The FaCT System is a general-purpose application to provide practice for learners in various domains. Practice in these domains takes the form of a sequence of discrete drill trials, each of which includes immediate corrective feedback for errors. This sequence of practice trials is selected with an algorithm that uses a cognitive model of skill learning and forgetting to predict the optimal item to practice for each trial. Although the system currently uses the ACT-R model for its declarative memory predictions and trial selections (Anderson & Schooler, 1991; Pavlik Jr. & Anderson, 2005), the FaCT architecture is designed to house any model that produces dependent measures that can be used to select practice (e.g., latency and probability correct). The FaCT System is written mainly as a Java applet and is delivered over the web to learners and experimental subjects when they navigate to a webpage where the Java applet is located.
- Anderson, J. R., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2(6), 396-408.
- Pavlik Jr., P. I. (in press). Timing is an order: Modeling order effects in the learning of information. In F. E., Ritter, J. Nerb, E. Lehtinen & T. O'Shea (Eds.), In order to learn: How order effects in machine learning illuminate human learning. New York: Oxford University Press.
- Pavlik Jr., P. I., & Anderson, J. R. (2005). Practice and forgetting effects on vocabulary memory: An activation-based model of the spacing effect. Cognitive Science, 29(4), 559-586.