memorable and funny mnemonics, called Picards, gaining points when they help themselves or others remember flashcards. Players use these Picards to learn and prove knowledge of the material at spaced intervals, which research has shown to be maximally effective for learning. Our game is the novel combination of an established learning methodology with player creativity and social support for learning. Picard increases player investment in the process of learning by allowing players to create and share useful visual mnemonics, while at the same time motivating and structuring their study habits through spaced-repetition quizzes.